using digital media technologies to improve museum archival monitoring systems · 2017. 9. 20. ·...

Using Digital Media Technologies to Improve Museum Archival Monitoring Systems

A Thesis

Submitted to the Faculty

of

Drexel University

by

Patrick A Dean

in partial fulfillment of the

requirements for the degree

of

Masters of Science in Digital Media

August 2017

DM Tech to Improve Archival Monitoring Systems

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Abstract

Archival collections composed of vulnerable materials require careful monitoring of temperature

and humidity. Archivists currently use a variety of data loggers to monitor relative temperature

and humidity. Normal data logging systems including the HOBO and eClimateNotebook use

expensive digital data loggers whose data is typically converted from an excel spreadsheet to a

basic line graph. This project sought to convene with the archival department at the Academy of

Natural Sciences in Philadelphia, PA to see how improving the collection and visualization of

environmental data for museum archives. With assistance from a group of experts from the

Academy of Natural Sciences, this project developed a low-cost data logging system using

Arduino microcontrollers to collect the data, and a custom-built web based interface to visualize

the data. We believe that this created an improved data logging system that allowed live data to

be accessed via web interface while also generating new visualization methods that highlighted

problem areas within the archival collection facilities.


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Acknowledgments

I would like to take this opportunity to thank my committee for all of their guidance

during the course of my research project: Professor Finamore for overseeing my project and

answering my endless number of questions, Professor Wagner for his guidance with my

research, and Dr. Rice for her guidance with core aspects of the project.

I would also like to give thanks to my mother, father and brother for their support and

understanding throughout this whole process. It was thanks to you that I was able to realize my

dream of working in the field of digital media, and for that you have my eternal gratitude.


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Table of Contents ABSTRACT..................................................................................................................................................3 ACKNOWLEDGMENTS...........................................................................................................................4 1. INTRODUCTION ...................................................................................................................................6 2. RELATED WORKS..............................................................................................................................15

2.1 SIMILAR PROJECTS.............................................................................................................................16 2.2 WHY USE DIGITAL TECHNOLOGIES WITHIN ARCHIVES? ....................................................................18 2.3 PAST/PRESENT RESEARCH OVERLAPS ...............................................................................................20

3. RESEARCH QUESTION .....................................................................................................................24 4. METHODOLOGY ................................................................................................................................25

4.1 SPARKFUN THING ..............................................................................................................................26 4.2 WEB BASED VISUALIZATIONS............................................................................................................34 4.3 EXPERT PANEL...................................................................................................................................40

5. ANALYSIS .............................................................................................................................................42 5.1 EXPERT PANEL SELECTION ...............................................................................................................44

5.1.1 First Round - Background Information .....................................................................................44 5.1.2 Second Round - Current Implementation ..................................................................................45 5.1.3 Third Round - Enviro-Alert Survey............................................................................................48

6. DISCUSSION.........................................................................................................................................52 6.1 SIGNIFICANCE ....................................................................................................................................55

7. CONCLUSION ......................................................................................................................................57 8. FUTURE WORK...................................................................................................................................58 BIBLIOGRAPHY......................................................................................................................................64 APPENDIX.................................................................................................................................................65


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1. Introduction

Due to physical composition, environmental and storage conditions, artifacts including

papers, books, manuscripts, fabrics, paintings, earthenware, wood products, and ornaments

degrade over time. For archival collections, protecting precious and culturally valuable artifacts

against this deterioration presents an urgent problem as HVAC systems are often not controlled

directly by the archivists (Conrad, 1999). In an attempt to mitigate harmful environmental

storage conditions and slow the process of deterioration, archivists use data loggers to monitor

storage conditions and capture environmental data. By having access to this data, archivists can

then make adjustments within their storage areas to better preserve their artifacts. Data loggers

are a key interest point from the digital media perspective, as they provide key information that

directly aid archivists and preservationists monitoring and visualizing environmental degradation

(Conrad, 1999).

Within archives, historical societies and museums, one of the key standards for collecting

environmental data is through an instrument called the hygrothermograph.


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Figure 1

Image of a hygrothermograph. Conservation Notes: Get to Know a Hygrothermograph. Digital image. Art Gallery of Ontario. 27 Aug. 2012. Web. 7 July 2017. <http://artmatters.ca/wp/2012/08/conservation-notes-get-to-know-a-hygrothermograph/>.

While this device provides critical temperature and relative humidity information in the form of a

line graph, the device contains a few issues that make it a rather unsavory choice in terms of data

loggers. The hygrothermograph records on a paper medium that often outputs environmental

data for a set number of hours, after which the paper must be replaced. These devices also

require constant maintenance and recalibration in order to make sure that they’re correctly

collecting environmental data, which takes manpower and money that an institution may not

necessarily have in abundance. Institutions may switch over to a digital data logger like the

HOBO or PEM plug loading systems in order to collect environmental data in a digital format,


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which is beneficial for storing large quantities of information and visualizing that data within a

simple line or bar chart.

Figure 2

Image of a Plug Load HOBO data logging device. HOBO Plug Load Data Logger. Digital image. ONSET. N.p., n.d. Web. 8 July 2017. <http://www.onsetcomp.com/products/data-loggers/ux120-018>.


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Figure 3

PEM2 digital data logger that collects temperature and humidity data. Data collected by this device can then be visualized using the eClimateNotebook system. PEM2 Datalogger. Digital image. Image Permanence Institute. N.p., n.d. Web. 8 July 2017. <https://www.imagepermanenceinstitute.org/store/environmental-monitoring/pem2-datalogger>.

Unfortunately, there are still issues that pop up with digital data loggers. Plug load data loggers

require someone to manually connect the devices into a computer to collect the data. This

process usually takes place once a month due to the time-consuming nature of physically

collecting multiple sensors, downloading the data, and setting up the visualization system during

a routine check. This assumes of course that the institution purchases the basic digital data logger

and not the wireless version of these devices, as cost is often the most critical component behind

any such device purchase, especially for smaller institutions and historical societies. As wireless

data loggers can cost several hundred dollars per device before the cost of an online system to

interpret that data, this cost is a real issue that cripples small to medium archival collection


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facilities. Even when institutions do purchase several data loggers for their collections, the

standard practice of an archival facility is to place one or two loggers per collection space, which

aids in monitoring the macro-environment of a room, but fails to monitor microenvironments

that are inevitably present in the facilities (Morris, 2009). The main areas that should be

monitored are near windows, doors and ventilation systems where temperature and relative

humidity fluctuations are not stable (Morris, 2009).

Another issue of standard data logging systems like the HOBO, eClimateNotebook and

hygrothermograph is the visual representation of data presented to an archivist, historian or

museum curator. The most commonly accepted visualization is a simple line graph that shows

the temperature over a period of days, weeks and months. This type of line graph only provides a

single-colored line to visualize the data set, which can be problematic if the archivist wishes to

present the data to an interested party outside of archives, as the outside party may not

understand issues presented by a simple line. More modern line graphs give the ability to change

color dynamically based on data points, giving a subtle yet effective depth to their visualization.

One could then combine this type of visualization with the addition of a heat map to provide

effective visualization options to the users, ultimately providing a graphical representation of the

physical archival environment.

With the advent of microcontrollers (such as the Arduino Uno or ESP8266 Thing), there

is now an opportunity to create a customizable data logging system that will aid in the

monitoring, collection and visualization of external and internal environmental factors.


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Figure 4

Image of an Arduino Uno microcontroller. What Is an Arduino? Digital image. SparkFun. N.p., n.d. Web. 7 July 2017. <https://learn.sparkfun.com/tutorials/what-is-an-arduino>.


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Figure 5

Image of the ESP8266 Thing microcontroller. SparkFun ESP8266 Thing. Digital image. SparkFun. N.p., n.d. Web. 7 July 2017.

This system can be as robust as individual institutions require in their range of data collection

needs while also implementing visualization graphs that allow for a wider range of interpretation

and use of collected data. Additionally, this system allows for multiple data loggers to be used in

conjunction with one another to record various problematic areas within an archival facility and

generate a more detailed map of the collection space.

This project’s main goal is to study the application of digital media climate monitoring


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technologies within archives to record, collect and visualize environmental conditions of archival

collection facilities. This is due to the necessity of finding out how these technologies can be

used to interpret and visualize data in a customizable range so that archival collection facilities

can better safeguard their artifacts against degradation caused by fluctuations in temperature and

relative humidity.

This research project consisted of three main stages of development: the setup of a

microcontroller with temperature and humidity sensors to collect environmental data, the

creation and implementation of web-based chart visualizations to interpret collected data and a

user experience analysis to determine if the application was successful at addressing the research

questions. The user experience analysis was conducted with the assistance of an expert panel,

which was formed by members of the archival community from the Academy of Natural

Sciences (ANS) in Philadelphia, PA. These experts gave critical input into the design process of

this research project and gave feedback into as to how they believed a better data logging system

could be built from the ground up.

The first stage of development consisted of creating a low-cost wireless digital data

logger that was responsible for collecting temperature and relative humidity at the ANS for the

duration of this project. The data logger was created from a microcontroller, environmental

sensor, and a solderless breadboard designed to connect the two parts together. After coding the

microcontroller to function with the sensor, the functioning data-logging device was then set up

in a diorama room at the ANS. The room chosen for this project was a “poor” archival diorama

room, meaning that it did not have environmental data monitored by the archival staff and was

known to be heavily influenced by outdoor conditions. The main area of concern was the

diorama exhibit itself, but our project was allowed to deploy one data logger within the exhibit


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and two behind the exhibit’s room in a sort of crawlspace. This crawlspace contained both a door

that entered into a staff room and two windows that faced the outdoor environment, meaning that

data loggers were deployed near these zones to fully capture their respective microenvironments.

The second stage of development consisted of creating a web-based system that would

pull collected data and visualize it in such a way as to improve upon the basic line graph that is a

standard for visualizing environmental data within archival collection facilities. These

visualizations took two forms: one, which was to make a line graph that dynamically changed

colors based on data ranges and two, to create a two-dimensional heat map of the diorama

exhibit and its accompanying crawlspace. The goal with these visualizations were to allow

archivists to be able to know when environmental conditions were unfavorable within the

diorama and be able to present this information to outside parties if required.

Once an initial rough draft of the web-application was developed, the expert panel was

gathered to give critiques and guidance on how to improve the visualizations and features. The

experts also gave their opinions on the process as a whole, giving insight into how future work

could expand upon this project’s research to create a more dynamic and user-controlled system.

The experts met together with research personnel for three one-hour sessions, during which they

were presented with this research project’s web-application titled Enviro-Alert. As the experts

gave feedback on this project’s development, they also were prompted to give limitations and

successes of their currently implemented data logging systems.


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2. Related Works

When it comes to the preservation of historical materials, temperature and humidity are

two of biggest environmental threats that preservationists have to deal with on a daily basis.

While there are numerous other environmental factors that also facilitate in the degradation of

materials, temperature and humidity allow for the development of microorganisms that speed up

the natural deterioration process. This fact coupled with the need to present items to the general

public means that certain balances must be found between preservation and presentation (Morris,

2009). In the ideal world, a balance is achieved by creating environmental conditions that allow

for humans to interact with materials comfortably while also limiting the temperature and

relative humidity to unfavorable conditions for microorganism development.

Unfortunately, these ideal conditions are not always applicable in the real world. Even

with features like HVAC systems, dehumidifiers, and insulated buildings, there is not a

guaranteed guard against environmental swings. Building features like windows, doors, shelves,

vents, and boxes can cause microenvironment conditions to fluctuate enough to affect the overall

macro-environments (Morris, 2009). Archival collection institutions thus require the use of data

loggers to help keep a tab on internal environmental conditions and record these fluctuations.

Archivists require data loggers to contain certain qualities that make data collection flexible.

These features range from the data logging device having an ability to be powered either through

battery or plug-in, to also being able to accurately record variations in temperature and humidity

in unfavorable environmental conditions. These loggers must have the ability to collect long-

term environmental data and be able to present users with legible information. Archival


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collections often require a combination of a digital data logger to collect data and an online

service in order to interpret the data, thus bringing this paper to the first two main limitations of

these data logging systems, which is their cost and readability.

2.1 Similar projects

According to Patricia Morris, data logging systems can range from a couple hundred to

several thousand dollars, often meaning that smaller historical societies and libraries cannot

afford to monitor their collections with any real efficiency (Morris, 2009). Even when smaller

archival collection facilities are able to purchase equipment like the physical data logger known

as the hygrothermograph, the equipment can be difficult to interpret without proper training, and

require daily maintenance in order to keep the devices in working order (Morris, 2009). If these

initial requirements are met, then there is still the issue of storing the acquired data sets, a task

that is hardly viable for analogue data sets on paper but a trivial task for digital content (Morris,

2009).

There have been studies done to see how microcomputers can function with regards to

recording and relaying environmental data in order to automate smart climate control (Gurdita,

Vovko, & Ungrin, 2016; Vujovi, Vladimir, Maksimovi, & Mirjana). These studies were

conducted to provide a clear guideline for future work to take place and have a checklist of

desirable features that both microcomputers and microcontrollers can employ (Vujovi et al.).

These devices had to have the ability to be customized from the ground up, have access to

knowledge communities that allow for ease of development, and have the ability to fulfill all the

requirements that an collection institution would need in terms of monitoring, collecting and

sending environmental data (Vujovi et al.).

Several devices were considered for the purpose of this paper’s study, including the


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Raspberry Pi that was proposed by these other studies (Gurdita et al., 2016; Vujovi et al.). As

this project didn’t require a microcomputer to perform the basic task of collecting data and

uploading it to a online repository, the microcontroller known as the SparkFun ESP8266 Thing

was chosen due to having all the desirable features for environmental data collection while also

having a built-in wireless shield that gave the microcontroller the ability to connect wirelessly to

the Internet.

While it is always a necessary to strive to reduce or eliminate false reports, it is equally

important that the sensors record accurate data as well. There are often times where sensors must

be able to record with high-levels of accuracy in order to protect against environmental

fluctuations. This is what truly separates microcontrollers from other monitoring equipment,

which is to say the ability to be customized for such accuracy (Lewis, Campbell, & Stavroulakis,

2016). Depending on the individual user’s needs, attached sensors can be recalibrated to read

fluctuations in as little as .11 degrees in Celsius (Lewis et al., 2016). This is due to the fact that

these devices can have small but powerful algorithms implemented to improve accuracy and also

have sensors replaced with more powerful versions should the need ever become necessary. This

combination makes microcontrollers a desirable and highly customizable choice in terms of

customizable data loggers.

Microcontrollers with temperature and humidity sensors can also perform tasks that

standard plug load data loggers cannot do, such as using the collected data in conjunction with

other microcontrollers to create dynamic visualizations that allow for different

microenvironments within a archival facility to be monitored. With an appropriate online

monitoring application, one could be able to see the data at any time or place so long as one has

an Internet connection (Gurdita et al., 2016). This is coupled with an online database that allows


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for notifications to be sent to users in the event of breaches in specified parameters (Gurdita et

al., 2016). Even with the ever-increasing use of microcontroller capabilities, it is possible to push

its ability to collect data and combine it with other digital media techniques to lower the bar of

entry for small historical collection institutions. Studies have already been done on the use of

data-mining equipment for the purposes of preservation, but it can always be pushed further if a

technological advancements have allowed for previous process to be done cheaper and easier

(Morris, 2009).

2.2 Why use digital technologies within archives?

Along with setting up data logging systems to monitor and collect temperature and

relative humidity data, there is a real need for collected data to be more accessible to archivists

and collection managers, both in terms of being able to access and interpret the data from

anywhere and being able to interpret the data (Kilb & Jansen, 2016). Simple things like color,

letter size, font, etc allow for different visual interpretation, but overall the data must be able to

be read by archivists and outside parties like engineers, donors, scientists, or administrative staff

(Morris, 2009). These visualizations can include graphical representations like that of a heat

map, which could readily provide visual cues as to where problem areas are within an archival

facility. It should be noted that these graphical representations need to be simple yet effective, as

complex visualizations run the risk of being more of a distraction and being generally inefficient

(Shamim, Balakrishnan, & Tahir, 2015). As the standard design is either a line graph or numbers

on a screen, improving the design can be as simple as creating a dynamic line graph that lets

users know what times problems occurred.


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Figure 6

Illustrating the difference between a standard line graph collecting temperature versus a dynamically colored line graph. The left image is a standard type of line graph that would be commonly seen in an archival institution or as part of a standard data logging system. The right image is a dynamically colored graph that illustrates how adding a bit of color can highlight key information of a normal graph.

Within the realm of archival facilities and libraries, data visualizations already exist in

various degrees. One of the key examples is the use of bar charts within libraries to show how

collections are being handled comparatively to one another (Phetteplace, 2012). Unfortunately,

even with visualizations as simple as bar charts, issues arise. Seemingly minor things like length

of a bar compared to presented numbers can cause confusion and may put data interpretation in

jeopardy if presented in a way that cannot be deciphered by the user (Phetteplace, 2012). This is

why it is important to pick the correct visualization for the type of data that will be presented.

With that said, visualizations are useless if the collected data is not properly maintained or stored

in such a fashion that makes the raw data accessible (Phetteplace, 2012).

This is where digital technologies step in to prevent such issues. Web-based applications

combined with digital data loggers allow for visualizations to be rendered in real time while

keeping a consistent overall look. This inherently keeps the data from being stored improperly,


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as the only way to make the system work is by having the raw data being stored correctly and

being parsed in a legible manner. Even with larger systems and multiple data loggers collecting

from the same room, the nature of microcontrollers allows for their data to be easily accessed

and utilized together.

With the assistance of a web-based application, it is then possible to have a data logger

collect information that can then be wirelessly transferred to an online repository. From the

online repository, one could take the data and interpret it through the use of chart visualizations

while simultaneously creating an alert system that notifies users of potentially dangerous events

within an archival facility. The visualizations and alerts would all be presented to the user in a

way that would be easy to read visually yet provide substantial wealth of knowledge that would

otherwise be lost through the use of a simple line (Morton-Owens & Hanson, 2012; Phetteplace,

2012).

2.3 Past/Present research overlaps

While it is expected that archival personnel place their artifacts within environmentally

stable/safe conditions, there are often real world issues that can prevent this from occurring.

When this happens, the archival collection facilities need to raise the necessary revenues through

donations, state funds, or other interested parties in order to fund the enhanced protection of

stored artifacts. These funds that may or may not be released based on the need of individual

facilities, often requiring proof that there are problems within an institution. Having the ability

to prove that a facility is in need of funds for the continued preservation of materials is an

essential task for archival facilities of all sizes. Without collected environmental data, it can be

difficult to prove that artifacts stored within different parts of a building are being affected by

different environmental fluctuations. It is also a common tale to hear about how administrators


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may turn off heating and cooling systems in archival facilities hoping to save money, only to

learn later that mold and other environmental hazards have damaged the archival collections.

Archival personnel always make it a mission to keep a record of environmental fluctuations

through the use of data loggers in order to provide proof of the necessity of proper facilities,

environmental controls and staff numbers. With that said, raw environmental data is presented to

the archivist in the form of a line graph or basic numbers, which requires explanation as to what

the numbers mean. The next stage to assisting in the data collection process therefore is to be

able to present the data in such a way that allows for different parties to understand the context of

the information and where issues are within a facility. One could even make a valid argument

that it is more critical to present this information to outside sources than it is to archivists

themselves.

Past studies of representing data in a graphical format within libraries illustrate how

creating legible visualizations is equivalent to creating a working language, going so far as to

equate it to reading sheet music (Kong & Agrawala, 2012). When archival personnel work with

outside sources, like scientists, to present or store data, there is often a disconnect as both parties

have personal preferences to in how they use and visualize their collected data (Akmon,

Zimmerman, Daniels, & Hedstrom, 2011). This disconnect shows that archivists potentially have

hard times explaining their facilities’ situation to donors, engineers, and even administrators who

may be interested in aiding an archival facility with preserving artifacts through various methods.

By proving that specific areas within the archives need assistance, the limited funds of smaller

archival facilities can then be channeled to areas that need the most aid. It is therefore essential

that a common visual language be established with any sort of chosen visualization, as a wide

audience requires both the archival personnel and outside sources to view data in a way that


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makes issues immediately apparent to all parties involved.

As a line graph is simple chart visualization, it is not inherently difficult to understand.

The main problem occurs when the line graph is only a line with numbers, as it does not reveal

issues without context, which professions outside of archives may not necessarily know or

understand.

Figure 7

Image of the eClimateNotebook line chart. Dew Point Temperature Outdoors in Washington DC, and in one storage space for music, 2009. Institute, I. P. (2017). DP°F of Music Room et al. In monitoring_dp_graph_example.jpg (Ed.), eClimateNotebook (700x470 Dew Point Temperature Outdoors in Washington DC, and in one storage space for music, 2009.). Image Permanence Institute.

By adding something as simple as coloring the line red when it goes past an archival

collection standard temperature and relative humidity threshold while remaining a black line

when inside of safe parameters, this gives instant feedback that illustrates issues without

requiring extensive background knowledge. This can be pushed further by adding in a range


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element to the line graph, thus causing the red to stand out more by creating visual danger zones

that are in direct contrast with a gray background.


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3. Research Question

This paper is studying the application of microcontrollers and web-based repositories to

monitor and collect environmental conditions of archival collection facilities. This is because this

paper wants to find out how these microcontrollers can be used in conjunction with a web-based

application to interpret and visualize data in a customizable range so that low-budget historical

societies can better safeguard their artifacts against degradation caused by fluctuations in

temperature and relative humidity.


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4. Methodology

The proposed approach of this research was to utilize microcontrollers to collect

temperature and humidity data within an archival facility for the purpose of storing and

visualizing the collected data in order. This was done in order to decrease the amount of time

required to acquire environmental data and emphasis shifts in temperature and relative humidity

within an archival collection. The overall goal of this project was to create a low-cost multi-point

data logging system to monitor, store and visualize environmental data within archival collection

facilities. This was accomplished with several stages of development that built upon each other

in order to create a stronger information network that would assist in environmental data

collection and retrieval.

The first stage was setting up multiple microcontrollers within a single room of an

archival collection facility. This facility had to meet the requirement of being a medium sized

collection facility that not only contained an archival department, but also housed dioramas in

museum spaces. This is due to the fact that dioramas have a wide range of environments that

must be both protected enough to allow for long-term preservation while also allowing visitors to

the museum to view exhibits and artifacts. By setting up the project in such a setting, the

noticeable shifts within the collected data would allow the created system to demonstrate the

entire range of good and bad qualities that the proposed system should reasonably be expected

encounter.

The second stage of the project was to develop a web-based application that stored the

collected environmental data from the microcontrollers and visualized the data into two different


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visualizations. The first visualization was a line-range chart that allowed for dynamic coloration

to occur based on live-data feeds. The second visualization was a heat map visualization of the

space where the microcontrollers would be set, offering a clear yet simple visual guide to where

the microcontrollers were located within the archival collection environment. The purpose of this

was two-fold: one, to see if the visualization would be of assistance, as the heat map is generally

not a standard visualization for archivists, and two, to see if there was any value to using such a

visualization for showing outside parties environmental conditions within the archives. These

charts would be rendered client side as opposed to server side, serving the purpose of being open

sourced and available to parties interested in designing their own versions of the application.

The third stage of this project was to gather an expert panel to assist with the analysis of

the system. The expert panel consisted of members who were part of the archival personnel at

the ANS and who had at least year or more experience with data logging systems. The expert

panel consisted of three members from three levels of archival management, ranging from an

assistant who checked data loggers for their assigned department to a director who oversaw the

entirety of the ANS’s archival facility. This allowed a unique insight into the range of an archival

collection facility and gave the greatest potential to receive feedback from different levels of

archives.

4.1 SparkFun Thing

The first step in this project was to outfit three microcontroller units with RHT03 sensors

before implementing code for the units to use previously mentioned sensors.


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Figure 8

Image of the RHT03 temperature and humidity sensor. Humidity and Temperature Sensor - RHT03. Digital image. SparkFun. N.p., n.d. Web. 7 July 2017.

The microcontroller chosen for this project is known as the SparkFun ESP8266 Thing.

This microcontroller was chosen for reasons including the capability with the Arduino library,

compatibility with existing sensors, the large knowledge community-sharing site and a built-in

Wi-Fi shield.


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Figure 9

Diagram of the ESP8266 Thing development board with RHT03 temperature and humidity sensor and an LED. Thingdev. Digital image. Exosite Documentation. N.p., n.d. Web. 21 July 2017. <http://docs.exosite.com/tutorials/esp8266-tutorial/>.

The microcontroller selection and implementation stage were fairly straightforward in

terms of development. The researchers involved in this project initially had to find a mini-

computer or microcontroller that would allow for the implementation of customized sensor

setups while also being flexible enough code-wise to access a variety of open-source knowledge

communities. A Raspberry Pi mini-computer was considered as a strong contender during this

round of development, but several issues arose that ultimately pushed the mini-computer to the

side in terms of data logging capability. The main problem with a Raspberry Pi stemmed from

the facts pertaining to the mini-computer, such as the fact that the device consumed more energy

than a microcontroller does and the greater entry level of coding knowledge required to get a

functioning device up and running when the system was designed to be as low entry as possible.


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This eventually led to the study of Arduino capable devices, specifically microcontrollers

with WiFi capabilities. After a comparison period, taking into account WiFi shields, physical

size of devices, sensor compatibles and Arduino library capabilities, ultimately the SparkFun

ESP8266 Thing was chosen for this project. The knowledge community of the Arduino library

was also particularly helpful for designing this project, as data logging projects similar to this

one have been completed and implemented within the last few years. This has lowered the bar of

entry for designing such systems, as both hobbyists and professional coders break down their

systems into easy to interpret bits. This would allow archivists an opportunity to have an

accessible database of code that could be customized to fit the needs of an individual archival

collection facility.

The SparkFun ESP8266 Thing’s overall cost and built-in WiFi shield were strong initial

desirable factors for this project. With that said, the ESP8266 device did require a few additional

components to be prepared before adding in an external sensor. These items included straight

breakaway headers, a solderless breadboard, jumper wires, wall adaptor 5V DC 2A power supply

for micro-USB and a resistor 10k Ohm 1/6th Watt PTH. Once one factors in the cost of a higher-

end sensor like the RHT03 humidity and temperature sensor used in this project, the overall cost

per device is roughly forty-five dollars. This is immensely cheaper than many other wireless data

loggers that were reviewed at the time of this paper, as a normally accepted data-logger with

wireless capabilities can cost anywhere from one hundred to six hundred dollars. One of the

main downsides to this setup though is the fact that the ESP8266 does require a bit of preemptive

work in order to prepare everything, as the device comes broken out and needs to have the

straight breakaway headers soldered to the ESP8266 before it can function. The device also

requires a one-time purchase of a SparkFun FTDI Basic Breakout board to both connect and


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upload data from the Arduino IDE, and issue that is not made apparent in the documentation

when purchasing the device.

After the microcontrollers were put together and coded with the correct functionality,

three devices were deployed at the ANS in the Desert of Borkou diorama. Two microcontrollers

were deployed behind the diorama in a sort of crawlspace and the third device was deployed

inside the exhibit near the staff entrance door. After ESP8266 Thing’s were deployed, the

devices were allowed to collect data from February to June while the rest of the project moved

forward.


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Figure 10

Top: Image of the diorama where the ESP8266 devices were monitoring. One ESP8266 device was in the diorama towards the left side of the exhibit, out of view of the general public.

Middle: Image of the crawlspace behind the Desert of Borkou diorama.

Bottom: One of the three ESP8266 devices. This particular microcontroller was named #Window, as this device was monitoring the conditions nearest the Window of the diorama’s crawlspace.

The ESP8266’s data was stored on the online repository, ThingSpeak.com.

ThingSpeak.com is an Internet of Things (IoT) online repository, which specializes in the

collection of data from Arduinos and Raspberry Pi devices. Since the compatibility and

straightforward parsing features were highly desirable for this project, the ThingSpeak site was

chosen to store all of the ESP8266’s data. This data would eventually be fed into the web-

application that was designed to go with this paper to test out various features that would assist

the archival facility’s environmental data collection and presentation. A rather important limiting

factor to the development of this web-application was an eight thousand data point retrieval limit


33

from ThingSpeak.com. If one moved the data from ThingSpeak.com into a personal network

server, this limit could have been removed. However, this would also require knowledge into

networking and node-based management, a feature that was not pursued during the development

of this project.

During this stage in the project, it become necessary to store the collected data on an

online repository that allowed for an external application to access the information. The main

data sets required for this project were the following: dates, temperatures, and relative humidity.

These data sets were required to be easily retrievable via cloud connection, which required the

use of a cloud-based storage application. For the purposes of this project, this feature was

completed through the use of a third-party website known as ThingSpeak.com. ThingSpeak

allowed devices like the ESP8266 to upload sensor data to its server and easily forward stored

data to an external site. ThingSpeak also translated the collected data into JSON, XML and CSV

file formats, allowing for HTML sites to easily access the stored data and visualize it outside of

the ThingSpeak site.


34

Figure 11

Image of standard line graphs from ThingSpeak.com as they collect data. ThingSpeak Setup. Digital image. SODAQ. N.p., n.d. Web. 7 July 2017.

4.2 Web based visualizations

The second stage of this project was to create dynamic visualizations from the collected

data in order to easily interpret the data. These visualized instances were to be compared to the

graphs produced by a hygrothermograph and eClimateNotebook system before being read by

experts within the ANS in order to compare and contrast the usefulness and usability of these

visualized data sets.

The visualized graphs designed for this project were line-range charts that dynamically

turned the line and ranged areas red if the temperature shown on the chart were over 70°

Fahrenheit or under 50° Fahrenheit and over 50% in relative humidity or under 30% relative


35

humidity. These ranges were chosen by the National Archives in order to best safeguard the

typical archival environment, taking into account both the safety of artifacts and the ability for

humans to reside near the collections (Conrad, 1999).

Figure 12

Illustrating the coloration range for humidity taken by the #Window ESP8266 device during the month of May.

One of the key areas of interest during the creation of the visualizations for this project

was creating a heat map that showed live temperature data as is was being drawn from the

microcontrollers, thus providing a new form of graphical representation that could aid in the

ability to visually see problem areas within a collection. While this may or may not be

particularly helpful in the day-to-day operations of an archival facility, it would eventually prove

to be of interest to outside parties, as the heat map provides context to data that line graphs

cannot be reasonably expected to visualize in a similar manner.

In order to provide a client-side visualization of the collected environmental data, a

JavaScript library known as D3 was implemented into this project. D3 has many beneficial uses

in terms of programming, as it allows a coder to take raw JSON, XML or CSV data and convert


36

it into simple or complex graphical visualizations. D3, along with the JQuery JavaScript library

were implemented into this project and gave rise to a web-based application that would

eventually be tested by the expert panel. The D3 library also proved to be especially important

during the heat map creation process, as the ability to create visualizations that responded to live

data gave unintentional benefits to the overall study.

Figure 13

Visualization of how the system works. The ESP8266 device uploads the information collected by the sensors to the online repository through the use of WiFi, as indicated by the Cloud. When the user’s web-browser opens Enviro-Alert, the web-application pulls the requested data from ThingSpeak and forms visualizations on the client’s web-browser. Nantakaew, Adun. Arduino and ESP8266 Control Device with ThingSpeak (IoT). Digital image. Blogger. N.p., 24 May 2015. Web. 21 July 2017.

As part of this stage in development, a simple dashboard was created and utilized to

house the visualizations while allowing for the visuals to be generated from the client side web

browser. The web-based application was a mixture of HTML, CSS, JavaScript, JQuery and D3

web code. The bulk of the application came from the development of a D3 code that allowed for

two distinct visualizations to be created. The first visualization was the line-range chart that was

discussed previously in this paper.


37

Figure 14

Screenshots of the dashboard and visualizations of the Enviro-Alert page. The user would typically see only the first visualization (temperature) before scrolling down the page to see the relative humidity line-range chart. As the temperature and humidity breach “safe parameters” as set by the National Archives, the line would turn red and the graph would fill with red.

The temperature line-range chart only showed the range from 80° Fahrenheit to 40°

Fahrenheit while the relative humidity line-range chart displayed the range from 60% humidity


38

to 20% humidity. By limiting the range viewed by the user, it was hoped that users would focus

more on the peaks of the data instead of viewing empty space. Between 70-80° and 40-50°

Fahrenheit and 20-30% and 50-60% relative humidity, the background of the line-range chart

filled in with a light gray color. Between 50-70° Fahrenheit and 30-50% relative humidity, the

background is left blank, with no additional colors behind displayed. A line is then generated

based on parsed data from the microcontrollers through the third-party repository of ThingSpeak.

This generated line, while in the colorless background zone, was then colored black to contrast

against the white background. As the line was generated based on numerous points from the

parsed data, if any of the points go into the grey background zones, the line and background

within the line were colored red. This gives a distinct visual warning that parameters set by the

National Archives had been breached, either by being higher or lower than the recommended

safe parameters for archrival materials.

The heat map visualization builds upon this color idea by providing a grey circle

collection graphic that turned red if the zone was too warm or blue if the zone is too cold. This

graphical zone was then superimposed over a PNG file that contained a rough schematic of the

room where the ESP8266 microcontrollers were placed within the ANS. This not only gave a

visualization of the area of collection for each device, but also allowed users to see the

differences in temperature between the microcontrollers. Besides the graphic zones, the ESP8266

were assigned somewhat arbitrary names that were determined by their location, such as

window, case and door. As these three areas of monitoring were considered to be the most

important areas of environmental fluctuation, this setup allowed for a real world monitoring

scenario to be set up without any need for assumptions on determining data collection sites. The

overall web-application was named Enviro-Alert and was to be directly tested against the


39

eClimateNotebook, HOBO and hygrothermograph systems with the expert panel section.

Figure 15

This image illustrates the heat map design used for the duration of this project.

As part of this stage of the project, a rudimentary alert system was designed and

implemented for when safe parameters were breached. These safe parameters once again dealt

with the standard safe zones set by the National Archives, meaning that an alert was sent

whenever temperature or humidity breached their respective zones. This notification system was

setup in ThingSpeak.com, as the repository already contained all of the relevant information for


40

setting up such an alert scenario. By implementing an algorithm to check the live data feeds for

parameter breaches, a Tweet would then be sent out any time there were unfavorable conditions

were detected by the three devices. This Tweet was then linked to a Smartphone, giving instant

notification of any of the three microcontrollers that there had been a breach of safe parameters.

These Tweets were set to private notification, thus preventing any unnecessary leaking of

information to outside parties. A second algorithm was set up to check the parameters once an

hour to make certain that the microcontrollers were still recording favorable conditions within

the dioramas. If the parameters were still in unsafe zones or if the microcontrollers failed to

respond to the hourly check, a second alert was sent out via Tweet that informed the user that

conditions needed to be checked within the collection site. This proved to be an insightful

addition to the alert system, as the location chosen to set up the microcontrollers happened to be

poorly insulated against temperature and relative humidity, making collection of data during the

months of May and June a constant stream of Tweets.

4.3 Expert Panel

The third stage of development for this project involved gathering the expert panel and

performing three rounds of User Experience (UX) testing to see how the digital data logger and

web-based application system performed when compared to their standard data loggers. Before

officially meeting with the expert panel, the experts were asked to give a brief description of the

data logging systems that they were familiar with and how long they used the system. The

HOBO, EL-USB-2 and hygrothermograth data loggers were the most familiar loggers used by

the experts, and the web-based system commonly used was the HOBO and eClimateNotebook.

During the expert panel meetings, the Enviro-Alert system was then compared to those familiar

systems to see how the multi-point microcontroller based digital data logging system improved


41

or failed to improve collection of holistic data, whether the data collected indicated any issues

within the collected environment, whether the issues were obvious and how the familiar system

would have shown the variations in microenvironments versus macroenvironments.


42

5. Analysis

In order to analyze the success or failure of this project, several questions had to be asked

and answered regarding the data loggers and web-application. As the purpose of this project was

to create a low-cost wireless data logging system that improved upon both collection and

visualization of data, the questions pertained to the ease of use for creating data loggers, how

collection of data was performed, whether that was an improvement or not, whether the

visualizations worked for interpreting data and highlighting issues, whether the web-application

functioned in intuitive manner, and what kind of features would need to be present to make truly

useable within archives. During the third stage of development for this project’s research, an

expert panel was gathered who provided key insight into answering these and other questions

regarding the overall data logging system. The expert’s opinions and thoughts were recorded as

they performed three rounds of research, with each round focusing on a different aspect of

research project.

The first round involved gathering information based on past experiences with data

logging systems. Experts were first introduced to the Enviro-Alert system, but were not asked to

perform any tasks with the system at that time. Instead, they were given the opportunity to air

any compliments or grievances with their current data logging system and what they would have

desired if a system could come out that they could customize. The experts and research agreed

on the time-consuming nature of retrieving data and desired an easier method of gathering the

environmental data, while also complimenting the amount of internal storage that the data

loggers contained for housing large amounts of raw data.

The second round with the experts involved side-by-side comparison of the Enviro-Alert


43

to the HOBO, hygrothermograph, and eClimateNotebook systems. While the Enviro-Alert

provided easier to interpret data, it also lacked user-controlled features. Experts found that, when

compared to the other systems, Enviro-Alert’s data was easier to interpret and show to people

outside of archives and even for archivists but found that the lack of user-input meant that

archivists couldn’t control the data in any way that they would have liked. In terms of the

visualizations however, the experts praised the development of the heat map and found that they

would like to see it develop more and show temperature fluctuation over time. As the heat map

visualization was not present in any of the other data logging systems, this was particularly

insightful for the development of this visualization. When comparing the line-graph

visualizations with one another, while experts had no issues with the standard line graph from the

other systems, the Enviro-Alert’s dynamically colored graph was seen as an improvement for

showing outside parties (donors, administrative staff, engineers) data without having to explain

what the graph was representing.

The third round of testing involved the experts filling out an online survey while tasked

with finding different bits of information within the Enviro-Alert system. The purpose of this

round’s research was to thoroughly test the Enviro-Alert system and see where the strengths and

weaknesses of the system laid. The experts were also given an opportunity to verbally speak

about their experiences with the system during and immediately following the survey, which

gave insight into the ease or frustration that the experts felt during the process. Experts found

that, while the system was currently too bare-bones to be of any significant assistance to

archivists in its current form, they believed that the visualizations and ability to retrieve data was

an important aspect that solved archive’s issues with being able to easily collect environmental

data and show it to outside interested parties. The foreshadowed benefit of the Enviro-Alert


44

system was being able to access the data from anywhere in the world, meaning that the archivists

could look up on how their collections were doing even if they were somewhere else trying to

recruit donors.

5.1 Expert Panel Selection

As part of this paper’s research, an expert panel was assembled at the ANS in

Philadelphia, PA consisting of various levels of archival management within the archival

facilities. The experts consisted of a Senior Director of Public Spaces, an archivist and a library

assistant. As these experts had various levels of interactions with data loggers, an initial review

was given to check the levels of interaction with hygrothermographs and other standard digital

data logging systems took place before the study commenced. All experts had worked with data

logging systems for at least a year and had extensive familiarity with the data logging

technologies, though not all of the experts used the data loggers on a constant basis within the

prior year of this paper’s study.

5.1.1 First Round - Background Information

The Director of Public Spaces’ job was to ensure a consistent environment for their

collections as a whole and therefore did not have the time or manpower to check data logging

systems on any regular basis. While this expert had kept up with how different systems were

presented and utilized, it also meant that they personally had not interacted with the physical

portion of the data logging system in several years. According to this expert, the accepted data

logging system at the time was the HOBO system. The HOBO system gave the desirable effects

of data collection accuracy, large data storage, implemented a small physical data logging device

and had the ability to allow for customizable line graphs for multiple rooms/devices to be shown

and displayed on one graph. The cumbersome side of the HOBO system included short battery


45

life for the physical device, lack of user friendliness on the web application, required constant

upkeep of the devices and the general length of time required to retrieve physical devices and

data. The expert felt that the time required to maintain and calibrate the system was a big enough

flaw that kept it from being implemented to the current day within the ANS.

The archivist and library assistant regularly checked their data logging systems, which

was a combination of a digital data logger known as an EL-USB-2 with the eClimateNotebook

web-service system that interpreted the environmental data. These systems were compatible with

one another, mostly due to the fact that the EL-USB-2 digital recorded data in the form of a

spreadsheet, which the eClimateNotebook was then able to use to create visualizations. The main

benefit of this data logging system is the non-intrusiveness of the data loggers and the

eClimateNotebook system’s ability to create easy visualizations. There were significant

downsides to the system as a whole however, including the battery life of the EL-USB-2 device,

connectivity issues, and the general length of time it took to retrieve the data and parse the data

by hand enough to be usable by the eClimateNotebook system. The biggest issue that the experts

had with the system as a whole was the inability to tell when the data loggers were offline, as

they only checked the devices once a month to see if the data had changed in any way.

5.1.2 Second Round - Current Implementation

The second round of meeting with the members of the expert panel consisted of testing

the web-application that was developed by this paper’s researchers to see how the data logging

system compared to standard data logging systems like the hygrothermograph, HOBO and

eClimateNotebook. When presented with the Enviro-Alert system, the Director of Public Spaces

found that the system did present a clearer picture for interested parties outside of the archival

facility but required more development to be of assistance to the archivists who deal with the


46

data on a daily basis. One of the more favorable features that the Eviro-Alert system presented

from the test was the ability to constantly collect the data and have it comparable to the other

ESP8266 devices. When compared to the hygrothermograph, HOBO system and

eClimateNotebook, the director found that the heat map visualization was particularly useful for

presenting current temperatures inside of the dioramas and displaying live data to interested

outside parties. As this feature was not present in the three other standard data logging systems,

this feature was determined to be a particularly helpful addition to the overall data logging

system. There may even be a benefit in the future to creating a Smartphone-based application

that focuses on the heat map, allowing for enhanced notification possibilities based on user-set

parameters.

When asked about whether the Director of Public Spaces would use the Enviro-Alert

system in its current state, the director found that the system was currently too lightweight in

terms of features to be particularly useful within the archival facility. The complaints were

directed at the lack of control that the user has when presented the data, as the HOBO system and

eClimateNotebook allows users to customize the x and y axes. The HOBO and

eClimateNotebook also allowed for a customizable date range to be presented to the user while

the Enviro-Alert system only presented a few predetermined date ranges to the users, which was

deemed as too limiting. Finally, the director found that the colors of the line graph could be

misinterpreted and preferred a color spectrum of red for too high value (too hot or humid), green

for neutral and blue for too low value (too cold or humid).

The archivist and library assistant were also presented with the same questions and

scenarios as the Director of Public Spaces. When presented with the Enviro-Alert and

eClimateNotebook system comparisons, the two experts took the questions towards a different


47

direction to look over the possibilities of the presented research project being more of an open

source manual to designing similar systems within archival environments. They explained that in

small to medium-sized archival facilities, there was a growing demand for open source projects

as the idea of being able to set up low-cost but customized monitoring systems was gaining

traction within the archival community. The main problem with their current data logging

systems were that the devices only collected data from a single point of reference, and while

these data points could be compared to the other rooms where data loggers were also present, the

ability to compare these sites may not necessarily be the most efficient of ways to study

environmental conditions within any single room. The experts believed that the Enviro-Alert

system contained the desirable Do-It-Yourself (DIY) project that archivists would be looking for

and felt that the ability to set up multiple sensors within the same room without interfering with

the overall results was a valuable tool. This was then elaborated on with the visualizations, as the

experts found the visualizations straightforward and easy to comprehend while also being

presentable to outside interested parties.

When asked to compare the visualizations differences between the hygrothermograph,

HOBO, eClimateNotebook and Enviro-Alert systems, the archivist and library assistant found

that the eClimateNotebook system had simple line graphs that effectively gave required

temperature and humidity information while the Enviro-Alert system presented a similar graph

that also had the added benefit of being more presentable to outside parties. They believed that

this would make it easier to explain the environmental conditions to their administrative staff and

engineers who may not necessarily interpret a standard line graph the same way that archivists

would. They found that the heat map visualization was also particularly useful for displaying the

conditions within the collection zone on a two-dimensional level more effectively than a line


48

graph could ever accomplish. It was believed that this would be an efficient way of explaining

issues within the archival collection to donors or engineers who may require the visualization to

fully comprehend the real-world implications of environmental parameter breaches. The experts

felt that the heat map should be made to display temperature change over time as opposed to

showing the last recorded temperature reading from the ESP8266 devices, but otherwise believed

that the heat map visualization would be an effective tool in understanding the environmental

data.

All experts felt that a notification system would be strongest feature that should be

implemented in order to truly differentiate itself from the other three standard data logging

systems. The experts believed that a notification system which would send an alert to their

phones or through email whenever temperatures climbed to over 75° Fahrenheit or whenever the

data was not being retrieved would prove to be an invaluable tool would distinguish itself from

the Plug Load data loggers. The experts also felt that the ability to have live data that was parsed

already saved an immense amount of time, going from taking several hours to collect data to

only taking a few seconds to open a web browser. This time saving feature was highly sought

after as it is one of the most critical complaints that the experts had about the hygrothermograph,

HOBO and eClimateNotebook systems. The experts also found that the graphs allowed for the

data to be presented while they were traveling, which would open up the possibilities of

answering questions and displaying the data in a legible fashion while speaking to potential

donors or parties interested in seeing the inner functions of an archival space.

5.1.3 Third Round - Enviro-Alert Survey

The third round of meeting with the expert panel consisted of the experts using Enviro-

Alert to fill out a survey designed to test out all of the various features and different scenarios.


49

These scenarios ranged from finding the temperature of a certain date and time to explaining

why they preferred certain features to others. Each expert was given the same survey to fill out

and answer before finishing with a few final comments designed to see how they felt about the

project overall. The overall survey was divided up into four sections, with an additional fifth

section dedicated to identifying each of the expert’s submission.

The first section of the survey introduced the expert panel members to the index page of

Enviro-Alert, which contained six line-range graphs that displayed the data from the past twenty-

four hour period. Each graph corresponded to either the temperature or relative humidity of the

three ESP8266 devices and gave live data straight from the dioramas within the ANS. The

experts were to fill out this section of the survey before continuing the survey. In the second

section of the survey, the expert panel was asked to click on the Enviro-Alert section labeled “7

Days.” They were then presented with the same questions from the first section, only now being

asked to locate the temperature and humidity for certain times and on certain dates.

The third section had the expert panel utilize the past few months feature of Enviro-Alert,

having each expert finding a certain date before being asked if they felt that the navigation to and

from the various pages were understood or if there needed to be improvements made. This

culminated in the fourth and final section, where experts were asked to give their overall opinion

on the Enviro-Alert before being asked to consider what they felt were the most important

features that they would like data loggers to perform in an archival facility environment.


50

Table 1

Experts were given eight questions requested that they locate the temperature and humidity of certain times ranging from the past 24 hours to several past months. This in turn allowed for the collection of twenty-four different responses, from which this paper can determine the visual accuracy of data when compared to the raw numbers.

Table 2

Experts were also asked to rank their opinions on the visualizations, dashboard, and overall look of the web-application known as Enviro-Alert. This ranged from 1-5 for the first eight questions and 1-10 for the last three, with 1 being considered a more

75%

17%

8%

Accuracy of visualizations

Under 1% or 1°F

1%-5% or 1F°-5°F

Over 5% or 5°F

1

1

17

11

6

0 5 10 15 20

Greatly Disliked

Disliked

Neutral

Liked

Greatly Liked

Opinions on visuals

Greatly Disliked

Disliked

Neutral

Liked

Greatly Liked


51

negative opinion of a feature and 5/10 being a more favorable opinion. For the above table, opinions following within 2-4 and 6-9 are considered slightly disliked and slightly liked respectively.

Table 3

Expert’s opinions on individual sections were ranked from a positive opinion to a negative opinion based on their interpretation, ease of understanding and overall understanding of each visualization section.

0

2

4

6

8

10

12

14

24 Hour 7 Day Month Heat Map

Opinions of visualization sections

Positive

Neutral

Negative


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6. Discussion

Based on the findings of this paper’s research combined with the feedback acquired from

the expert panel, several new concepts sprang forward that contribute to the knowledge of

creating a better overall of data logging system by highlighting both their strengths and

weaknesses. Through the background research and knowledge acquired, data logging system

decisions and implementation ultimately boils down to cost efficiency, data accuracy, data

accessibility and ease of use (Conrad, 1999; Fagan, 2014; Morris, 2009; Morton-Owens &

Hanson, 2012; Phetteplace, 2012). These factors weigh in to determine the type of data logging

device an archival facility will utilize, with some facilities choosing to go without loggers due to

the inability to act upon collected data (Morris, 2009). However, with the advent of affordable

microcontrollers and open source knowledge communities like the IoT, there is no longer a

reason to outright dismiss data logging systems. Even if a facility cannot act upon the collected

data, having the data available for future use can prove invaluable should a donor or interested

party come into the equation that could solve facility issues.

Once the issue of collecting the data has been solved, the next logical stage is being able

to present the data in a meaningful way (Kilb & Jansen, 2016). Having the data in the form of an

spreadsheet or a basic line chart could lead to confusion as to where problem areas arise in

archival facilities (Kilb & Jansen, 2016; Morton-Owens & Hanson, 2012). Changing minor

details like the coloration, font and size of different elements within the visualization can alter

the interpretation of data, which can ultimately be the deciding factor as to whether potential

donors to archival facilities understand and are willing to help based on their needs (Morton-

Owens & Hanson, 2012). Even if the data is not shown to donors or outside parties, archival


53

collection facility curators need to be able to show and explain the collected data as efficiently as

possible.

This project’s research found that the basic line graph has its benefits, but also has

enough issues to warrant a change in the way the graph is presented. By making the line portion

of the line-range chart dynamic and change colors based on the height of the line, researchers

found that the line became easier to interpret while also creating a lower bar of entry for

explaining showing issues within the diorama room. Without explaining the graph or what the

colors represented, all participants understood that there had been issues within the diorama

room and that the issues were great enough to require action in the near future. This also proved

that simple alterations to a standard line graph could enhance the interpretation of the displayed

data (Kilb & Jansen, 2016; Morton-Owens & Hanson, 2012). All three ESP8266 devices

contained readings in the upper seventies to lower eighties during the months of May and June

while maintaining a safe temperature zone from February to April. The collected data revealed

that the interior space of the diorama had been breached, as the temperature collected outside of

the diorama was within a few degrees difference of the inside of the diorama. As the inside of the

ANS is climate controlled via HVAC system, this also revealed that the diorama’s space was not

being cooled or dehumidified by the HVAC system, revealing further flaws from within the

space that the diorama had been set up.

The ANS was not actively collecting data from the particular diorama that the researchers

of this project were granted access to, but researchers had been informed that the diorama was

isolated from the rest of the ANS’s climate control systems. If the dioramas had the standard data

logging system in place, meaning a single HOBO, EL-USB-2, hygrothermograph or

eClimateNotebook device would have been placed in the diorama, the standard data logger setup


54

would have revealed a problem within the diorama but not necessarily where the issue was

originating. By having a three-point data logging system in place, the issue became clear that the

diorama was not isolated from the outside environment, but rather contained a breach somewhere

along the back wall of the exhibit where the outside ESP8266 devices were collecting

environmental data. This was an unexpected discovery, but it did also bring up the idea that

having multiple data logging devices within a single area did provide valuable information that a

single point of data would not have revealed (Morris, 2009). The reason why three

microcontroller data loggers were placed within the same diorama space was to test for this

possibility, as the standard data logging setup is to use one data logger per room monitored.

However, it is important to look at these spaces as containing multiple entry points for

temperature and humidity through doors, windows and vents while also remembering that

shelves and boxes create microenvironments that are each contain different environmental

conditions (Morris, 2009).

The visualization of these data points played an important factor in how the data was

interpreted and understood by the expert panel, especially in the case of the heat map. While the

heat map visualization only showed the latest recorded temperatures by the ESP8266 devices, the

idea that these visualizations could give a literal picture of the environment meant that the

experts could show the visualization to administrative staff, scientists or engineers to show were

problem areas are within the archival collection facility (Akmon et al., 2011). With the addition

of a date-picker, the user could control the time and range of the temperature data, providing a

powerful visualization of past environmental data within the archives. The combination of the

highlighting color, showing temperature readings, and displaying all three ESP8266 devices at

the same time revealed that the heat map visualization left a favorable impression on the experts.


55

Each expert felt that the heat map could be taken a step further by showing temperature change

over time, a task that could be taken up by future researchers who wish to build upon this project.

The entire project was created from various knowledge communities who have, to our

knowledge, not attempted to recreate a holistic system the way that this project has created.

There has been research done on using Raspberry Pis’ to create digital data loggers for the

purposes of monitoring data and sending alerts to users if safe parameters have been breached,

and most projects involve visualizing the data in the form of a standard line graph, but all

projects focus on different aspects and never truly unite their ideas (Lewis et al., 2016; Vujovi et

al.). Unlike the research done on the Raspberry Pis’, this project’s research was more focused on

using several microcontrollers that work in close proximity and gave readings on a single room

to present a clear picture of the environmental conditions that did not require interpretation from

the users to fully understand internal conditions. Even in laboratory settings of other research

projects, collected data was only understood by researchers performing the experiments as

outside groups would have required explanation as to where the safe parameters were located per

device (Lewis et al., 2016). By focusing more on the visualizations between the different

microcontrollers, this research proved that improving the data visualization variable affected the

way the data was interpreted by viewers and thus increased the legibility of data for both archival

collection facility curators and outside interested parties.

6.1 Significance

In terms of significance towards the field of digital media, this project has proven that

web-based applications and the IoT knowledge communities can be utilized to create a working

data logging system that is both practical and useful for archival environmental data collection,

management and visualization. The data collected by the microcontrollers had been created from


56

scratch as a DIY data logging system with the help of the IoT knowledge community, stored and

utilized by an online repository that openly shared the knowledge from the IoT community and

visualized by a D3 library that is shared by yet another knowledge community that gave example

codes for repurposing visualizations for unique projects. This project overall gave a clear

indication that these knowledge communities can not only be repurposed for the use of creating a

digital data logging device, but can be taken to several steps beyond to create an entire data

logging system from physical device to web-application and notification system without the need

for expensive hardware and software.


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7. Conclusion

The goal of this research paper was to study how to create a low-cost data logging system,

complete with a digital data logger and web-based application, for accessing internal

environmental data while also bringing together an expert panel to give insight and context to the

development of the overall project. This in turn would allow smaller archival collection facilities,

museums and historical societies to benefit from the project’s work by laying out a blueprint that

these institutions could follow and expand upon to suit individual needs. These created systems

would provide the necessary data that would aid in the protection of historical artifacts by

highlighting dangerous environmental elements and providing an easy to access application that

can be viewed from any web browser.

This project’s research has shown that a DIY data logging system is a valid cost-efficient

method of collecting environmental data within archival collection facilities and that the IoT

knowledge community is a powerful tool for creating systems designed to utilize and visualize

this data in a multi-purpose manner. By going through the steps of implementing a

microcontroller for the purposes of creating a digital data logger, utilizing a IoT compatible

online repository, and repurposing JavaScript knowledge communities to create visualizations

from data, this paper has provided a blueprint that can change the way that archival collection

facilities gather environmental data and utilize that data in a meaningful way. From creating a

heat map to alerting the users of potentially damaging humidity levels, this project’s work has

created a strong starting point for future archival collection facilities to create personal data

logging systems that cater to their individual needs.


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8. Future Work

After testing out all of the necessary features that were implemented in this paper’s

project, several issues and realizations occurred that future works could expand upon or enhance

as technology improves, knowledge community grow and as net coding becomes more powerful.

One of the first issues that this project happened across and requires future work to find a

solution was when the ESP8266 data-logging device lost power or was otherwise interrupted

from uploading data to its online repository. If the microcontrollers lose the ability to upload the

data for any amount of time (power outage, Internet loss, etc), that data was simply lost. This is

why it is imperative to have the notification system that checks for lack of data on a cloud-based

platform and not to have that feature on the device itself. While a Raspberry Pi microcomputer

would allow one to host a notification system on the device itself, it would be imperative to have

a secondary notification system in the cloud that could still send notifications in the event of

device failure. A secondary option that could be implemented to keep the device operating in the

event of a power outage would be a universal power supply (UPS). This would allow for

microcomputers to keep collecting data, even if a localized power outage occurred within the

room that contained the data logger. The microcomputer could programmed to store the data

locally until it reconnected to the Internet, a feature that would be ideal for temporary power

outages. During this power outage and for longer term power failures, an email or text message

would be sent to the archival collections manager courtesy of the cloud-based notification

system, informing archivists of issues that have arisen in the archives.


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During the expert panel stage of this project, an idea of having the web-application being

able to generate customizable reports appeared and generated quite a bit of interest. While the

current method of generating these reports comes from paying companies to provide this service,

there has been a rise in open-sourced JavaScript based libraries that will one day give the ability

to generate these reports based on parameters that the user sets and controls. It was not possible

to test these libraries during the creation process of this project, but it is believed that knowledge

communities will provide the required information for generating the reports. These reports

would require the ability to gather temperature data over a user-controlled time range before

calculating the frequency of temperature fluctuations and the average amount of time that the

collected data was either in unsafe zones or how often the environmental conditions fluctuated.

This kind of automated task could be generated with the correct algorithm implemented via

JavaScript, with the only current hurdle being able to generate a PDF or compatible file that

would allow for a clean appearance physical printout. As JavaScript does not natively allow for

such files to be created, an external library would need to be implemented for this to work.

There are also a number of smaller features that one could add to the provided setup

depending on the individual needs of an archival institution. These features range from different

visualizations, user inputs, dynamic graphs, different types of data, storing data on local servers,

comparing various year’s worth of data to one another, etc. Visualizations and user inputs can be

implemented via JavaScript and its various libraries like JQuery and AJAX, but would also

require a dedicated computer scientist to correctly set up the coding script. Otherwise, the

JavaScript knowledge communities are informative and growing enough to assist in creating

DIY systems that all archival collection facilities could take advantage of regardless of size and

budget.


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This project has revealed several research paths that one could take in future projects

should certain technology and knowledge barriers are overcome. Costs associated with data

logging development will inevitably become cheaper and the bar of entry will continue to be

lowered as time progresses. Along with this inevitable progress are features that can improve this

project’s web-application while also expanding upon the microcontroller and microcomputer

digital data logging ideas. Setting up these data logging systems could soon be as straightforward

as downloading a piece of open source software, uploading it to a customized digital data logger

and using an open sourced web-application to monitor the facility.

In both the immediate and near future, systems can be set up that allow for monitoring,

collecting and uploading data while also providing cloud-based systems to act upon the gathered

data. If the data was stored on a network that an institution controlled and gave permission for

the archival collection facility to utilize the information, a notification system could be set up

that would email or text archivists in the event that unfavorable conditions occurred within the

archives. This project had a basic notification system that was set up using ThingSpeak.com

during the expert panel phase of this project, but it had predetermined sections and parameters

that the archivists couldn’t control and thus was considered more of an untested experiment into

seeing how a cloud-based system worked with this project’s original setup. If the system was

redesigned to work on a network instead of the client side hosting setup, then the overall project

could be designed to work in tangent with an institution’s network setup. This redesigned setup

would benefit medium to larger institutions, as they would be able to customize the notification

scenario to act upon data as soon was it was pulled instead of when the client opened the

browser. Smaller institutions or historical societies may not have access to a network’s Structural

Query Language (SQL) to store their data, and thus may follow this project’s approach to


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utilizing a third party repository that can act upon data as it was being uploaded to the storage

site. Smaller institutions would then have access to emergency notification possibilities, though

they would not be able to set up a forewarning system as that ability would require access to the

SQL database that third-party repositories may not provide. As technology improves and new

web-based coding languages appear, this divide in network access for third-party systems will

become null as databases are becoming easier to create and allow for more user-controlled

content.

By having access to the SQL databases, one could negate the eight-thousand data point

limitation of ThingSpeak.com, creating fully customizable ranges of data sets. This would be

especially useful for creating graphs that chart more than a single month’s worth of data, though

this feature would need to be coupled with an ability for user-controlled date ranges in order to

function correctly. A date-picker function would prove useful and straightforward to implement

in future data logging systems, as adding in the required JQuery library is already a well-known

feature that many websites utilize. There are some issues when using JQuery with D3.js,

especially in generating graphs from JSON data, so it may prove to be beneficial to replace D3

with a different JavaScript visualization library in order to get around this problem.

Another highly desirable feature that would prove to be an effective tool for future

projects is the ability to capture external weather conditions and display it next to or onto the

graph of the internal environmental conditions of the archival collection facility. While one can

currently buy historical weather data and current weather updates via third party applications, if

one were to find a way to get parsed or raw weather data for their local area, then they could use

the same visualization method provided by this project to generate their own weather graphs. By

collecting the data into an online repository and then visualizing is using one’s own developed


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web-application, the overall design integrity would not be compromised by a third party’s design

principles and would be easily retrievable by the archival collection facilities’ system. The

benefit of having this internal and external environmental comparison is significant; if one were

to determine that internal humidity drastically went up on certain days that also corresponded to

weather events like rain, then a direct link between external variables and internal factors would

be established. This would be especially useful should this concept be taken further by using

future forecasts to predict weather events and allow archivists time to prepare their collections

against upcoming external conditions.

Looking even further into the future, it will soon be possible to create the ideal setup for a

multi-point data logging system that will be both low cost and more efficient than current

methods. Setting aside the microcomputer’s need to be plugged into a power outlet, using the

device along with the previously mentioned suggestions would allow multiple custom sensors to

be deployed in each archival collection room, with the sensors having the ability to send alerts to

users should safe parameter within archival collections become too unfavorable for artifacts.

These devices would be controlled via a web-application, thus allowing archivists to remotely set

parameters and monitor various locations around a facility. This web-application would also

allow users to generate reports based on user-controlled parameters, and could be tailored to

provide information based on individual microcomputer’s readings. By having access to the SQL

databases and a weather forecast site, an algorithm could be set up to see future weather

predictions and generate a predictive graph for interior conditions. This predictive graph would

be based on past historical data from outside conditions alongside interior conditions during the

same time frame. With this tool in hand, archivists would have up to ten day’s worth of notice


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for internal facility conditions and thus would be able to take preemptive measures to safe-

guarding their artifacts.

These concepts can be further enhanced when inevitably an open-sourced or inexpensive

form of web-based Artificial Intelligence (AI) becomes available, which will revolutionize the

concept of data loggers. The AI would not necessarily need to be overly complex to be a game

changer; it would need to run algorithms to determine risks at archival collection facilities based

on collected data from digital data loggers. By comparing past internal environmental conditions

with external weather conditions and current temperature and relative humidity data, the AI

could chart a sophisticated graph that takes future forecast data and calculates whether upcoming

days will have enhanced risks to archival collections. This AI software can be taken even further

if multiple archival collection facilities shared their data with one another, allowing the software

to see patterns in internal conditions based on weather forecasts and general climate predictions.

By sharing this data with other facilities, it would also allow a network of knowledge to be

established and potentially allow archival collection faculties to aid one another should internal

conditions prove to be too unfavorable to their more vulnerable artifacts.


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Bibliography

Akmon, D., Zimmerman, A., Daniels, M., & Hedstrom, M. (2011). The application of archival concepts to a data-intensive environment: working with scientists to understand data management and preservation needs. Archival Science, 11(3), 329-348. doi: 10.1007/s10502-011-9151-4

Conrad, E. A. (1999). Realistic Preservation Environment. Paper presented at the Preservation Conference, Washington, DC. https://www.archives.gov/preservation/environmental-control/realistic-preservation-environment.html

Fagan, J. C. (2014). The Suitability of Web Analytics Key Performance Indicators in the Academic Library Environment. The Journal of Academic Librarianship, 40(1), 25-34. doi: http://dx.doi.org/10.1016/j.acalib.2013.06.005

Gurdita, A., Vovko, H., & Ungrin, M. (2016). A Simple and Low-Cost Monitoring System to Investigate Environmental Conditions in a Biological Research Laboratory. PloS one, 11(1), e0147140. doi: 10.1371/journal.pone.0147140

Kilb, M., & Jansen, M. (2016). Visualizing Collections Data: Why Pie Charts Aren't Always the Answer. Serials Review, 42(3), 192-200. doi: 10.1080/00987913.2016.1207479

Kong, N., & Agrawala, M. (2012). Graphical Overlays: Using Layered Elements to Aid Chart Reading. IEEE Transactions on Visualization and Computer Graphics, 18(12), 2631-2638. doi: 10.1109/TVCG.2012.229

Lewis, A. J., Campbell, M., & Stavroulakis, P. (2016). Performance evaluation of a cheap, open source, digital environmental monitor based on the Raspberry Pi. Measurement, 87, 228-235. doi: http://dx.doi.org/10.1016/j.measurement.2016.03.023

Morris, P. (2009). Achieving a Preservation Environment with Data Logging Technology and Microclimates. College & Undergraduate Libraries, 16(1), 83-104. doi: 10.1080/10691310902754247

Morton-Owens, E., & Hanson, K. L. (2012). Trends at a Glance: A Management Dashboard of Library Statistics. Information Technology and Libraries (Online), 31(3), 36-51. doi: 10.6017/ital.v31i3.1919

Phetteplace, E. (2012). Effectively Visualizing Library Data. Reference & User Services Quarterly, 52(2), 93-97. doi: 10.5860/rusq.52n2.93

Shamim, A., Balakrishnan, V., & Tahir, M. (2015). Evaluation of opinion visualization techniques. Information Visualization, 14(4), 339-358. doi: 10.1177/1473871614550537

Vujovi, Vladimir, Maksimovi, & Mirjana. Raspberry Pi as a Sensor Web node for home automation. Computers & electrical engineering, 44, 153-171. doi: 10.1016/j.compeleceng.2015.01.019


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Appendix

Below are the questions and responses for the expert panel’s third round of testing that involved a survey: Enviro-Alert Testing Section 1: Last 24 Hours Page Question Director Archivist Library Assist At 6:00am, what was the temperature reading for the Arduino labeled "Door?"

77 degrees

Looks to be around 76, just above 75

76

At 9:00pm, what was the humidity reading for the Arduino labeled "Window?"

48 %

About 51%

47%

At 1:00pm, what was the temperature reading for the Arduino labeled "Case?"

78 Approximately 77 degrees

76

How would you describe the page setup? Is the information relevant? Do you have any issues finding information?

Scale 1-5, with 1 being irrelevant and 5 being very relevant: 5

The page set up is straight forward and basic. The information is relevant to our needs. Expert thinks having all of the graphs for each area looking exactly the same could be problematic. Setting each area off in some way in addition to the title could decrease the chances of mixing up the data.

The page setup is a little clunky. With three different locations it isn't too difficult to scroll through the page and find what expert looking for but if there are more than three locations it might become somewhat cumbersome to scroll through the page to find what the expert is looking for. As it stands, expert did find the information relevant and didn't have any issues finding what the expert was looking for.

How relevant is the information for finding environmental data?




How useful would this setup be for a day-to-day check of data?

Scale 1-5, with 1 being not useful and 5 being very useful: 3 Scale 1-5, with 1 being not useful and 5 being very useful: 4


Scale 1-5, with 1 being not useful and 5 being very useful: 3

Would you use this page as it currently stands?

Maybe Maybe Maybe

If you could, what would you change about this page? Would you like to

Bigger everything.

Being able to isolate each area of measurement would be helpful to me.

Expert would probably make it easier to get to the data point expert is


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see any additional features or information?

While seeing every reading for every space on the same page can be useful, it's a lot of information to scroll through when sometimes all expert needs is to see one reading for one area.

looking for rather than scrolling through the page to find what data the expert is looking for.

Additional Comments? Nope No No Section 2: Last Seven Days Page Question Director Archivist Library Assist At 12:00pm on June 17th, what was the humidity reading for the Arduino labeled "Window?"

53% About 57%

53%

At 3:00pm for June 18th, what was the temperature reading for the Arduino labeled "Case?"

77 55% 75

At 2:00pm for June 16th, what was the humidity reading for the Arduino labeled "Door?"

33% 48% 50%

At 8:00pm for June 17th, what was the humidity reading for the Arduino labeled "Case?"

50% 51% 51%

At 1:00am for June 19th, what was the humidity reading for the Arduino labeled "Window?"

58% 59% 60%

How would you describe the page setup? Is the information relevant? Do you have any issues finding information?

x/y axis is too loose. Needs to be tighter and larger since the variables are so small.

Again the information is straight forward and basic. The information is relevant. It's nice to be able to see the changes over a week, which can be very helpful in determining trends. Being able to pin point specific data for specific times doesn't seem to be particularly easy.

Again the scrolling through the page to find the relevant data points is a bit cumbersome. The way the graph is set up with the date and time listed on the column is a little bit confusing.









Would you use this page as it currently stands?

No Maybe No

If you could, what would The variables should be Expert would like to Make the graphs slightly


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you add, subtract or change about this page?

easier to deduce and see. possibly see more divisions along the bottom line giving a better grasp of time relative to changes. So rather than just start of day and mid-day having every three hours might be helpful.

larger to show larger stretches of time.

Any additional comments or suggestions about this page?

No Similar to the 'last 24 hours' having to scroll through the page is a bit cumbersome, when expert often wants specific data from a specific area.

No response

Section 3: ESP8266 Individual Device Pages Note: Each time the question starts with “How easy was it to find this page” illustrates a different page that the expert had to find without any guidance from the researchers. Question Director Archivist Library Assist How easy was it to find this page? (#Case Page)

Scale 1-5, with 1 being hard and 5 being easy: 4



How quickly were you able to locate and click to this page?

Scale 1-5, with 1 being very slowly and 5 being very quickly: 4



Do you have any comments or critiques for this particular page?

Top tabs should be very clearly written.

It took expert a couple tries to figure out how to navigate to the specific month for the specific area. Expert had been in "Window" and it took going to window February before heading back to Case and then to Case February.

The graph only had data for a few days of the month available.

How easy was it to find this page? (#Window Page)




How quickly were you able to locate and click to this page?




Do you have any comments or critiques for this particular page?

Same Once expert figured out the navigation it was easy to move from one to the other. It does take several steps to get to the specified graph, which isn't necessarily a problem, just a bit cumbersome.

This graph has more days listed than February but still doesn't show the full month.

How easy was it to find this page? (Heat map page)




How quickly were you able to locate and click to

Scale 1-5, with 1 being very slowly and 5 being




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this page? very quickly: 4 very quickly: 5 very quickly: 5 Do you have any comments or critiques for this particular page?

It should be made clear that the heat map covers the last hour only.

Expert liked having the option of a heat map. No suggestions, though it would be interesting to see how it functions with a more complex layout.

No

Section 4: Final Thoughts Question Director Archivist Library Assist How easy was the system to navigate? Were you able to get to every page without any issues?

Scale 1-10, with 1 being heard and 10 being easy: 6



Was it clear to you as to what kind of information you were looking at?

No Yes Yes

Were the charts easy to read?

Scale 1-10, with 1 being difficult to decipher, hard to read and 10 being legible and easy to read: 2



Could you see any potential in using the heat map within your archival facility?

Maybe Yes Maybe

Any comments or suggestions for improving the heat map?

Font/page data too small. Variables should be finer and easier to locate

Right now it looks good, but expert could envision using it for a more complex layout - multiple rooms or floors, and expert is not sure how that would change the visualization.

If you're looking to see the current temperature in a location the heat map is useful. Although I cannot see myself checking it every day.

Would you prefer any other types or kinds of visualizations?

Yes No No

If you would prefer other kinds of visualizations, what type would you prefer? Would you like additional data to be displayed?

Heat map over time would be nice.

No response No response

Would you prefer to have raw data displayed on any of the pages?

Maybe Yes Maybe

Would you consider using this system within your own archival facility?

Yes Yes Maybe

If this was a DIY (Do It Yourself) system, what would you change about it? What features would you add or take away?

Expert wouldn't have time to do a DIY system

Given the current technological knowledge of our staff we probably wouldn't make changes. It offers the basics of what we need and it looks good. Expert does like the idea

Expert would probably make data points for each location separate while having the data points for each month of each location stay on the same page. Expert thinks that


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of being able to funnel the data into a report that outputs the information according to specified parameters.

adding a sidebar versus a drop down menu might potentially make it easier to get to data points.

If you were paying a company to implement a system like this, what additional features would you like to see?

Ease of use and speed of set up.

A flexible reporting module

The potential for alerts when temperatures and relative humidity exit the normal ranges would be helpful although there would need to be a balance when it comes to the amount of alerts someone receives.

If money was not a limiting factor, what additional features would aid you in collecting and interpreting data from data loggers?

An alert for my phone that expert can easily set. The opportunity to add the HVAC system controls of my building over the heat map--so expert can theoretically control a particular area that alarms me.

Same as above. Extremely long battery life!

If money was a limiting factor, what features would take priority within a DIY system?

Being able to be alerted when the numbers go pear shaped.

No response Getting only temperature and relative humidity to a graph would probably be the lowest bar if money was a limiting factor.

Final comments or suggestions on the overall system?

None No response Expert thinks that the system is easy enough to understand with only a couple hiccups. Expert feels that it is a system that one could easily navigate with little instruction. Expert thinks that the system would be an extremely good fit for smaller museums who might be unable to afford some of the systems offered now. It is also great for museums with a limited staff who don't have the time to go back and forth collecting and placing data loggers and manually uploading the data. Expert feels that the system's remote data uploads is the most enticing aspect.

Github repository of web-application code: https://github.com/DragonPower456/EnviroAlert

using digital media technologies to improve museum archival monitoring systems · 2017. 9. 20. ·...

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