Semantic Support for Complex Ecosystem Research

Environments

Deborah McGuinness1, Paulo Pinheiro1, Henrique Santos1,2, Matthew Klawonn1,

Katherine Chastain1

1Rensselaer Polytechnic Institute, USA2Universidade de Fortaleza, Brazil

AGU, December 2015

Outline

• Problem Statement• Foundational Technologies

–Long standing semantic tools–Custom solutions

• Recent Developments• Conclusions• Future Directions

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Problem Statement

• In large projects, how should data be:– Integrated with other relevant data and

metadata?– Interpreted?

• And also–Accessed, shared, and visualized?

• Examples of data types in projects we work on:–Environmental monitoring–Architecture science and ecology

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Foundational Technologies

• Ontologies: For capturing context–PROV-O–OBOE–VSTO–HASNetO

• Apache SOLR: For storage and retrieval• Contextualized CSVs: For data annotation• D3 Javascript: For metadata visualization

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The Human-Aware Sensor Network Ontology

vstoi:Detector

vstoi:Instrument

vstoi:Platform

hasneto:Sensing

Perspective

oboe:Characteristic

oboe:Entity

vstoi:Detachable

Detector

vstoi:AttachedDetector

*

*

*1

0..1

*hasPerspectiveCharacteristic

perspectiveOf

prov:Activity

hasneto:DataCollection

vstoi:Deployment

xsd:dateTime

xsd:dateTime

hasDataCollection

1*

prov:Agent

wasAssociatedWithstartedAtTime

endedAtTime

1

1

*

**

*

oboe:Measurement

of-characteristic

hasneto:hasMeasurement 1

1

*

*

HADatAc

• Human Aware Data Acquisition Framework• A web application based on Apache SOLR, the

Play Framework• Goal: To provide a one-stop-shop for combined

data and metadata management, markup, integration, retrieval, and visualization

• Uses ontologies combined with limited human markup to achieve this goal

• Can be deployed on a laptop or server, depending on a user's needs

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Combining Data and Metadata

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Mouse over

Mouse over

Metadata

based

facete

d searc

h

Measurement metadata

Metadata about the metadata

Data Privacy

• In addition to nice visualization, integration, and retrieval features, HADatAc has sophisticated privacy mechanisms

• Data has various levels of access open to anonymous and pre-registered users.

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Data Privacy cont.

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Ease of Use== START-PREAMBLE ==

@base <http://localhost#> .

.

@prefix hasneto: <http://hadatac.org/ont/hasneto#> .

@prefix hadatac: <http://hadatac.org/ont/hadatac#> .

<example-kb> a hadatac:KnowledgeBase; hadatac:hasHost "http://localhost"^^xsd:anyURI .

<dataCollection-example01> a hasneto:DataCollection; prov:startedAtTime "2015-02-12T09:30:00Z"^^xsd:dateTime .

<deployment-example01> hasneto:hasDataCollection <dataCollection-example01> .

<example01-dataset01> a vstoi:Dataset; prov:wasGeneratedBy <dataCollection-example01>; hadatac:hasMeasurementType <mt0>,<mt1> .

<mt0> a hadatac:MeasurementType; time:inDateTime <ts0>; hadatac:atColumn 3; oboe:ofCharacteristic hadatac-entities:EC-WindDirection; oboe:usesStandard oboe-standards:Degree .

<mt1> a hadatac:MeasurementType; time:inDateTime <ts0>; hadatac:atColumn 2; oboe:ofCharacteristic hadatac-entities:EC-WindSpeed; oboe:usesStandard oboe-standards:MeterPerSecond .

<ts0> hadatac:atColumn 0 .

== END-PREAMBLE ==

TimeStamp,Record,WindSpdAve_ms,WindDir,WindSpd_ms_Min,WindSpdGust_ms_Max,AirTemp_C_Avg,RH_Pct_Avg,BaroPress_hPa_Avg,Rain_mm_Tot,Hail_Hits_Tot

2015-02-12T09:30:00Z,0,0.99,217.9,0.3,1.7,-4.5,66.58,995,0,0

2015-02-12T09:45:00Z,1,1.112,227.8,0.1,2.1,-4.372,66.45,995,0,0

2015-02-12T10:00:00Z,2,1.169,222.2,0.3,2.6,-4.146,65.98,995,0,0

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• Work with csv files• Automate data

transfer across the web, including large amounts of data

• Retrieval (e.g faceted search), and visualization tools are automatically usable with uploaded data.

Conclusions

• Various ontologies were presented with the intent to show how they capture context in big data projects

• HADatAc was introduced, along with some of its key functionalities.

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HADatAc is a cross-platform web service which integrates annotated data sets with other relevant data and metadata, and surrounds them with retrieval (faceted search) and visualization tools as well as privacy controls.

Future Steps

• Refine HASNetO vocabulary and test it over a constantly growing HASNetO-based knowledge base.

• Continue to add functionality to HADatAc–More visualization tools–Enhanced search capabilities–Looking to integrate with lab information

management systems (potentially use with science other than medicine)

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More Information

• Contact Information–Deborah McGuinness: dlm@cs.rpi.edu–Paulo Pinheiro: pinhep@rpi.edu–Matt Klawonn: klawom@rpi.edu

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