semantics and analytics = making the data and the decisions smarter?

Semantics and analytics = making the data and the decisions smarter?

Digital Antiquity CI

Feb 7-8, 2013, Arlington VA

Peter Fox (RPI and WHOI) pfox@cs.rpi.edu, @taswegian, http://tw.rpi.edu/web/person/PeterFox Tetherless World Constellation http://tw.rpi.edu and AOP&E

Analytics – data and visual

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Data Information Knowledge

Producers Consumers

Context

PresentationOrganization

IntegrationConversation

CreationGathering

Experience• Analytics

Ecosystem

• StimulateInnovation

Research

Exploration

Discovery

Data as Infostructure

Curation for analytics

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Producers Consumers

Quality Control

Fitness for Purpose Fitness for Use

Quality Assessment

Trustee Trustor

Others… Others…

Technical advances

From: C. Borgman, 2008, NSF Cyberlearning Report

Working with knowledge

Expressivity

Maintainability/ Extensibility

Implement-ability

Query

Rule execution

Inference

For real discovery – we need abduction!

- a method of logical inference introduced by C. S. Peirce which comes prior to induction and deduction for which the colloquial name is to have a "hunch”Importantly -

human intuition is needed in interacting with large-scale data

Yes, we need a Knowledge Base

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Smart visual exploration

Semantics - Modern informatics enables a new scale-free** framework approach

• Use cases• Stakeholders• Distributed

authority• Access control• Ontologies• Maintaining

Identity

Finally

• Significant opportunities for smart data-as-a-service approaches to ‘scale’ for big data (on the web)

• Delivering ‘products’ allows analytics on the back end, but tools to plug into a framework are lacking

• Exploit late semantic binding for ABDUCTION• Next generation analytics must accommodate:

abduction, translucency, interactivity and retain what they do well!

• So we all need to get cracking!• Thanks. @taswegian, pfox@cs.rpi.edu

Back shed

Fox & McGuinness Semantic Technologies May 21, 2007

1: Integrating Multiple Data Sources

• The Semantic Web lets us merge statements from different sources

• The RDF Graph Model allows programs to use data uniformly regardless of the source

• Figuring out where to find such data is a motivator for Semantic Web Services

#Ionosphere #magnetic

“100”“TerrestrialIonosphere”

name

hasCoordinates

hasLowerBoundaryValue

Different line & text colors represent different data sources

hasLowerBoundaryUnit“km”

Fox & McGuinness Semantic Technologies May 21, 2007

2: Drill Down /Focused Perusal

• The Semantic Web uses Uniform Resource Identifiers (URIs) to name things

• These can typically be resolved to get more information about the resource

• This essentially creates a web of data analogous to the web of text created by the World Wide Web

• Ontologies are represented using the same structure as content– We can resolve class and

property URIs to learn about the ontology

InternetInternet

…#NeutralTemperature

...#ISR

…#Norway

…#EISCAT

measuredby

type

locatedIn

...#FPI

...#MilllstoneHill

operatedby

Fox & McGuinness Semantic Technologies May 21, 2007

3: Statements about Statements

• The Semantic Web allows us to make statements about statements– Timestamps– Provenance / Lineage– Authoritativeness /

Probability / Uncertainty– Security classification– …

• This is an unsung virtue of the Semantic Web

#Aurora

Red

#Danny’s

20031031

hascolor

hasSource

hasDateTime

Ontologies Workshop, APL May 26, 2006

Fox & McGuinness Semantic Technologies May 21, 2007

8: Proof

• The logical foundations of the Semantic Web allow us to construct proofs that can be used to improve transparency, understanding, and trust

• Proof and Trust are on-going research areas for the Semantic Web

#FlatField#CriticalDataset

#SolarPhysicsPaper

hasCalibration

hasPeerReview

“Critical Dataset has been calibrated with a flat field program that is publishedIn the peer reviewed literature.”

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Knowledge representation

• Statements as triples: {subject-predicate-object}interferometer is-a optical instrumentFabry-Perot is-a interferometerOptical instrument has focal lengthOptical instrument is-a instrumentInstrument has instrument operating modeInstrument has measured parameterInstrument operating mode has measured parameterNeutralTemperature is-a temperatureTemperature is-a parameter

• A query*: select all optical instruments which have operating mode vertical

• An inference: infer operating modes for a Fabry-Perot Interferometer which measures neutral temperature

• ISWC paper award 2006, IAAI best paper (2007), Fox et al. 2009 in Computers and Geosciences.

Visual discovery

Traversal for new patterns

However - Skill/ tools?

Summary

• Get the data well structured! Be aware of the distinctions between data, information, knowledge.

• Develop multi-domain KBs

• Use the standards, and tools that are available

• Get familiar with semantic technology but do not let it drive what you explore

And…

• Frameworks more than systems

• Leverage semantic methodologies that are shown to work/ be useful

• Vocabulary development … by communities, leverage what you have and for the things that matter

• Exploit late semantic binding for ABDUCTION