Semantic Support for Complex Ecosystem Research Environments
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Transcript of Semantic Support for Complex Ecosystem Research Environments
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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
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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
*
*
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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
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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.
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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.
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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: [email protected]–Paulo Pinheiro: [email protected]–Matt Klawonn: [email protected]
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