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Linking Disparate Datasets of the Earth Sciences with the
SemantEco Annotator
Session: Managing Ecological Data for
Effective Use and Reuse
Patrice Seyed1,2, Katherine Chastain1, and Deborah McGuinness1
1 Tetherless World Constellation, Rensselaer Polytechnic Institute, 110 8 th Street, Troy, NY 121802 DataONE, University of New Mexico, 1 University Boulevard N.E., Albuquerque, NM 87131
Overview
• Introduction• Semantics and Linked Data• Use Case: SemantEco• SemantEco Annotator
– Concept– Getting started– Overview
• Ontologies• Capabilities• Integration with Semantic Applications• Future Work• Quick Look Video• Summary
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Introduction
• How can we take datasets from different sources and make them– Easy to search and to discover?– Easy to use and to re-use?– Easy to integrate with each other for
visualization and other applications?
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Semantics and Linked Data
• We need a way to describe the relationships between tabular data columns…
Linked-data formats such as the Resource Description Framework (RDF) capture such relationships in subject-
predicate-object triples.
• … and we need a method of description that is both standardized and machine-readable.
Communities can develop, use, and reuse common vocabulary with ontologies, expressed in a computer-readable format: the Web Ontology Language (OWL)
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Semantics and Linked Data
• Linked format aids interoperability, making it easier to share.
• Use existing URI’s to refer to well-defined entities and concepts: – How do you make sure that everyone using
your data understands that the string “NY” refers to the US state of New York?
– What more can you learn if you can easily discover other datasets that also refer to the US state of New York?
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Use Case: SemantEco
• SemantEco is a data visualization environment that allows a user to explore ecological data through a map-based interface.
• Data comes from a variety of sources: – Federal, such as the USGS, EPA.– Local, such as the Darrin Freshwater
Institute of Upstate New York.– … each with different notations and best-
practices for gathering and recording.
Conceptually....
• Represent data independent of the schema by which it was recorded
• This enables comparisons across data from different sources
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• In SemantEco, we look at Measurements:• Water quality• Air quality• Birds• Fish
SemantEco Annotator
Allows a user to:• Translate data into linked-data formats such as RDF:
– Linked data triples describe how columns in a data table relate to each other, and to the data in that column.
– OWL ontologies provide standard vocabularies for describing data these relationships.
– Resulting enriched RDF data can be used immediately within RDF stores / hosted as LD.
• OR to utilize semantics to annotate data:– Column headers correspond to OWL properties – Data cell values can correspond to OWL classes or datatypes– Organizational best-practices and terminology can be defined in
the data files themselves.8
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Provenance and Metadata
• Annotator asks the user to provide metadata about the dataset.
• This is also becomes part of the final RDF, facilitating the dataset’s discoverability.
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Ontologies
• Load one or more ontologies from the dropdown menu.
• Or import from a URI.
• Annotator also maintains a list of recent imports for re-use.
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Capabilities
• Provide a definition for “Accession Code”• Specify which standard was used to record the Date• Group “Lake Name”, “Z Max” and “Sample Z” together as a single
entity: the location where the sample was taken• Make explicit that “NH4+” is the same thing as “Ammonium”, and
that the units (mg/L) apply to each number in that column.
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Integration with Semantic Applications
• Identify application’s requirements:• Eg., a piece of data with lat-long
coordinates can be plotted on a map.
• We brought in data from the Darrin Freshwater Institute containing water quality data for lakes in Upstate New York, augmenting existing data from the U.S. Geological Survey.
“Big Moose Lake”
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Integration with Semantic Applications
• Linking data to well-defined entities and concepts by URI enhances searchability.
dbpedia:New_York
“New York”“New York State”“NY”
dbpedia:New_York_City
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Future Work
• Automatic mappings directed to a particular graph closed under a predicate/object pair, use of OWL domain and range restriction axioms to guide the user in vocabulary selection decisions
• Use of OWL class definitions to enable a top-down approach for modeling data
• Ability to load enhancement files, both to facilitate translation of multiple similar datasets, and to make corrections easier.
• Construction of a platform for better management of linked data, within which the Annotator plays a vital role.
• Use of application requirements to create “templates” for new data sources to be integrated more easily.
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Summary
• “SemantEco Annotator” component for ease of translation into RDF
• Multi-purposed for translation, annotation, and generalized mapping.
• A Part of a Future “Suite” that couples Annotation and Search
SemantEco Annotator Project Page
Want more info? Interested in collaborating?See Evan Patton or email Deborah McGuinness dlm@cs.rpi.edu
We also have a project page with screenshots and demonstration videos: http://tw.rpi.edu/web/project/SemantEcoAnnotator
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Acknowledgements
• Rensselaer Polytechnic Institute• Tetherless World Constellation at RPI• DataONE
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