eXtended Metadata Registry (XMDR) International Ecoinformatics Technical Collaboration
Jennifer A. Dunne Santa Fe Institute Pacific Ecoinformatics & Computational Ecology Lab
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Transcript of Jennifer A. Dunne Santa Fe Institute Pacific Ecoinformatics & Computational Ecology Lab
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Jennifer A. Dunne
Santa Fe InstitutePacific Ecoinformatics & Computational
Ecology Lab
Rich William, Neo Martinez, et al.
www.foodwebs.org
Challenges & Opportunitiesfor Ecological Informatics
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• Ecologists make observations and save them as spreadsheet or text files
• Raw data rarely published or made available online• Summaries provide minimal ad-hoc descriptions of data context• Context (why, when, where, how) lost as time proceeds
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Challenge #1: Basic Data
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Challenge #2: Finding & Integrating Data
• Data relevant for ecological questions is DIVERSE & DISPERSED
• Available databases often primitive (little or no metadata)• Data gathering, integration, and synthesis are done by
hand
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Ecoinformatics: technologies and practices for gath-ering, analyzing, visualizing, storing, retrieving and other-wise managing ecological knowledge and information
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Ecoinformatic fantasy
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Early food-web researchers (primarily Joel Cohen) introduced sharable catalogs of ecological datasets:
1978: First published “catalog” included 30 food webs
1986: Catalog expanded to 113 food webs
1989: EcOWEB, the first “machine-readable data base of food webs” (now >200 webs)
Interest in comparative studies led to a culture of data sharing and an early “first-generation” data base.
BUT, current access to food web data is still primitive: Requesting EcOWEB floppy disc from Cohen/Rockefeller Hand-mining individual datasets from literature Contacting researchers individually Emailing me for second generation data
From Data to Data Bases
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In Final Development: Webs on the Web (WoW)
1) Knowledge Base -100s to 1000s of food webs and other ecological networks, flexible data format-10Ks to 100Ks instances of feeding interactions-Species info (taxonomy, phylogeny, biomass, body size, metabolic rates, etc.)-Quantitative link info (frequency, flow, preference, etc.)-Additional info (geographic, provenance, versions, citations, geographic, etc.)-Downloading, uploading, annotation capabilities
2) Analysis Tools-Calculation of dozens of network structure properties-Modeling (network structure, nonlinear bioenergetic dynamics)-In silico experiments (biodiversity loss, invasions, etc.)-Link to other software (Pajek, Mage, EcoPath/EcoSim, etc.)-Trophic inference (phylogenetic, morphological)-Pipeline architecture allows users to plug in their own algorithms
3) Visualization Tools-Highly interactive and customizable 3D visualizations of ecological networks-Animations of dynamics, and graphical output of simulations-Images & movies of species & interactions (www.arkive.com - Images of Life on
Earth)
From Data Bases to Knowledge Bases
Challenges: usability, quality control, security, accessibility, storage, maintenance
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Linking KBs through Semantic Webs Tools
““The Semantic WebThe Semantic Web is an extension of the is an extension of the current web in which information is given well-current web in which information is given well-defined meaning, better enabling computers and defined meaning, better enabling computers and people to work in cooperation.”people to work in cooperation.”
-Tim Berners-Lee et al. (2001) The Semantic Web. Scientific American
Semantic Web technologies are being “designed to improve communications between people using differing terminologies to extend the interoperability of databases.”
-Jim Hendler (2003) Science and the Semantic Web. Science
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How to integrate dispersed, heterogeneous ecological information
resources on the WWW?
SPiRE: Semantic Prototypes in Research Ecoinformatics
SWISST: Semantic Web Informatics for Species in Space & Time
Creating a first generation of user-friendly and highly extensible open-source software that stores, retrieves, analyzes, visualizes, and integrates distributed information relating to variation within and among species.
Ontologies: mapping between current terminologies and cleaned-up, structured categories Integrative web services: queries & information mashups Integrative reasoning tools Easy-to-use user interfaces
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Three Central Tasks for SPiRE & SWISST:
1) Implement new information architectures to increase functionality of ecoinformatic software
2) Implement new client tools with user-friendly GUIs (for concept refining; data entry, discovery, analysis; data visualization)
3) DBs into KBs: extend ontologies & increase metadata
New Semantic Web Standards (W3C):
OWL: ontology web languageRDF: resource description frameworkSWRL*: semantic web rules languageSPARQL: SPARQL protocol and RDF query language
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Projects funded by the U.S. National Science Foundation:Projects funded by the U.S. National Science Foundation:
Webs on the Web: Webs on the Web: Internet Database, Analysis & Visualization of Ecological NetworksInternet Database, Analysis & Visualization of Ecological Networks
Science on the Semantic Web: Science on the Semantic Web: Prototypes in BioinformaticsPrototypes in Bioinformatics
Science Environment for Ecological Knowledge (NCEAS)Science Environment for Ecological Knowledge (NCEAS)