Skip to main content
SpringerLink
Log in
Book cover

Evolutionary Genomics pp 489–511Cite as

Genomics Data Resources: Frameworks and Standards

  • Protocol
  • First Online:

Part of the book series: Methods in Molecular Biology ((MIMB,volume 856))

Abstract

The emergence of genomics tools for the evolutionary and comparative biology community led to a rapid explosion in the number of online resources targeted at this specialized community, including Web-based comparative genomics software, such as the Artemis Comparison Tool (WebACT); databases, such as PaleoDB, Global Biodiversity Information Facility, and TreeBase; and knowledge frameworks, such as the Evolution Ontology. Unfortunately, these providers are largely independent of one another and therefore the individual resources do not share any centralized plan for how the data or tools would or should be provided. As a result, there are a myriad of often incompatible technologies and frameworks being used by this community of providers. In this chapter, we explore approaches to online resource publication, both those already in use by the community, as well as new and emergent frameworks and standards. Exploration of the strengths and weaknesses of each approach, together with a brief exploration of the philosophy or informatics theory behind the varying approaches, will hopefully help readers as they navigate this data space. The discussion is constructed such that it lays the groundwork for exploration of a new global standard for data and knowledge representation—“The Semantic Web”—that holds promise of providing solutions to many of the complexities users face in their attempts to discover and integrate biodiversity data, and examples are provided.

This is a preview of subscription content, log in via an institution.

Protocol
USD   49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   179.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

Notes

  1. 1.

    The process of retrieving the data and/or metadata that is identified by any Web identifier is called “resolution”; therefore, URIs of all types are “resolved” to data or “resolved” to metadata by calling a server using a protocol that is appropriate for that type of URI.

  2. 2.

    The HTTP methods, GET, PUT, POST, and DELETE, roughly mimic the database operations of Retrieve, Create, Update, and Delete. The fifth method, HEAD, is used to retrieve basic metadata about the page, such as its expiry date, its size, or its date of creation.

  3. 3.

    Though there is no formal requirement for RESTful applications to be Web based at all, REST is a design pattern, not a Web architecture. On the contrary—the Web follows the REST pattern, not the other way around.

References

  1. Stein, L. (2003). Bioinformatics: Gone in 2012. O'Reilly Bioinformatics Technology Conference, 2003, San Diego, California, USA.

    Google Scholar 

  2. Pearson, H. (2001). Biology’s name game. Nature 411 (7 June), 631–632.

    Google Scholar 

  3. Good, B.; Wilkinson, M. D. (2006). The Life Sciences Semantic Web is Full of Creeps! Briefings in Bioinformatics 7 (3), 275–286.

    Article  PubMed  Google Scholar 

  4. World Wide Web Consortium. Cool URIs. http://www.w3.org/TR/cooluris.

  5. World Wide Web Consortium. URIs, URLs, and URNs: Clarifications and Recommendations 1.0. http://www.w3.org/TR/uri-clarification.

  6. Clark, T.; Martin, S.; Liefeld, T. (2004). Globally distributed object identification for biological knowledgebases. Briefings in bioinformatics 5 (1), 57–70.

    Article  Google Scholar 

  7. Bafna, S.; Humphries, J.; Miranke, D. (2008). Schema driven assignment and implementation of life science identifiers (LSIDs). Journal of Biomedical Informatics 41 (5), 730–738.

    Article  PubMed  Google Scholar 

  8. Mendelsohn, N. My conversation with Sean Martin about LSIDs. http://lists.w3.org/Archives/Public/www-tag/2006Jul/0041.

  9. Object Management Group Inc. Document – dtc/04-10-08 (Final available Life Science Identifier specification). http://www.omg.org/cgi-bin/doc?dtc/04-10-08.

  10. Vision, T. (2010). The Dryad Digital Repository: Published evolutionary data as part of the greater data ecosystem. Available from Nature Precedings: http://hdl.handle.net/10101/npre.2010.4595.1.

  11. Booth, D. Denotation as a Two-Step Mapping in Semantic Web Architecture. http://dbooth.org/2009/denotation.

  12. SKP1 (S phase Kinase-associated Protein 1). http://www.ncbi.nlm.nih.gov/sites/entrez?db=protein%26cmd=Link%26LinkName=protein_gene%26from_uid=18410982.

  13. World Wide Web Consortium (W3C). RDF – Semantic Web Standards. http://www.w3.org/RDF.

  14. World Wide Web Consortium. OWL Web Ontology Language Overview. http://www.w3.org/TR/owl-features.

  15. Bizer, C.; Heath, T.; Berners-Lee, T. (2009). Linked Data – The Story So Far. International Journal on Semantic Web and Information Systems 5 (3), 1–22.

    Article  Google Scholar 

  16. Gene Ontology Consortium (2008). The Gene Ontology project in 2008. Nucleic Acids Res 36 (Database Issue), D440–D444.

    Google Scholar 

  17. World Wide Web Consortium. Semantic Web Health Care and Life Sciences (HCLS) Interest Group. http://www.w3.org/blog/hcls.

  18. Comparative Data Analysis Ontology. http://www.evolutionaryontology.org.

  19. Wolstencroft, K.; Alper, P.; Hull, D.; Wroe, C.; Lord, P.; Stevens, R.; Goble, C. A. (2007). The myGrid ontology: bioinformatics service discovery. International Journal of Bioinformatics Research and Applications 3 (3), 303–325.

    Article  PubMed  CAS  Google Scholar 

  20. Taxonomic Database Working Group. Darwin Core. http://rs.tdwg.org/dwc.

  21. Taxonomic Database Working Group. Darwin Core Project site for discussion and development. http://code.google.com/p/darwincore.

  22. Taxonomic Database Working Group. TDWG Homepage. http://www.tdwg.org.

  23. Goldstein, A. M. (2009). The Evolution Ontology. Available from Nature Precedings: http://dx.doi.org/10.1038/npre.2009.3557.1.

  24. Fielding, R. T. Architectural Styles and the Design of Network-based Software Architectures. http://www.ics.uci.edu/~fielding/pubs/dissertation/top.htm.

  25. NESCENT. PhyloWS/REST. https://www.nescent.org/wg/evoinfo/index.php?title=PhyloWS/REST.

  26. Encyclopedia of Life. http://www.eol.org/api.

  27. The Paleobiology Database. http://paleodb.org.

  28. Stein, L. (2002). Creating a bioinformatics nation. Nature 417, 119–120.

    Article  PubMed  CAS  Google Scholar 

  29. World Wide Web Consortium. Web Services Activity. http://www.w3.org/2002/ws.

  30. World Wide Web Consortium. Web Services Description Language (WSDL) 1.1. http://www.w3.org/TR/wsdl.

  31. Taxonomic Database Working Group. TAPIR – TDWG Access Protocol for Information Retrieval. http://www.tdwg.org/dav/subgroups/tapir/1.0/docs/tdwg_tapir_specification_2010-05-05.htm.

  32. Wroe, C.; Goble, C.; Goderis, A.; Lord, P.; Miles, S.; Papay, J.; Alper, P.; Moreau, L. (2007). Recycling workflows and services through discovery and reuse. Concurrency and Computation: Practice and Experience 19 (2), 181–194.

    Article  Google Scholar 

  33. Stevens, R.; Baker, P.; Bechhofer, S.; Ng, G.; Jacoby, A.; Paton, N. W.; Goble, C. A.; Brass, A. (2000). TAMBIS: Transparent Access to Multiple Bioinformatics Information Sources. Bioinformatics 16 (2), 184–186.

    Article  PubMed  CAS  Google Scholar 

  34. myGrid Project. myGrid Home. http://www.mygrid.org.uk.

  35. The BioMoby Consortium (2008). Interoperability With Moby 1.0 – It’s Better Than Sharing Your Toothbrush! Briefings in Bioinformatics 9 (3), 220.

    Google Scholar 

  36. Lord, P.; Bechhofer, S.; Wilkinson, M. D.; Schiltz, G.; Gessler, D.; Hull, D.; Carole, G.; Stein, L. (2004). Applying Semantic Web Services to Bioinformatics: Experiences Gained, Lessons Learnt. Lecture Notes in Computer Science, The Semantic Web – ISWC 2004, 3298, 350–364.

    Google Scholar 

  37. Gessler, D. D.; Schiltz, G. S.; May, G. D.; Avraham, S.; Town, C.; Grant, D.; Nelson, R. T. (2009). SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services. BMC Bioinformatics 10, 309.

    Google Scholar 

  38. The iPlant Collaborative. http://www.iplantcollaborative.org.

  39. Wilkinson, M. D.; Vandervalk, B.; McCarthy, L. (2009) SADI Semantic Web Services – ‚cause you can't always GET what you want! Services Computing Conference, APSCC 2009. IEEE Asia-Pacific, Singapore, 2009; pp 13–18.

    Google Scholar 

  40. Vandervalk, B.; McCarthy, L.; Wilkinson, M.D. (2010). SHARE & The Semantic Web – This Time it’s Personal! Proceedings of OWLED 2010, San Francisco, California, USA 21–22 June 2010.

    Google Scholar 

  41. Bhagat, J.; Tanoh, F.; Nzuobontane, E.; Laurent, T.; Orlowski, J.; Roos, M.; Wolstencroft, K.; Aleksejevs, S.; Stevens, R.; Pettifer, S.; Lopez, R.; Goble, C. A. (2010). BioCatalogue: a universal catalogue of web services for the life sciences. Nucleic Acids Research 38 (suppl), W689–W694.

    Article  PubMed  CAS  Google Scholar 

  42. Goble, C. A.; De Roure, D. (2007). myExperiment: social networking for workflow-using e-scientists. Proceedings of the 2nd workshop on Workflows in support of large-scale science; High Performance Distributed Computing 2007; pp 1–2.

    Google Scholar 

  43. Prins, P., Belhachemi, D., Möller, S., Smant, G. (2012) Scalable computing in evolutionary genomics. In: Anisimova, M., (ed.), Evolutionary genomics: statistical and computational methods (volume 1). Methods in Molecular Biology, Springer Science+Business Media New York.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Medical Genetics, University of British Columbia and PI Bioinformatics, Heart + Lung Institute at St. Paul’s Hospital, Vancouver, BC, Canada

    Mark D. Wilkinson

Authors
  1. Mark D. Wilkinson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mark D. Wilkinson .

Editor information

Editors and Affiliations

  1. Department of Computer Science, ETH Zürich, Universitätsstr. 6, Zürich, 8092, Switzerland

    Maria Anisimova

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media, LLC

About this protocol

Cite this protocol

Wilkinson, M.D. (2012). Genomics Data Resources: Frameworks and Standards. In: Anisimova, M. (eds) Evolutionary Genomics. Methods in Molecular Biology, vol 856. Humana Press. https://doi.org/10.1007/978-1-61779-585-5_20

Download citation

  • DOI: https://doi.org/10.1007/978-1-61779-585-5_20

  • Published:

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-61779-584-8

  • Online ISBN: 978-1-61779-585-5

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation