Ecoinformatics: Supporting ecology as a data-intensive science

Trends in Ecology and Evolution

Volumn 27, Issue 2, 2012, Pages 85-93

  Michener, William K ^a   Jones, Matthew B ^b  

^a UNIVERSITY OF NEW MEXICO   (United States)

^b NATIONAL CENTER FOR ECOLOGICAL ANALYSIS AND SYNTHESIS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOSPHERE; DATA SET; ECOLOGICAL APPROACH; GENE EXPRESSION; HETEROGENEITY; INTERDISCIPLINARY APPROACH; KNOWLEDGE; LITERATURE REVIEW; RESEARCH WORK;

BIOLOGY; COMPUTER PROGRAM; DATA BASE; ECOLOGY; METHODOLOGY; REVIEW;

COMPUTATIONAL BIOLOGY; DATABASES AS TOPIC; ECOLOGY; SOFTWARE;

EID: 84856119548     PISSN: 01695347     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tree.2011.11.016     Document Type: Review

References (76)

1. Kelling S., et al. Data-intensive science: a new paradigm for biodiversity studies. Bioscience 2009, 59:613-620.
2. Hey T.S., et al. The Fourth Paradigm 2009, Microsoft Corporation.
3. Jensen J.R. Remote Sensing of the Environment: An Earth Resource Perspective 2006, Prentice Hall.
4. Collins S.L., et al. New opportunities in ecological sensing using wireless sensor networks. Front. Ecol. Environ. 2006, 4:402-407.
5. Porter J.H., et al. New eyes on the world: advanced sensors for ecology. Bioscience 2009, 59:385-397.
6. Rundel P.W., et al. Environmental sensor networks in ecological research. New Phytol. 2009, 182:589-607.
7. Benson B.J., et al. Perspectives on next-generation technology for environmental sensor networks. Front. Ecol. Environ. 2010, 8:193-200.
8. Keller M., et al. A continental strategy for the National Ecological Observatory Network. Front. Ecol. Environ. 2008, 6:282-284.
9. Kratz T.K., et al. Toward a global lake ecological observatory network. Publ. Karelian Inst. 2006, 145:51-63.
10. Fleishman E., et al. Top 40 priorities for science to inform US conservation and management policy. Bioscience 2011, 61:290-300.
11. Hackett E.J., et al. Ecology transformed: the National Center for Ecological Analysis and Synthesis and the changing patterns of ecological research. Scientific Collaboration on the Internet 2008, 277-296. MIT Press. G.M. Olson (Ed.).
12. Peters D.P.C., et al. Living in an increasingly connected world: a framework for continental-scale environmental science. Front. Ecol. Environ. 2008, 5:229-237.
13. Michener W.K., Waide R.B. The evolution of collaboration in ecology: lessons from the United States Long Term Ecological Research Program. Scientific Collaboration on the Internet 2008, 297-310. MIT Press. G.M. Olson (Ed.).
14. Gosz J.R., et al. Twenty-eight years of the US-LTER program: experience, results, and research questions. Long-Term Ecological Research 2010, 59-74. Springer. F. Müller (Ed.).
15. Reichmann O.J., et al. Challenges and opportunities of open data in ecology. Science 2011, 331:703-705.
16. Whitlock M.C. Data archiving in ecology and evolution: best practices. Trends Ecol. Evol. 2010, 26:61-65.
17. Whitlock M.C., et al. Data archiving. Am. Nat. 2010, 175:145-146.
18. Heidorn P.B. Shedding light on the dark data in the long tail of science. Libr. Trends 2008, 57:280-299.
19. Borer E., et al. Some simple guidelines for effective data management. Bull. Ecol. Soc. Am. 2009, 90:205-214.
20. Cook R.B., et al. Best practices for preparing ecological data sets to share and archive. Bull. Ecol. Soc. Am. 2000, 82:138-141.
21. Donnelly M., et al. DMP online: the Digital Curation Centre's web-based tool for creating, maintaining and exporting data management plans. Int. J. Digit. Curation 2010, 5:187-193.
22. Strasser C., et al. DataONE promoting data stewardship through best practices. Proceedings of the Environmental Information Management Conference 2011 (EIM 2011) 2011, 126-131. University of California. M.B. Jones, C. Gries (Eds.).
23. Cowles T., et al. The Ocean Observatories Initiative: sustained ocean observing across a range of spatial scales. Mar. Technol. Soc. J. 2010, 44:54-64.
24. Vanderbilt K., Michener W.K. Information management standards and strategies for net primary production data. Principles and Standards for Measuring Primary Production 2007, 12-26. Oxford University Press. T.J. Fahey, A.K. Knapp (Eds.).
25. Michener W., et al. Long term ecological research and information management. Ecol. Inform. 2011, 6:13-24.
26. Barseghian D., et al. Workflows and extensions to the Kepler scientific workflow system to support environmental sensor data access and analysis. Ecol. Inform. 2010, 5:3-8.
27. Barseghian D., et al. Sensor lifecycle management using scientific workflows. Proceedings of the Environmental Information Management Conference 2011 (EIM 2011) 2011, 33-38. University of California. M.B. Jones, C. Gries (Eds.).
28. Gries C., Porter J.H. Moving from custom scripts with extensive instructions to a workflow system: use of the Kepler workflow engine in environmental information management. Proceedings of the Environmental Information Management Conference 2011 (EIM 2011) 2011, 70-75. University of California. M.B. Jones, C. Gries (Eds.).
29. Lerner B., et al. Provenance and quality control in sensor networks. Proceedings of the Environmental Information Management Conference 2011 (EIM 2011) 2011, 98-103. University of California. M.B. Jones, C. Gries (Eds.).
30. Michener W. Meta-information concepts for ecological data management. Ecol. Inform. 2006, 1:3-7.
31. Fegraus E.H., et al. Maximizing the value of ecological data with structured metadata: an introduction to ecological metadata language (EML) and principles for metadata creation. Bull. Ecol. Soc. Am. 2005, 86:158-168.
32. Jones M.B., et al. Managing scientific metadata. IEEE Internet Comput. 2001, 5:59-68.
33. Rugge, D.J. (2005) Creating FGDC and NBII Metadata using Metavist 2005, Gen. Tech. Rep. NC-255, US Department of Agriculture.
34. Higgins D., et al. Managing heterogeneous ecological data using Morpho. Proceedings of the Fourteenth International Conference on Scientific and Statistical Database Management 2002, 69-76. IEEE Computer Society.
35. Jones M.B., et al. The new bioinformatics: integrating ecological data from the gene to the biosphere. Annu. Rev. Ecol. Syst. 2006, 37:519-544.
36. Marcial L.H., Hemminger B.M. Scientific data repositories on the web: an initial survey. J. Am. Soc. Inf. Sci. Technol. 2010, 61:2029-2048.
37. Cook R. Citations to published data sets. FluxLetter 2008, 1:4-5.
38. Vision T. Open data and the social contract of scientific publishing. Bioscience 2010, 60:330-331.
39. Michener W., et al. DataONE: Data Observation Network for Earth - preserving data and enabling innovation in the biological and environmental sciences. D-Lib Mag. 2011, 17. 10.1045/january2011-michener.
40. Porter J.H., et al. A controlled vocabulary for LTER data keywords. Proceedings of the Environmental Information Management Conference 2011 (EIM 2011), Vol. 103 2011, 18-169. University of California. M.B. Jones, C. Gries (Eds.).
41. Madin J., et al. An ontology for describing and synthesizing ecological observation data. Int. J. Ecol. Inform. 2007, 2:279-296.
42. Madin J.S., et al. Advancing ecological research with ontologies. Trends Ecol. Evol. 2008, 23:159-168.
43. Berkley C., et al. Improving data discovery in metadata repositories through semantic search. Proceedings of iSEEK'09 2009, 1152-1159. IEEE Computer Society.
44. Leinfelder B., et al. Using semantic metadata for discovery and integration of heterogeneous ecological data. Proceedings of the Environmental Information Management Conference (EIM 2011) 2011, 92-97. University of California. M.B. Jones, C. Gries (Eds.).
45. Buccella A., et al. Ontology-driven geographic information integration: a survey of current approaches. Comput. Geosci. 2009, 35:710-723.
46. ® sensor web enablement: overview and high level architecture. IEEE Autotestcon 2007, 372-380.
47. Missier P., et al. Linking multiple workflow provenance traces for interoperable collaborative science. Proceedings of the 5th Workshop on Workflows in Support of Large-Scale Science (WORKS) 2010, 1-8. IEEE.
48. Osterweil L.J., et al. Clear and precise specification of ecological data management processes and dataset provenance. IEEE Trans. Automation Sci. Eng. 2010, 7:189-195.
49. Kernighan B.W., Ritchie D.M. The C Programming Language 1988, Prentice Hall. 2nd edn.
50. Stroustrup B. The C++ Programming Language 1997, Addison-Wesley Professional.
51. Adams J.C., et al. The Fortran 2003 Handbook 2009, Springer.
52. Schwartz R.L., et al. Learning Perl 2011, O'Reilly Media.
53. Lutz M. Learning Python 2009, O'Reilly Media.
54. Hanselman D., Littlefield B. Mastering MATLAB 7 2004, Prentice Hall.
55. Crawley M.J. The R Book 2007, Wiley.
56. Elliott A.C., Woodward W.A. SAS Essentials: A Guide to Mastering SAS for Research 2010, John Wiley and Sons.
57. Ludäscher B., et al. Scientific workflow management and the Kepler system. Special Issue: Workflow Grid Syst. Concurrency and Comput.: Pract. Exp. 2006, 18:1039-1065.
58. De Roure D., et al. The design and realisation of the myExperiment virtual research environment for social sharing of workflows. Future Gen. Comput. Syst. 2009, 25:561-567.
59. Deelman E., et al. Pegasus: a framework for mapping complex scientific workflows onto distributed systems. Sci. Program. J. 2005, 13:219-237.
60. Hull K., et al. Taverna: a tool for building and running workflows of services. Nucleic Acids Res. 2006, 34:729-732.
61. Silva C.T., et al. Provenance for visualizations: reproducibility and beyond. Comput. Sci. Eng. 2007, 9:82-90.
62. Ellison A.M., et al. Analytic webs support the synthesis of ecological data sets. Ecology 2006, 87:1345-1358.
63. Ludäscher B., et al. Scientific process automation and workflow management. Scientific Data Management: Challenges, Technology, and Deployment 2009, 467-509. Chapman & Hall/CRC. A. Shoshani, D. Rotem (Eds.).
64. Taylor I.J., et al. Workflows for e-Science: Scientific Workflows for Grids 2007, Springer.
65. Wang J., et al. Accelerating parameter sweep workfl{ligature}ows by utilizing ad-hoc network computing resources: an ecological example. 2009 World Conference on Services I 2009, 267-274. IEEE.
66. Wang J., et al. Kepler + Hadoop: a general architecture facilitating data-intensive applications in scientific workflow systems. Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science (WORKS09) at Supercomputing 2009 (SC2009) Conference 2009, ACM. 10.1145/1645164.1645176.
67. Servilla M., et al. PASTA: a network-level architecture design for generating synthetic data products in the LTER network. LTER Databits 2006, Fall.
68. Fox P., Hendler J. Changing the equation on scientific data visualization. Science 2011, 331:705-708.
69. Peng R.D., et al. Reproducible epidemiologic research. Am. J. Epidemiol. 2006, 163:783-789.
70. Hollister J.W., Walker H.A. Beyond data: reproducible research in ecology and environmental science. Front. Ecol. Environ. 2007, 5:11-12.
71. Cassey P., Blackburn T.M. Reproducibility and repeatability in ecology. Bioscience 2006, 56:958-959.
72. Goble C.A., et al. myExperiment: a repository and social network for the sharing of bioinformatics workflows. Nucleic Acids Res. 2010, 38(Suppl 2):W677-W682.
73. Halpern, et al. A global map of human impact on marine ecosystems. Science 2008, 319:948-952.
74. Gruner D.S., et al. A cross-system synthesis of consumer and nutrient resource control on producer biomass. Ecol. Lett. 2008, 11:740-755.
75. Reay D.S. Lessons from Climategate. Nature 2010, 467:2010.
76. Bowers S., et al. Provenance in collection-oriented scientific workflows. Concurrency Comput.: Pract. Exp. 2008, 20:519-529.