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Published in:
Ecological Informatics: An Introduction Read chapter Read first chapter

2018 | OriginalPaper | Chapter

7. Data Discovery

Author : William K. Michener

Published in: Ecological Informatics

Publisher: Springer International Publishing

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Abstract

Data may be discovered by searching commercially available internet search engines, institutional and public repositories, online data directories, and the content exposed by data aggregators. Chapter 7 describes these various search approaches and presents seven best practices that can promote data discovery and reuse. It further emphasizes the need for data products to be uniquely identifiable and attributable to the data originators who must also be uniquely identifiable.

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previous chapter Preserve: Protecting Data for Long-Term Use
next chapter Data Integration: Principles and Practice
Footnotes
1
re3data.​org: Macaulay Library; editing status 2014-06-25; re3data.​org—Registry of Research Data Repositories. http://​doi.​org/​10.​17616/​R3CS4N last accessed: 2016-01-14.
 
2
re3data.​org: HJ Andrews Experimental Forest; editing status 2015-05-28; re3data.​org—Registry of Research Data Repositories. http://​doi.​org/​10.​17616/​R3591T last accessed: 2016-01-14.
 
3
re3data.​org: DRYAD; editing status 2015-11-18; re3data.​org—Registry of Research Data Repositories. http://​doi.​org/​10.​17616/​R34S33 last accessed: 2016-01-14.
 
Literature
Barnes N (2010) Publish your computer code: it is good enough. Nature 467:753CrossRef
Cook RB, Wie Y, Hook LA et al (2017) Preserve: protecting data for long-term use, Chapter 6. In: Recknagel F, Michener W (eds) Ecological informatics. Data management and knowledge discovery. Springer, Heidelberg
Duke CS, Porter JH (2013) The ethics of data sharing and reuse in biology. BioSci 63:483–489CrossRef
Ince DC, Hatton L, Graham-Cumming J (2012) The case for open computer programs. Nature 482:485–488CrossRef
Mascaro J, Hughes RF, Schnitzer SA (2012) Novel forests maintain ecosystem processes after the decline of native tree species. Ecol Monogr 82:221–228CrossRef
Michener WK (2017a) Quality assurance and quality control (QA/QC), Chapter 4. In: Recknagel F, Michener W (eds) Ecological informatics. Data management and knowledge discovery. Springer, Heidelberg
Michener WK (2017b) Creating and managing metadata, Chapter 5. In: Recknagel F, Michener W (eds) Ecological informatics. Data management and knowledge discovery. Springer, Heidelberg
Michener W, Vieglais D, Vision T et al (2011) DataONE: Data Observation Network for Earth – preserving data and enabling innovation in the biological and environmental sciences. D-Lib Mag17 (Jan/Feb 2011). doi:10.​1045/​january2011-michener
Michener WK, Allard S, Budden A et al (2012) Participatory design of DataONE—enabling cyberinfrastructure for the biological and environmental sciences. Ecol Inf 11:5–15CrossRef
Peng RD (2011) Reproducible research in computational science. Science 334:1226–1227CrossRef
Porter JH (2017) Scientific databases for environmental research, Chapter 3. In: Recknagel F, Michener W (eds) Ecological informatics. Data management and knowledge discovery. Springer, Heidelberg
Zanne AE, Lopez-Gonzalez G, Coomes DA, et al (2009) Data from: towards a worldwide wood economics spectrum. Dryad Digital Repository. doi:10.​5061/​dryad.​234
Metadata
Title
Data Discovery
Author
William K. Michener
Copyright Year
2018
Book
Ecological Informatics

Print ISBN: 978-3-319-59926-7

Electronic ISBN: 978-3-319-59928-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-59928-1_7