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Biblio

Author Title [ Type(Desc)] Year
Filters: First Letter Of Last Name is P  [Clear All Filters]
Book Chapter
Dey S, Köhler S, Bowers S, Ludäscher B. Computing Location-Based Lineage from Workflow Specifications to Optimize Provenance Queries. In: Ludäscher B, Plale B, eds. Provenance and Annotation of Data and Processes.Vol 8628. Provenance and Annotation of Data and Processes. Springer International Publishing; 2015:180-193. Available at: http://dx.doi.org/10.1007/978-3-319-16462-5_14.
Conference Paper
Tuarob S, Pouchard LC, C. Giles L. Automatic Tag Recommendation for Metadata Annotation Using Probabilistic Topic Modeling. In: Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries. Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries. New York, NY, USA: ACM; 2013. Available at: http://doi.acm.org/10.1145/2467696.2467706.
Pardo TA, Sayogo DS. Exploring the determinants of publication of scientific data in open data initiative. In: Proceedings of the 5th International Conference on Theory and Practice of Electronic Governance. Proceedings of the 5th International Conference on Theory and Practice of Electronic Governance. Tallinn, Estonia; 2011. Available at: http://doi.acm.org/10.1145/2072069.2072087.
Sayogo DS, Pardo TA. Exploring the Motive for Data Publication in Open Data Initiative: Linking Intention to Action. In: 2012 45th Hawaii International Conference on System Sciences (HICSS). 2012 45th Hawaii International Conference on System Sciences (HICSS). Maui, HI, USA: IEEE; 2012.
Salayandia L, Gates AQ, Pennington D. MetaShare: Constructing Actionable Data Management Plans through Formal Semantics. In: Research Data Management Implementations Workshop. Research Data Management Implementations Workshop.; 2013.
Tenopir C, Pollock D, Allard S, Hughes D. Research Data Services in European and North American Libraries: Current Offerings and Plans for the Future. In: Proceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives Through Information & Technology. Proceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives Through Information & Technology. Silver Springs, MD, USA: American Society for Information Science; 2016. Available at: http://dl.acm.org/citation.cfm?id=3017447.3017576.
Pollock D. Understanding Scientific Data Sharing Outside of the Academy. In: Proceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives Through Information & Technology. Proceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives Through Information & Technology. Silver Springs, MD, USA: American Society for Information Science; 2016. Available at: http://dl.acm.org/citation.cfm?id=3017447.3017591.
Sayogo DS, Pardo TA. Understanding the Capabilities and Critical Success Factors for Scientific Data Sharing in DataONE Collaborative Network. In: Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times . Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times . College Park, MarylandNew York, New York, USA: ACM Press; 2011.
Journal Article
Levy O, Ball BA, Bond-Lamberty B, et al. Approaches to advance scientific understanding of macrosystems ecology. Frontiers in Ecology and the Environment. 2014;12:15–23. Available at: http://dx.doi.org/10.1890/130019.
Hardisty AR, Michener WK, Agosti D, et al. The Bari Manifesto: An interoperability framework for essential biodiversity variables. Ecological Informatics. 2018. Available at: http://www.sciencedirect.com/science/article/pii/S1574954118301961.
Hampton SE, Strasser CA, Tewksbury JJ, et al. Big data and the future of ecology. 2013;11(3):156 - 162.
Mason SJK, Cleveland SB, Llovet P, Izurieta C, Poole GC. A centralized tool for managing, archiving, and serving point-in-time data in ecological research laboratories. Environmental Modelling & Software. 2014;51:59 - 69. Available at: http://www.sciencedirect.com/science/article/pii/S1364815213001990.
Tenopir C, Dalton ED, Allard S, et al. Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide. PLoS ONE . 2015;10(8).
Tenopir C, Dalton ED, Allard S, et al. Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide. PLoS ONE . 2015;10(8).
McKinley DC, Miller-Rushing AJ, Ballard HL, et al. Citizen science can improve conservation science, natural resource management, and environmental protection. The role of citizen science in biological conservation. 2017;208:15 - 28. Available at: http://www.sciencedirect.com/science/article/pii/S0006320716301963.
McKinley DC, Miller-Rushing AJ, Ballard HL, et al. Citizen science can improve conservation science, natural resource management, and environmental protection. The role of citizen science in biological conservation. 2017;208:15 - 28. Available at: http://www.sciencedirect.com/science/article/pii/S0006320716301963.
McKinley DC, Miller-Rushing AJ, Ballard HL, et al. Citizen science can improve conservation science, natural resource management, and environmental protection. The role of citizen science in biological conservation. 2017;208:15 - 28. Available at: http://www.sciencedirect.com/science/article/pii/S0006320716301963.
Osterweil LJ, Clarke LA, Ellison AM, et al. Clear and precise specification of ecological data management processes and dataset provenance. 2010;7(1).
Dickinson JL, Shirk J, Bonter D, et al. The current state of citizen science as a tool for ecological research and public engagement. Frontiers in Ecology and the Environment. 2012;10(6):291 - 297.
Dickinson JL, Shirk J, Bonter D, et al. The current state of citizen science as a tool for ecological research and public engagement. Frontiers in Ecology and the Environment. 2012;10(6):291 - 297.
Piwowar HA, Vision TJ, Whitlock MC. Data archiving is a good investment. Nature. 2011;473(7347):285 - 285.
Wu M, Psomopoulos F, Khalsa SJ, de Waard A. Data Discovery Paradigms: User Requirements and Recommendations for Data Repositories. Data Science Journal. 2019;18(1).
Pouchard L, Barton A, Zilinski L. Data narratives: Increasing scholarly value. Proceedings of the American Society for Information Science and Technology. 2014;51:1–4. Available at: http://dx.doi.org/10.1002/meet.2014.14505101088.

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