Research Presentations - CIRSS http://hdl.handle.net/2142/9713 Mon, 30 May 2016 20:29:14 GMT 2016-05-30T20:29:14Z Site-Based Data Curation at Yellowstone National Park http://hdl.handle.net/2142/44836 Site-Based Data Curation at Yellowstone National Park Palmer, Carole L.; Varvel, Virgil E., Jr.; Thomer, Andrea K.; Baker, Karen S.; Wickett, Karen M.; Fouke, Bruce W.; Asangba, Abigail E.; Rodman, Ann; Choudhury, G. Sayeed; DiLauro, Tim The Site-Based Data Curation (SBDC) project at the University of Illinois at Urbana-Champaign is developing a framework of policies and processes for the curation of research data generated at scientifically significant sites. The model will be built around the case of systems geobiology at Yellowstone National Park. Research Data Curation; Yellowstone National Park Mon, 01 Apr 2013 00:00:00 GMT http://hdl.handle.net/2142/44836 2013-04-01T00:00:00Z Palmer, Carole L. Varvel, Virgil E., Jr. Thomer, Andrea K. Baker, Karen S. Wickett, Karen M. Fouke, Bruce W. Asangba, Abigail E. Rodman, Ann Choudhury, G. Sayeed DiLauro, Tim Data practices across disciplines: Informing collections & curation. http://hdl.handle.net/2142/30641 Data practices across disciplines: Informing collections & curation. Palmer, Carole L. data practices; DataNet; data curation Wed, 09 Feb 2011 00:00:00 GMT http://hdl.handle.net/2142/30641 2011-02-09T00:00:00Z Palmer, Carole L. Data sharing practices: Implications for curation and re-use. http://hdl.handle.net/2142/30640 Data sharing practices: Implications for curation and re-use. Palmer, Carole L. data sharing, data practices, data re-use Thu, 13 Oct 2011 00:00:00 GMT http://hdl.handle.net/2142/30640 2011-10-13T00:00:00Z Palmer, Carole L. Integrating Conceptual and Empirical Studies of Data to Guide Curatorial Processes http://hdl.handle.net/2142/30634 Integrating Conceptual and Empirical Studies of Data to Guide Curatorial Processes Palmer, Carole L.; Chao, Tiffany C.; Weber, Nicholas M.; Sacchi, Simone Two research teams within the Data Conservancy (http://dataconservancy.org/) project are investigating different aspects of scientific data curation. Data Concepts is developing a conceptual model to foster shared understanding of identity conditions and representation levels for data sets. Data Practices is conducting qualitative studies of data production and use in the earth and life sciences, analyzing curation needs, cultures of sharing, and re-use potential across disciplines. This poster will illustrate the integration of results from three phases of research to develop a more comprehensive and practical analysis of fundamental aspects of data curation. • Phase 1, Data Concepts team - Preliminary framework for definitions of “dataset” based on review of technical documentation and scientific literature, to support curation and integration of data across disciplines. Found four common features across definitions--grouping, content, relatedness, and purpose, elaborating each based on evidence from the literature. • Phase 2, Data Practices team - Conceptual mapping of data characteristics, data practices, and curation activities, consisting of approximately 145 terms. Emphasizes relationships between data practices and curatorial activities for application to description and assessment of curation services. • Phase 3, Data Practices team - Analytic potential concept developed as a theoretical approach to assessing the value of data beyond its original intended use. Extends Hjørland’s (1997) notion of “epistemological potential”, acknowledging the essential condition of preservation readiness and two key interrelated factors, potential user communities and fit for purpose. We will demonstrate how the Phase 1 framework has been tested and extended based on empirical data and analysis from Phases 2-3. In particular, we show how scientists’ practices and ideas about meaningful units of data adhere to and diverge from the framework’s conception of “grouping”. We also identify and discuss additional elements of “purpose” needed to inform the curatorial processes of selection and appraisal and set curation priorities for making data fit for long-term use. data practices, data concepts, data curation, scientific research data Thu, 22 Mar 2012 00:00:00 GMT http://hdl.handle.net/2142/30634 2012-03-22T00:00:00Z Palmer, Carole L. Chao, Tiffany C. Weber, Nicholas M. Sacchi, Simone What Dataset Descriptions Actually Describe: Using the Systematic Assertion Model to Connect Theory and Practice http://hdl.handle.net/2142/30470 What Dataset Descriptions Actually Describe: Using the Systematic Assertion Model to Connect Theory and Practice Wickett, Karen M.; Thomer, Andrea; Sacchi, Simone; Baker, Karen S.; Dubin, David Scientific data is encoded and described with the aim of supporting retrieval, meaningful interpretation and reuse. Encoding standards for datasets like FGDC, DwC, EML typically include tagged metadata elements along with the encoded data, suggesting that, per the Dublin Core 1:1 principle, those elements apply to one and only one entity (a specimen, observation, dataset, etc.). However, in practice vocabularies are often used to describe different dimensions of scientific data collection and communication processes. Discriminating these aspects offers a more precise account of how symbols and the propositions they express acquire the status of “data” and “data content,” respectively. In this poster we present an analysis of species occurrence records basecd on the Systematic Assertion Model (SAM) [DWS]. SAM is a framework for describing the encoding and representation of scientific data, bridging the gap between data preservation models and discipline-specific scientific ontologies. The model is intended to be general enough for any scientific domain, and not bound to any particular methodology or field of study. Since species occurrence records are a kind of data that is frequent re-used, migrated across systems and shared they are a good target for analysis. Sample data is reviewed in the context of SAM, and analyzed with respect to the provenance events, entities, and relationships governing our definitions of data and data content. The exercise serves to: 1. highlight targets for data description (expression, content, assertion, justification). 2. inform the discovery of anomalous or missing contextual/background information. 3. frame a comparison of generic metadata standards (e.g. Dublin Core) with standards created specifically for scientific use (FGDC, DwC, EML). 4. clarify competing criteria for the identification of data that is tied to the scientific assertions carried by a dataset, and not specific to the details of a format or encoding. Metadata, Scientific Data, Data Curation Thu, 22 Mar 2012 00:00:00 GMT http://hdl.handle.net/2142/30470 2012-03-22T00:00:00Z Wickett, Karen M. Thomer, Andrea Sacchi, Simone Baker, Karen S. Dubin, David Research Practices and Research Libraries: Working Toward High Impact Information Services http://hdl.handle.net/2142/9742 Research Practices and Research Libraries: Working Toward High Impact Information Services Palmer, Carole L. information use; academic libraries; scholarly research behavior; Arrowsmith Project; data curation; digital information use Sun, 01 Jun 2008 00:00:00 GMT http://hdl.handle.net/2142/9742 2008-06-01T00:00:00Z Palmer, Carole L. The Primitives and Potentials of Digital Scholarship: Where Does Research Librarianship Begin? http://hdl.handle.net/2142/9717 The Primitives and Potentials of Digital Scholarship: Where Does Research Librarianship Begin? Palmer, Carole L. collection development; scholarly communication; netchaining; research librarianship; academic librarianship Wed, 01 Oct 2008 00:00:00 GMT http://hdl.handle.net/2142/9717 2008-10-01T00:00:00Z Palmer, Carole L. Preparing e-Science Information Specialists: New Programs and Professionals http://hdl.handle.net/2142/9716 Preparing e-Science Information Specialists: New Programs and Professionals Palmer, Carole L. Academic librarianship; data curation education; biological informatics; information transfer; librarianship Wed, 01 Oct 2008 00:00:00 GMT http://hdl.handle.net/2142/9716 2008-10-01T00:00:00Z Palmer, Carole L. Contouring Curation for Disciplinary Difference and the Needs of Small Science http://hdl.handle.net/2142/9715 Contouring Curation for Disciplinary Difference and the Needs of Small Science Palmer, Carole L. Empirical studies of the information practices and needs of scientists date back to at least the 1940s. This work has increasingly focused on identifying differences across disciplines, but it has been primarily concerned with information seeking, retrieval, and use of the literature, and more recently on searching of web-based documents. Studies of scientific data practices are in their infancy, relatively speaking, yet they are essential for guiding development of data curation principles and repository services. Current data curation research at CIRSS is taking multiple approaches to studying data practices and curation requirements within and across sciences, to build our understanding of how data repositories can best facilitate future interdisciplinary and multi-scale science. This presentation will highlight the comparative approach being applied in the Curation Profiles Project, a partnership between Purdue University Libraries and CIRSS, to analyze scientific workflows and research outputs in twelve disciplines, to identify needs for discovery, access, usage, and re-use of data. Three additional studies that address problems associated with moving small science “research” collections into “resource” level repositories will also be discussed. A case study in neuroscience provides insights into the emergent roles of shared disciplinary data repositories, a survey of environmental scientists demonstrates the complexities of supporting diverse institution-based research communities, and a cultural heritage digital aggregation project foregrounds important problems representing scale, granularity, context, and long-term analytical potential in large-scale collections of collections. data curation; institutional repositories; Scholarly collaboration; digital collections; scientific collaboration Wed, 01 Oct 2008 00:00:00 GMT http://hdl.handle.net/2142/9715 2008-10-01T00:00:00Z Palmer, Carole L. Investing in Collection Representation For More Useful Repositories http://hdl.handle.net/2142/9714 Investing in Collection Representation For More Useful Repositories Palmer, Carole L. institutional repositories; digital collections; Collection development (Libraries); Metadata; scholarly communication Mon, 01 Oct 2007 00:00:00 GMT http://hdl.handle.net/2142/9714 2007-10-01T00:00:00Z Palmer, Carole L.
https://www.ideals.illinois.edu/feed/rss_2.0/2142/9713
www.ideals.illinois.edu
crawl=CC-MAIN-2016-22
13634
application/http; msgtype=response
sha1:IXEKATH2IT2VIYT6WQSZ3UZ4666R7XWZ
<urn:uuid:13a8a857-a07a-4bc2-90c0-9da925652655>
2016-05-30T20:29:14Z
192.17.174.8
sha1:VNSCRMQYE4KQYDSZKGPKBXM6QX4ZQNRW
<urn:uuid:2afbc65a-c2a2-4166-add8-065010186e71>
https://www.ideals.illinois.edu/feed/rss_2.0/2142/9713
response
<urn:uuid:230504c1-e4c7-4c5a-b1e5-0aaeb8d84527>
robots: classic
hostname: ip-10-185-217-139.ec2.internal
software: Nutch 1.6 (CC)/CC WarcExport 1.0
isPartOf: CC-MAIN-2016-22
operator: CommonCrawl Admin
description: Wide crawl of the web for May 2016
publisher: CommonCrawl
format: WARC File Format 1.0
conformsTo: http://bibnum.bnf.fr/WARC/WARC_ISO_28500_version1_latestdraft.pdf