Dealing with Data: A Case Study on Information and Data Management Literacy

Haendel, Melissa; Vasilevsky, Nicole; Wirz, J

doi:10.1371/journal.pbio.1001339

Cited by 53 publications

(35 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The knowledge factor becomes apparent in Sieber's study [43] in which most researchers stated that data sharing is advantageous for science, but that they had not thought about it until they were asked for their opinion. Missing knowledge further relates to poor curation and storing skills [33,44] and missing knowledge regarding adequate repositories [21,42]. In general, missing knowledge regarding the existence of databases and know-how to use them is described as a hindering factor for data sharing.…”

Section: Resources Neededmentioning

confidence: 99%

What Drives Academic Data Sharing?

2014

View full text Add to dashboard Cite

Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher's point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded as knowledge commons, but research policies that better incentivise data sharing are needed to improve the quality of research results and foster scientific progress.

show abstract

Section: Resources Neededmentioning

confidence: 99%

What Drives Academic Data Sharing?

2014

View full text Add to dashboard Cite

show abstract

“…New standards in information and data literacy need to be developed for data and information curation, and libraries are the natural experts in data management and can provide the institutional level of support to permeate these standards into the local cultures (Haendel et al, 2012) -that is, both to the individual scientist's level as well as the institutional level including that of public administration. Already, technological developments and international projects in fields such as astrophysics and bioscience preordain the path for the future of data curation through the combined deposition and query of all data available on an object of interest.…”

Section: Discussionmentioning

confidence: 99%

“…This process requires an information structure that facilitates the distribution and accessibility of content, that is, data, information and knowledge, over time and distance (Luzi, 2010). Barriers in sharing and unsolved complexities in structuring and managing knowledge have been identified as the major bottlenecks in the knowledge-building process (Borgman, 2011;Haendel et al, 2012;Whitlock et al, 2010). Numerous initiatives and international strategies have been set up recently to promote open science and the creation of structured knowledge, particularly aiming at (research) data curation and sharing.…”

Section: S Uhlemann Et Al: Data Expansion: the Potential Of Grey LImentioning

confidence: 99%

Data expansion: the potential of grey literature for understanding floods

Uhlemann

Bertelmann

Merz

2013

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Sophisticated methods have been developed and become standard in analysing floods as well as for assessing flood risk. However, increasingly critique of the current standards and scientific practice can be found both in the flood hydrology community as well as in the risk community who argue that the considerable amount of information already available on natural disasters has not been adequately deployed and brought to effective use. We describe this phenomenon as a failure to synthesize knowledge that results from barriers and ignorance in awareness, use and management of the entire spectrum of relevant content, that is, data, information and knowledge. In this paper we argue that the scientific community in flood risk research ignores event-specific analysis and documentations as another source of data. We present results from a systematic search that includes an intensive study on sources and ways of information dissemination of flood-relevant publications. We obtain 186 documents that contain information on the sources, pathways, receptors and/or consequences for any of the 40 strongest trans-basin floods in Germany in the period 1952-2002. This study therefore provides the most comprehensive metadata collection of flood documentations for the considered geographical space and period. A total of 87.5 % of all events have been documented, and especially the most severe floods have received extensive coverage. Only 30 % of the material has been produced in the scientific/academic environment, and the majority of all documents (about 80 %) can be considered grey literature (i.e. literature not controlled by commercial publishers). Therefore, ignoring grey sources in flood research also means ignoring the largest part of knowledge available on single flood events (in Germany). Further, the results of this study underpin the rapid changes in information dissemination of flood event literature over the last decade. We discuss the options and obstacles of incorporating this data into the knowledge-building process in light of the current technological developments and international, interdisciplinary debates for data curation.

show abstract

“…15 The advantages of data sharing are many. Scholars may benefit from accessing and using data produced by others, from preserving and sharing their own data, and from the benefits to research and the public good which can derive from the sharing and reuse of data.…”

mentioning

confidence: 99%

Data Curation: A Study of Researcher Practices and Needs

McLure¹,

Level²,

Cranston³

et al. 2014

pla

View full text Add to dashboard Cite

Colorado State University librarians conducted five focus groups with thirty-one faculty, research scientists, and research associates. The groups explored: (1) The nature of data sets that these researchers create or maintain; (2) How participants manage their data; (3) Needs for support that the participants identify in relation to sharing, curating, and preserving their data; and (4) The feasibility of adapting the Purdue University Libraries' Data Curation Profiles Toolkit 1 interview protocol for use in focus groups with researchers. The authors report their review of related literature, themes that emerged from analysis of the focus groups, and implications for related library services.

show abstract

Dealing with Data: A Case Study on Information and Data Management Literacy

Abstract: The launch of the eagle-i Consortium, a collaborative network for sharing information about research resources, such as protocols and reagents, provides a vivid demonstration of the challenges that researchers, libraries and institutions face in making their data available to others.

Cited by 53 publications

References 9 publications

What Drives Academic Data Sharing?

What Drives Academic Data Sharing?

Data expansion: the potential of grey literature for understanding floods

Data Curation: A Study of Researcher Practices and Needs

Contact Info

Product

Resources

About