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How can I encourage researchers to manage their data?

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  • Determine researchers' data management needs
  • Provide training and resources to researchers to help manage data
  • Implement an outreach program to inform researchers of available data management resources

 

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This presentation outlines strategies for implementing a data management outreach program.

Software Carpentry is a volunteer organization whose members teach basic software skills to researchers in science, engineering, and medicine. Founded in 1998, we are now part of the Mozilla Science Lab.

The UK Data Archive's Managing and Sharing Data: Training Resources presents a suite of flexible training materials for people who are charged with training researchers and research support staff in how to look after research data.

 

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Scientific data management encompasses a variety of concepts and methods to foster continuing access and long-term stewardship of data for current and future users. Considering the needs for scientific data management knowledge and capabilities to facilitate improved and persistent accessibility and use of scientific data throughout the data lifecycle, instruction on topics in scientific data management is recommended for data science education and workforce development programs for science communities.

 

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The authors present findings from a UKRDS survey of researchers' views on practices for preservation and dissemination of research data in four UK universities (Bristol, Leeds, Leicester, and Oxford) and place them in the wider UK and international context.

  • Cragin, Melissa H., Carole L. Palmer, and Tiffany C. Chao. “Relating Data Practices, Types, and Curation Functions: An Empirically Derived Framework.” Proceedings of the American Society for Information Science and Technology 47, no. 1 (November 2010): 1–2. doi:10.1002/meet.14504701426. http://doi.wiley.com/10.1002/meet.14504701426.

We present a general conceptual framework that maps relationships and dependencies among scientific data practices, types of data produced and used, and associated curation activities. As part of the Data Conservancy initiative, the framework is being elaborated through empirical studies of data practices in the earth sciences and life science and validated against use cases as curatorial services are developed around data being prepared for ingest into the repository. The framework can be applied more broadly for identifying and representing curation requirements and to support description and assessment of existing or planned curation infrastructure and services. It will support full accounts of the data products and workflows required to maintain the coherence and context of complex data collections.

  • Martin, Elaine, and Tracey Leger-Hornby. “Frameworks for a Data Management Curriculum.” University of Massachusetts Medical School Lamar Soutter Library & Worcester Polytechnic Institute George C. Gordon Library, February 2012. http://library.umassmed.edu/data_management_frameworks.pdf.

The Frameworks for a Data Management Curriculum packet has been developed for teaching research data management to undergraduate and graduate level students in the sciences, health sciences, and engineering disciplines. The curriculum has been designed as a series of seven course modules in order to allow maximum flexibility for customizing instruction. With this framework model, faculty have the option to integrate the entire series of modules into a program of study or select individual modules that target their students‟ learning needs.

What are the roles necessary to effective data management and what kinds of expertise are needed by the researchers and data specialists who are filling those roles? These questions were posed at a workshop of data creators and curators whose delegates challenged the DCC and RIN to identify the training needs and career opportunities for the broad cohort that finds itself working in data mnagement--sometimes by design but more often by accident.  This paper revisits previous investigations into the roles and responsibilities required by a "data workforce," presents a representative spectrum of informed opinion from the DCC Research Data Management Forum, and makes some recommendations for raising capability, capacity and status.

Data management is a timely and increasingly important topic for ecologists. Recent funder mandates requiring data management plans, combined with the data deluge that faces scientists, make education about data management critical for any future ecologist. In this study, we surveyed instructors of general ecology courses at 48 major institutions in the United States...We found that, in general, data management topics are not being covered in undergraduate ecology courses for a wide range of reasons. Most often, instructors cited a lack of time and a lack of resources as barriers to teaching data management. Although data are used for instruction at some point in the majority of the courses surveyed, good data management practices and a thorough understanding of the importance of data stewardship are not being taught. We offer potential explanations for this and suggestions for improvement.

  • Tenopir, Carol, Suzie Allard, Kimberly Douglass, Arsev Umur Aydinoglu, Lei Wu, Eleanor Read, Maribeth Manoff, and Mike Frame. “Data Sharing by Scientists: Practices and Perceptions.” Edited by Cameron Neylon. PLoS ONE 6, no. 6 (June 29, 2011): e21101. doi:10.1371/journal.pone.0021101. http://dx.plos.org/10.1371/journal.pone.0021101

Scientific research in the 21st century is more data intensive and collaborative than in the past. It is important to study the data practices of researchers – data accessibility, discovery, re-use, preservation and, particularly, data sharing. Data sharing is a valuable part of the scientific method allowing for verification of results and extending research from prior results.  A total of 1329 scientists participated in this survey exploring current data sharing practices and perceptions of the barriers and enablers of data sharing...Barriers to effective data sharing and preservation are deeply rooted in the practices and culture of the research process as well as the researchers themselves.

  • Ward, Catharine, Lesley Freiman, Sarah Jones, Laura Molloy, and Kellie Snow. “Making Sense: Talking Data Management with Researchers.” International Journal of Digital Curation 6, no. 2 (October 7, 2011). doi:10.2218/ijdc.v6i2.202.

We found that many researchers: (i) organise their data in an ad hoc fashion, posing difficulties with retrieval and re-use; (ii) store their data on all kinds of media without always considering security and back-up; (iii) are positive about data sharing in principle though reluctant in practice; (iv) believe back-up is equivalent to preservation...We are employing a bottom-up approach as we feel that to support the step-by-step development of sound research data management practices, you must first understand researchers’ needs and perspectives.



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