Where Have All the Scientific Data Gone? LIS Perspective on the Data-At-Risk Predicament

Abstract

Scientists produce vast amounts of data that often are not preserved properly or do not have inventories, placing them at risk. As part of an effort to more fully understand the data-at-risk predicament, researchers who were engaged in the DARI project at UNC's Metadata Research Center surveyed information custodians working in a range of settings. The survey collected information on the data characteristics and preservation plans. Forty-three information custodians completed the survey. The results indicate that atrisk data include a variety of formats, subject areas, and ownership status, as well as compliance with a variety of standards. Although a majority of respondents agree that data preservation is important, they caution that time is the greatest barrier to sharing these data. The study has implications for data rescue and for training information custodians.xperimental and observational data are central to scientific research. With a growing pool of scientific data, researchers have the potential to investigate new questions and use new analytical techniques. To enable this data revolution, the National Science Foundation has funded initiatives to develop cyberinfrastructure for managing, preserving, and sharing scientific data.1 In addition to infrastructure development, there are increasing expectations of open access and new mandates for scientific data management and sharing. For instance, on February 22, 2013, the U.S. Office of Science and Technology Policy released a memo directing federal agencies to increase public access to federal research publications and digital data.2 The memo called for federal agencies with over $100 million in research and development expenditures to develop policies and a plan for access and long-term preservation of government-sponsored research products. Open access presents many challenges for scientists. Scientists are so concerned about data sharing and preservation that the editors of Science recently devoted a special issue to the topic.

Factors influencing research data communication on Zika virus: a grounded theory

“…The use of English represents an additional effort required for open communication in the process of data registry. The interviewees' opinion was that data processing is a hindrance to open communication, which seems to be in accordance with issues discussed by Dallmeier-Tiessen et al (2014), Thompson et al (2014), and Douglass et al (2014). According to the authors, data processing for open communication requires more time and effort, as it is necessary to structure the data according to a given standard, or describe the data more thoroughly than the original research would require.…”

“…The authors did not explore the nuances of the relationship, they just pointed it out. In the same sense Sturges et al (2015), Gardner (2004) and Thompson et al (2014) and Dallmeier-Tiessen et al (2014) presented the theme as one of the barriers to the wide communication of research data.…”

“…Papers selected for systematized review LISA search argument [(ti ("research data") OR ti ("scientific data")) AND sharing]. mid 2016 Sturges et al (2015), Higman and Pinfield (2015), Whitmire et al (2015), Knight (2015), Thompson et al (2014), Melero and Hernández-San-Miguel (2014), Douglass et al (2014), Dallmeier-Tiessen et al (2014), Bond et al (2013), Cox et al (2012), Losoff (2009), Childs and Mcleod (2004) and Gardner (2004).…”

Risk Assessment for Scientific Data

“…The time required to create metadata, reformat files, create contingency plans, and communicate these efforts to user communities can be considerable. This time investment can be the greatest barrier to performing risk assessment and mitigation activities (Thompson, Robertson & Greenberg, 2014). Putting focus on assessment of data risk factors may mean that "certain priorities need to be re-ordered, new skills acquired and taught, resources redirected, and new networks constructed" (Griffin 2015, pg.…”

Where Does All the Data Go: Quantifying the Final Disposition of Research Data

“…Studies of the final disposition of research data are sparse. Much of the quantitative data used in the literature was collected as part of a project to develop systems, services, and policies for data preservation within a single organization or a consortium (Fear, 2011;Henty et al, 2008;Rolando, Doty, Hagenmaier, Valk, & Parham, 2013;Thompson, Robertson, & Greenberg, 2013).…”