If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology

By Jillian C. Wallis, E. Rolando, Christine L. Borgman. PLoS ONE, 2013

455 citations recorded by the source corpus.

Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies. CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities.

Subfields: Information Systems, Information Systems and Management, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/4d12b00963aa6e0d9b9b84a62f0543de608fccb5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

In Information Systems and Management

In Management Science and Operations Research

Citations in the corpus

On the Reuse of Scientific Data (2017, background): “Examples of sharing include private exchanges between researchers; posting datasets on researchers’ or laboratory websites; depositing datasets in archives, repositories, domain-specific collections, or library collections; and attaching data as supplemental materials in journal articles (Wallis et ”
Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda (2021, background): “On a general note, data reuse can lead to more findings from the same dataset (Joo, Kim, & Kim, 2017), to asking new questions (Wallis, Rolando, & Borgman, 2013), to testing different hypotheses (Kim & Adler, 2015), and to increasing the knowledge in the field (Joo et al., 2017).”
Impediment to insight to innovation: understanding data assemblages through the breakdown–repair process (2016, background): “…common expectation in academia, and while it presents enormous potential for furthering academic research, the practice comes with a host of challenges (e.g. Borgman, 2007; Edwards et al., 2013; Trainer, Chaihirunkarn, Kalyanasundaram, & Herbsleb, 2015; Wallis, Rolando, & Borgman, 2013).”
Data Sharing in Psychology: A Survey on Barriers and Preconditions (2018, methodology): “Our questionnaire items were based on earlier surveys (Cheah et al., 2015; Sayogo & Pardo, 2013; Schmidt et al., 2016; Tenopir et al., 2011; Wallis et al., 2013) and a discussion at a meeting of experts on reproducibility, held in Oxford in 2015.”
Singularity: Scientific containers for mobility of compute (2017, background): “…nature coupled with distribution-specific software builds meant that service providers would ultimately end up limiting the scope of computational science that their systems could support, leaving out the long tails of science [12–14] and scientific diversity of nontraditional HPC user bases.”
Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide (2015, background): “Yet even with these assurances, such direct requests for data are rare [17].”