The conundrum of sharing research data

By Christine L. Borgman. 2012

886 citations recorded by the source corpus.

Subfields: Information Systems, Information Systems and Management, Management Science and Operations Research, Social Sciences & Humanities

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

In Social Sciences & Humanities

Citations in the corpus

YFCC100M (2015, background): “The question of sharing data for replication and growth has arisen several times in the past 30 years alone [2, 7, 18] Table 1: Popular multimedia datasets used over the years by the research community.”
The Pushshift Reddit Dataset (2020, background): “2019), a lack of concern for data sharing or reproducibility (Borgman 2012; Weller and Kinder-Kurlanda 2016), and failures to validate constructs or generalize to off-platform behavior (Ekbia et al.”
Critique and Contribute: A Practice-Based Framework for Improving Critical Data Studies and Data Science (2017, background): “30 These ideas support what has been called an interactional view of context, seeing context as ‘‘relational properties occasioned through activi-ty’’(p.5), 28 in which data are not separate from practice.”
Garbage in, garbage out?: do machine learning application papers in social computing report where human-labeled training data comes from? (2019, neutral): “These issues have long been discussed in the fields of library and information science, particularly in Research Data Management [6, 37, 53, 56].”
MeDShare: Trust-Less Medical Data Sharing Among Cloud Service Providers via Blockchain (2017, background): “Cloud service providers are mandated to however provide a controlled, cross-domain and flexible data sharing of medical data stored in their repositories to beneficiaries [12].”
Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide (2015, background): “The prospect of widely available data for all has garnered the attention of such publications as Nature [2,3] and Science [4], in which whole feature sections have been devoted to the topic of "big data," as well as The Economist [5] [6] and The Atlantic [7].”
Uncovering the Challenges in Collection, Sharing and Documentation: The Hidden Data of Social Media Research? (2021, background): “Data sharing is an ‘intricate and difficult problem’ (Borgman 2012).”
The New Data and New Challenges in Multimedia Research (2015, background): “The question of sharing data for replication and growth has arisen several times in the past 30 years alone [13–15] and has been brought into discussion in ACM’s SIGCHI [16].”
Data Sharing in Psychology: A Survey on Barriers and Preconditions (2018, methodology): “In a qualitative study, Wallis, Rolando and Borgman (2013) found that the five most important conditions were: (1) first rights to publish results; (2) proper attribution of the data source; (3) familiarity between sharer and recipient; (4) funding agency expectations; and (5) the amount of effort r”
If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology (2013, methodology): “Dimensions identified elsewhere include (1) the specificity of purposes for collecting data, ranging from exploratory research to building observatories, (2) scope of data collection, from describing particular events or phenomena to modeling systems, and (3) goal of the research, from empirical to ”
Big data, bigger dilemmas: A critical review (2015, background): “The growing Big Data trend has also prompted a series of reflective engagements with the topic that, although few and far between, introduce stimulating insights and critical questions (e.g., Borgman, 2012; boyd & Crawford, 2012).”
Construction with digital twin information systems (2020, background): “” Data-Centric Engineering e14-13 Kitchin (2014) reasoned that data refer to those elements that are “ taken ” (derived from the Latin “ capere ” ), for example, “ extracted through observations, computations, experiments, and record keeping ” (Borgman, 2012).”