Data as Social Capital and the Gift Culture in Research

Klump, Jens

doi:10.5334/dsj-2017-014

Cited by 6 publications

(10 citation statements)

References 25 publications

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“…In order to characterize the rarity of data reuse, it is worthwhile to review current data sharing and reuse practices (Borgman 2012; Faniel, Kriesberg, and Yakel 2012; Klump 2017; Shen 2016). A recent survey by Shen (2016) explores the perceived and actual barriers to data sharing and reuse and validates researchers’ perceptions of data value and reusability with their practice of data sharing and reuse.…”

Section: Data Sharing: Practices and Attitudesmentioning

confidence: 99%

“…The similarity between Shen's findings and results emerging from RIN and other sources indicate that archaeologists, despite their attitudes, share and reuse data within a limited scope. A number of factors contribute to this situation: from the low velocity of data acquisition (Borgman 2012) to the closed nature of research communities (Klump 2017:2–3). This article focuses on the costs and obstacles to archaeological data reuse.…”

Section: Data Sharing: Practices and Attitudesmentioning

confidence: 99%

“…Shen (2016) and Faniel, Kriesberg, and Yakel (2012) articulate additional limiting factors such as institutional policies and the lack of standards, time, and funding. Klump (2017) points to varied cultures of sharing among disciplines, which may cancel out even generational change. “Generation Y” doctoral students who behaved as “digital natives” in their private lives have reported following the behaviors of their role model supervisors in academic life (Education for Change 2012).…”

Section: Data Sharing: Practices and Attitudesmentioning

confidence: 99%

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Sociotechnical Obstacles to Archaeological Data Reuse

Sobotková¹

2018

Adv. archaeol. pract.

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The ease of digital data capture and the proliferation of concepts such as the “data deluge” suggest that modern researchers are drowning in datasets. Yet citations of archaeological datasets are few and far between, pointing to low rates of data reuse. This article explores the difficulties that surround data reuse in large-scale regional research, including the cost and coordination necessary to extract useful data from digitized PDF reports. The amount of correction and enhancement matches the effort needed to undertake a small field survey project and can only be circumvented with a thoughtful application of computer-assisted text analysis. Missing data in excavation report PDFs are not only intractable but also insidious due to their concealed nature, leading to poor outcomes in terms of (re)use. Consequently, the degree of data reuse in archaeology has been overestimated.

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Section: Data Sharing: Practices and Attitudesmentioning

confidence: 99%

Section: Data Sharing: Practices and Attitudesmentioning

confidence: 99%

Section: Data Sharing: Practices and Attitudesmentioning

confidence: 99%

See 1 more Smart Citation

Sociotechnical Obstacles to Archaeological Data Reuse

Sobotková¹

2018

Adv. archaeol. pract.

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“…One concrete example of this is an increase in citations for publications that make their data open [19]. In particular, professional credit can be thought of as social capital, and plays a role in the utility of sharing data [20]. This includes (but is not limited to): recognition by tenure and promotion committees, normative recognition of Altmetric milestones [21], and an increased recognition of reanalysis and replication studies as a valid form of scientific discovery [22].…”

Section: Assumptionsmentioning

confidence: 99%

“…This suggests policy is helpful but not sufficient for encouraging data sharing. Klump [20] suggests that the cultural phenomenon of gift-giving is crucial to our understanding of how participation in open data sharing communities can be encouraged. Widely observed in more traditional scientific communities [33], gift-giving might consist of exchanging information for recognition, and exemplified through citation or co-authorship.…”

Section: Limitations and Conclusionmentioning

confidence: 99%

Data Reuse and the Social Capital of Open Science

Alicea

2016

Preprint

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Participation in Open Data initiatives require two semi-independent actions: the sharing of data produced by a researcher or group, and a consumer of shared data. Consumers of shared data range from people interested in validating the results of a given study to transformers of the data. These transformers can add value to the dataset by extracting new relationships and information. The relationship between producers and consumers can be modeled in a game-theoretic context, namely by using a Prisoners' Dilemma (PD) model to better understand potential barriers and benefits of sharing. In this paper, we will introduce the problem of data sharing, consider assumptions about economic versus social payoffs, and provide simplistic payoff matrices of data sharing. Several variations on the payoff matrix are given for different institutional scenarios, ranging from the ubiquitous acceptance of Open Science principles to a context where the standard is entirely non-cooperative. Implications for building a CC-BY economy are then discussed in context.

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Dynamics of cumulative advantage and threats to equity in open science: a scoping review

et al. 2022

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Open Science holds the promise to make scientific endeavours more inclusive, participatory, understandable, accessible and re-usable for large audiences. However, making processes open will not per se drive wide reuse or participation unless also accompanied by the capacity (in terms of knowledge, skills, financial resources, technological readiness and motivation) to do so. These capacities vary considerably across regions, institutions and demographics. Those advantaged by such factors will remain potentially privileged, putting Open Science's agenda of inclusivity at risk of propagating conditions of ‘cumulative advantage’. With this paper, we systematically scope existing research addressing the question: ‘What evidence and discourse exists in the literature about the ways in which dynamics and structures of inequality could persist or be exacerbated in the transition to Open Science, across disciplines, regions and demographics?’ Aiming to synthesize findings, identify gaps in the literature and inform future research and policy, our results identify threats to equity associated with all aspects of Open Science, including Open Access, Open and FAIR Data, Open Methods, Open Evaluation, Citizen Science, as well as its interfaces with society, industry and policy. Key threats include: stratifications of publishing due to the exclusionary nature of the author-pays model of Open Access; potential widening of the digital divide due to the infrastructure-dependent, highly situated nature of open data practices; risks of diminishing qualitative methodologies as ‘reproducibility’ becomes synonymous with quality; new risks of bias and exclusion in means of transparent evaluation; and crucial asymmetries in the Open Science relationships with industry and the public, which privileges the former and fails to fully include the latter.

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Data as Social Capital and the Gift Culture in Research

Cited by 6 publications

References 25 publications

Sociotechnical Obstacles to Archaeological Data Reuse

Sociotechnical Obstacles to Archaeological Data Reuse

Data Reuse and the Social Capital of Open Science

Dynamics of cumulative advantage and threats to equity in open science: a scoping review

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