Open data in the life sciences: the ‘Selfish Scientist Paradox’

Damalas, D.; Kalyvioti, G.; Sabatella, Evelina; Στεργίου, Κωνσταντίνος Ι.

doi:10.3354/esep00182

Cited by 8 publications

(8 citation statements)

References 36 publications

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“…Others view data sharing as a threat to intellectual property, professional value and economic benefits 166 . The greater value placed on publications by institutions has the potential to discourage data sharing 164 .…”

Section: Resultsmentioning

confidence: 99%

“…In reality, scientist are not as forthcoming with their data as expected [158][159][160][161][162][163] . Similarly, there are divergent views on the extent of data sharing among researchers and reported variations are contingent on career ranking and years of experience 159,164 . This difference may be associated with professional disciplines.…”

Section: Incentivisation Of Data Contributors and Usersmentioning

confidence: 99%

“…The greater value placed on publications by institutions may also be discouraging data sharing 164 .…”

mentioning

confidence: 99%

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Considerations for an integrated population health databank in Africa: lessons from global best practices

et al. 2021

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Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa. Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software © enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing. Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing. We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access. Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.

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Section: Resultsmentioning

confidence: 99%

Section: Incentivisation Of Data Contributors and Usersmentioning

confidence: 99%

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Considerations for an integrated population health databank in Africa: lessons from global best practices

et al. 2021

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“…Depending on the location, researchers might follow different open science rules. For instance, European researchers might be influenced by mandates from Horizon 2020, while those in other regions may operate under different guidelines (Damalas et al, 2018). Some cultures value group knowledge, while others value individual work, affecting how they view open sharing.…”

Section: Researchers' Characteristics and Backgroundmentioning

confidence: 99%

Factors Influencing Open Science Participation Through Research Data Sharing and Reuse Among Researchers: a Systematic Literature Review

Ahmed

2023

Preprint

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This systematic literature review investigates the influential factors guiding researchers' active engagement in open science through research data sharing and subsequent reuse, spanning various scientific disciplines. The review seeks to address key objectives and questions, including the identification of distinct sample types, data collection methods, critical factors, and existing gaps within the body of literature concerning data sharing and reuse in open science. The methodology employed in the review was detailed, outlining a series of systematic steps. These steps encompass the systematic search and selection of relevant studies, rigorous data extraction and analysis, comprehensive evaluation of selected studies, and transparent reporting of the resulting findings. The review's evaluation process was governed by well-defined inclusion and exclusion criteria, encompassing publication dates, language, study design, and research outcomes. Furthermore, it adheres to the PRISMA 2020 flow diagram, effectively illustrating the progression of records through the review stages, highlighting the number of records identified, screened, included, and excluded. The findings include a concise tabular representation summarizing data extracted from the 51 carefully selected studies incorporated within the review. The table provides essential details, including study citations, sample sizes, data collection methodologies, and the key factors that influence data sharing and reuse within the realm of open science. Additionally, common themes and categories among these influential factors are identified, shedding light on overarching trends in the field. In conclusion, this systematic literature review offers valuable insights into the multifaceted landscape of open science participation, emphasizing the critical role of research data sharing and reuse. It is a comprehensive resource for researchers and practitioners interested in further understanding the dynamics and factors shaping the open science ecosystem.

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“…But when researchers put their data into the public domain, there is a chance that others will use them to publish interpretations they might themselves otherwise have published. Consequently, players will typically feel more confidence about obtaining publication credit when they retain data in their own hands [ 32 ].…”

Section: Open Data Access As a Public Goods Gamementioning

confidence: 99%

Motivating data contributions via a distinct career currency

2021

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If collecting research data is perceived as poorly rewarded compared to data synthesis and analysis, this can slow overall research progress via two effects. People who have already collected data may be slow to make it openly accessible. Also, researchers may reallocate effort from collecting fresh data to synthesizing and analysing data already accessible. Here, we advocate for a second career currency in the form of data contributions statements embedded within applications for jobs, promotions and research grants. This workable step forward would provide for peer opinion to operate across thousands of selection and promotion committees and granting panels. In this way, fair valuation of data contributions relative to publications could emerge.

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Open data in the life sciences: the ‘Selfish Scientist Paradox’

Cited by 8 publications

References 36 publications

Considerations for an integrated population health databank in Africa: lessons from global best practices

Considerations for an integrated population health databank in Africa: lessons from global best practices

Factors Influencing Open Science Participation Through Research Data Sharing and Reuse Among Researchers: a Systematic Literature Review

Motivating data contributions via a distinct career currency

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