Ten simple rules for open human health research

Bafeta, Aïda; Bobe, Jason; Clucas, Jon; Gonsalves, Pattie P; Gruson-Daniel, Célya; Hudson, Kathy; Klein, Arno; Krishnakumar, Anirudh; McCollister-Slipp, Anna; Lindner, Ariel B.; Misevic, Dusan; Naslund, John A.; Nebeker, Camille; Nikolaidis, Aki; Pasquetto, Irene V.; Sanchez, Gabriela; Schapira, Matthieu; Scheininger, Tohar; Schoeller, Félix; Heinsfeld, Anibal Sólon; Taddéi, François

doi:10.1371/journal.pcbi.1007846

Cited by 3 publications

(3 citation statements)

References 72 publications

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“…Scientific communication, not only between researchers but also between institutions, should be promoted. Recently, requirements for researchers to make data public or open source have grown popular among journals and major funding agencies in the US, Europe, and globally; this is an important catalyst for open science and addressing issues such as reproducibility [ 72 ].…”

Section: Approaches To Improving Reproducibility and Scientific Integ...mentioning

confidence: 99%

Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action

Gutierrez

Lindegger

Heravi

et al. 2023

IJERPH

Self Cite

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The emergence of big data science presents a unique opportunity to improve public-health research practices. Because working with big data is inherently complex, big data research must be clear and transparent to avoid reproducibility issues and positively impact population health. Timely implementation of solution-focused approaches is critical as new data sources and methods take root in public-health research, including urban public health and digital epidemiology. This commentary highlights methodological and analytic approaches that can reduce research waste and improve the reproducibility and replicability of big data research in public health. The recommendations described in this commentary, including a focus on practices, publication norms, and education, are neither exhaustive nor unique to big data, but, nonetheless, implementing them can broadly improve public-health research. Clearly defined and openly shared guidelines will not only improve the quality of current research practices but also initiate change at multiple levels: the individual level, the institutional level, and the international level.

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Section: Approaches To Improving Reproducibility and Scientific Integ...mentioning

confidence: 99%

Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action

Gutierrez

Lindegger

Heravi

et al. 2023

IJERPH

Self Cite

View full text Add to dashboard Cite

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“…The workshop discussion and co-creation approach was co-designed with the co-organizers and based on experiences from previous workshops that organized by the Learning Planet Institute since 2017, which also resulted in position and opinion papers (Bafeta et al, 2020;Kusters et al, 2020).…”

Section: Workhop Format and Dynamicsmentioning

confidence: 99%

Harnessing collective intelligence for the future of learning – a co-constructed research and development agenda

Misevic

Atal²,

Bédard³

et al. 2023

HCj

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Learning, defined as the process of constructing meaning and developing competencies to act on it, is instrumental in helping individuals, communities, and organizations tackle challenges. When these challenges increase in complexity and require domain knowledge from diverse areas of expertise, it becomes difficult for single individuals to address them. In this context, collective intelligence, a capacity of groups of people to act together and solve problems using their collective knowledge, becomes of great importance. Technologies are instrumental both to support and understand learning and collective intelligence, hence the need for innovations in the area of technologies that can support user needs to learn and tackle collective challenges. Use-inspired research is a fitting paradigm that spans applied solutions and scientific explanations of the processes of learning and collective intelligence, and that can improve the technologies that may support them. Although some conceptual and theoretical work explaining and linking learning with collective intelligence is emerging, technological infrastructures as well as methodologies that employ and evidence that support them are nascent. We convened a group of experts to create a middleground and engage with the priorities for use-inspired research. Here we detail directions and methods they put forward as most promising for advancing a scientific agenda around learning and collective intelligence.

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“…Researchers within domains such as astronomy that have extensive knowledge infrastructures, similar research methods based on common data standards and formats, common documentation practices, and large collaborations are able to reuse each other's datasets readily (Borgman & Wofford, 2021). Conversely, researchers from different domains collaborating on a common problem in biomedicine took the better part of a decade to find methods of sharing data effectively (Bafeta et al, 2020;Pasquetto, 2018). Those who wish to reuse data from other domains, for purposes other than those for which the data were created, and at much earlier points in time, first should recognize the number of rivers they will need to cross.…”

Section: Discussionmentioning

confidence: 99%

What data release means, and why it matters: an interview with Prof. Christine Borgman

Borgman¹,

Plantin²

Ouvrir, Partager, Réutiliser

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Stanford University is going through the difficult and highly fraught process of figuring out a plan for the library of the future. Coming on the heels of the "bookless library," touted as the vision for a new engineering library, a preliminary proposal in 2007 to tear down the seismically unsafe Meyer Library and digitize and house off campus most of its 600,000 volumes produced a cry of protest. The utopian ideal, imposed from above, might have met with less resistance had faculty members been involved in the planning from the start. But as charged responses mounted, the administration announced it would delay razing the library. Last fall a faculty committee of the Academic Council proposed its own plan for rethinking the library to the Faculty Senate, which has accepted it with a call for further rethinking by various university groups of how to put the plan into effect.The new faculty plan is characterized by a key shift in emphasis that is both less charged and more pointed. Rather than envision a "library of the future," it discusses the "future of the library," stressing continuity with an old entity rather than the creation of something brand-new. The distinction exposes what is at stake.

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Ten simple rules for open human health research

Cited by 3 publications

References 72 publications

Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action

Reproducibility and Scientific Integrity of Big Data Research in Urban Public Health and Digital Epidemiology: A Call to Action

Harnessing collective intelligence for the future of learning – a co-constructed research and development agenda

What data release means, and why it matters: an interview with Prof. Christine Borgman

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