1
|
Maxwell L, Shreedhar P, Dauga D, McQuilton P, Terry RF, Denisiuk A, Molnar-Gabor F, Saxena A, Sansone SA. FAIR, ethical, and coordinated data sharing for COVID-19 response: a scoping review and cross-sectional survey of COVID-19 data sharing platforms and registries. Lancet Digit Health 2023; 5:e712-e736. [PMID: 37775189 PMCID: PMC10552001 DOI: 10.1016/s2589-7500(23)00129-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 04/27/2023] [Accepted: 07/05/2023] [Indexed: 10/01/2023]
Abstract
Data sharing is central to the rapid translation of research into advances in clinical medicine and public health practice. In the context of COVID-19, there has been a rush to share data marked by an explosion of population-specific and discipline-specific resources for collecting, curating, and disseminating participant-level data. We conducted a scoping review and cross-sectional survey to identify and describe COVID-19-related platforms and registries that harmonise and share participant-level clinical, omics (eg, genomic and metabolomic data), imaging data, and metadata. We assess how these initiatives map to the best practices for the ethical and equitable management of data and the findable, accessible, interoperable, and reusable (FAIR) principles for data resources. We review gaps and redundancies in COVID-19 data-sharing efforts and provide recommendations to build on existing synergies that align with frameworks for effective and equitable data reuse. We identified 44 COVID-19-related registries and 20 platforms from the scoping review. Data-sharing resources were concentrated in high-income countries and siloed by comorbidity, body system, and data type. Resources for harmonising and sharing clinical data were less likely to implement FAIR principles than those sharing omics or imaging data. Our findings are that more data sharing does not equate to better data sharing, and the semantic and technical interoperability of platforms and registries harmonising and sharing COVID-19-related participant-level data needs to improve to facilitate the global collaboration required to address the COVID-19 crisis.
Collapse
Affiliation(s)
- Lauren Maxwell
- Heidelberger Institut für Global Health, Universitätsklinikum Heidelberg, Heidelberg, Germany.
| | - Priya Shreedhar
- Heidelberger Institut für Global Health, Universitätsklinikum Heidelberg, Heidelberg, Germany
| | | | - Peter McQuilton
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Robert F Terry
- TDR, the Special Programme for Research and Training in Tropical Diseases, WHO, Geneva, Switzerland
| | - Alisa Denisiuk
- Faculty of Chemistry, Georg-August-Universität Göttingen, Göttingen, Germany
| | | | | | - Susanna-Assunta Sansone
- Oxford e-Research Centre, Department of Engineering Science, University of Oxford, Oxford, UK
| |
Collapse
|
2
|
Devriendt T, Borry P, Shabani M. Credit and Recognition for Contributions to Data-Sharing Platforms Among Cohort Holders and Platform Developers in Europe: Interview Study. J Med Internet Res 2022; 24:e25983. [PMID: 35023849 PMCID: PMC8796038 DOI: 10.2196/25983] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 03/14/2021] [Accepted: 11/19/2021] [Indexed: 12/22/2022] Open
Abstract
Background The European Commission is funding projects that aim to establish data-sharing platforms. These platforms are envisioned to enhance and facilitate the international sharing of cohort data. Nevertheless, broad data sharing may be restricted by the lack of adequate recognition for those who share data. Objective The aim of this study is to describe in depth the concerns about acquiring credit for data sharing within epidemiological research. Methods A total of 17 participants linked to European Union–funded data-sharing platforms were recruited for a semistructured interview. Transcripts were analyzed using inductive content analysis. Results Interviewees argued that data sharing within international projects could challenge authorship guidelines in multiple ways. Some respondents considered that the acquisition of credit for articles with extensive author lists could be problematic in some instances, such as for junior researchers. In addition, universities may be critical of researchers who share data more often than leading research. Some considered that the evaluation system undervalues data generators and specialists. Respondents generally looked favorably upon alternatives to the current evaluation system to potentially ameliorate these issues. Conclusions The evaluation system might impede data sharing because it mainly focuses on first and last authorship and undervalues the contributor’s work. Further movement of crediting models toward contributorship could potentially address this issue. Appropriate crediting mechanisms that are better aligned with the way science ought to be conducted in the future need to be developed.
Collapse
Affiliation(s)
- Thijs Devriendt
- Department of Public Health and Primary Care, Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - Pascal Borry
- Department of Public Health and Primary Care, Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - Mahsa Shabani
- Metamedica, Faculty of Law and Criminology, UGent, Gent, Belgium
| |
Collapse
|
3
|
Abstract
OBJECTIVES To explore the impact of data-sharing initiatives on the intent to share data, on actual data sharing, on the use of shared data and on research output and impact of shared data. ELIGIBILITY CRITERIA All studies investigating data-sharing practices for individual participant data (IPD) from clinical trials. SOURCES OF EVIDENCE We searched the Medline database, the Cochrane Library, the Science Citation Index Expanded and the Social Sciences Citation Index via Web of Science, and preprints and proceedings of the International Congress on Peer Review and Scientific Publication. In addition, we inspected major clinical trial data-sharing platforms, contacted major journals/publishers, editorial groups and some funders. CHARTING METHODS Two reviewers independently extracted information on methods and results from resources identified using a standardised questionnaire. A map of the extracted data was constructed and accompanied by a narrative summary for each outcome domain. RESULTS 93 studies identified in the literature search (published between 2001 and 2020, median: 2018) and 5 from additional information sources were included in the scoping review. Most studies were descriptive and focused on early phases of the data-sharing process. While the willingness to share IPD from clinical trials is extremely high, actual data-sharing rates are suboptimal. A survey of journal data suggests poor to moderate enforcement of the policies by publishers. Metrics provided by platforms suggest that a large majority of data remains unrequested. When requested, the purpose of the reuse is more often secondary analyses and meta-analyses, rarely re-analyses. Finally, studies focused on the real impact of data-sharing were rare and used surrogates such as citation metrics. CONCLUSIONS There is currently a gap in the evidence base for the impact of IPD sharing, which entails uncertainties in the implementation of current data-sharing policies. High level evidence is needed to assess whether the value of medical research increases with data-sharing practices.
Collapse
Affiliation(s)
- Christian Ohmann
- European Clinical Research Infrastructure Network, Paris, France
| | - David Moher
- Ottawa Methods Centre, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
| | - Maximilian Siebert
- CHU Rennes, CIC 1414 (Centre d'Investigation Clinique de Rennes), University Rennes, Rennes, France
| | - Edith Motschall
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Baden-Württemberg, Germany
| | - Florian Naudet
- CHU Rennes, INSERM CIC 1414 (Centre d'Investigation Clinique de Rennes), University Rennes, Rennes, Bretagne, France
| |
Collapse
|
4
|
Devriendt T, Borry P, Shabani M. Factors that influence data sharing through data sharing platforms: A qualitative study on the views and experiences of cohort holders and platform developers. PLoS One 2021; 16:e0254202. [PMID: 34214146 PMCID: PMC8253381 DOI: 10.1371/journal.pone.0254202] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 06/23/2021] [Indexed: 11/30/2022] Open
Abstract
Background Infrastructures are being developed to enhance and facilitate the sharing of cohort data internationally. However, empirical studies show that many barriers impede sharing data broadly. Purpose Therefore, our aim is to describe the barriers and concerns for the sharing of cohort data, and the implications for data sharing platforms. Methods Seventeen participants involved in developing data sharing platforms or tied to cohorts that are to be submitted to platforms were recruited for semi-structured interviews to share views and experiences regarding data sharing. Results Credit and recognition, the potential misuse of data, loss of control, lack of resources, socio-cultural factors and ethical and legal barriers are elements that influence decisions on data sharing. Core values underlying these reasons are equality, reciprocity, trust, transparency, gratification and beneficence. Conclusions Data generators might use data sharing platforms primarily for collaborative modes of working and network building. Data generators might be unwilling to contribute and share for non-collaborative work, or if no financial resources are provided for sharing data.
Collapse
Affiliation(s)
- Thijs Devriendt
- Faculty of Medicine, Department of Public Health and Primary Care, Centre for Biomedical Ethics and Law, KU Leuven, Leuven, Belgium
- * E-mail:
| | - Pascal Borry
- Faculty of Medicine, Department of Public Health and Primary Care, Centre for Biomedical Ethics and Law, KU Leuven, Leuven, Belgium
| | - Mahsa Shabani
- Faculty of Law and Criminology, Metamedica, Ghent University, Ghent, Belgium
| |
Collapse
|
5
|
Abstract
Background: The lack of incentives has been described as the rate-limiting step for data sharing. Currently, the evaluation of scientific productivity by academic institutions and funders has been heavily reliant upon the number of publications and citations, raising questions about the adequacy of such mechanisms to reward data generation and sharing. This article provides a systematic review of the current and proposed incentive mechanisms for researchers in biomedical sciences and discusses their strengths and weaknesses. Methods: PubMed, Web of Science, and Google Scholar were queried for original research articles, editorials, and opinion articles on incentives for data sharing. Articles were included if they discussed incentive mechanisms for data sharing, were applicable to biomedical sciences, and were written in English. Results: Although coauthorship in return for the sharing of data is common, this might be incompatible with authorship guidelines and raise concerns over the ability of secondary analysts to contest the proposed research methods or conclusions that are drawn. Data publication, citation, and altmetrics have been proposed as alternative routes to credit data generators, which could address these disadvantages. Their primary downsides are that they are not well-established, it is difficult to acquire evidence to support their implementation, and that they could be gamed or give rise to novel forms of research misconduct. Conclusions: Alternative recognition mechanisms need to be more commonly used to generate evidence on their power to stimulate data sharing, and to assess where they fall short. There is ample discussion in policy documents on alternative crediting systems to work toward Open Science, which indicates that that there is an interest in working out more elaborate metascience programs.
Collapse
Affiliation(s)
- Thijs Devriendt
- Department of Public Health and Primary Care, Centre for Biomedical Ethics and Law, KU Leuven, Leuven, Belgium
| | - Mahsa Shabani
- Department of Public Health and Primary Care, Centre for Biomedical Ethics and Law, KU Leuven, Leuven, Belgium.,Metamedica, Faculty of Law and Criminology, Ghent University, Gent, Belgium
| | - Pascal Borry
- Department of Public Health and Primary Care, Centre for Biomedical Ethics and Law, KU Leuven, Leuven, Belgium
| |
Collapse
|
6
|
Rathmes G, Rumisha SF, Lucas TCD, Twohig KA, Python A, Nguyen M, Nandi AK, Keddie SH, Collins EL, Rozier JA, Gibson HS, Chestnutt EG, Battle KE, Humphreys GS, Amratia P, Arambepola R, Bertozzi-Villa A, Hancock P, Millar JJ, Symons TL, Bhatt S, Cameron E, Guerin PJ, Gething PW, Weiss DJ. Global estimation of anti-malarial drug effectiveness for the treatment of uncomplicated Plasmodium falciparum malaria 1991-2019. Malar J 2020; 19:374. [PMID: 33081784 PMCID: PMC7573874 DOI: 10.1186/s12936-020-03446-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 10/10/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Anti-malarial drugs play a critical role in reducing malaria morbidity and mortality, but their role is mediated by their effectiveness. Effectiveness is defined as the probability that an anti-malarial drug will successfully treat an individual infected with malaria parasites under routine health care delivery system. Anti-malarial drug effectiveness (AmE) is influenced by drug resistance, drug quality, health system quality, and patient adherence to drug use; its influence on malaria burden varies through space and time. METHODS This study uses data from 232 efficacy trials comprised of 86,776 infected individuals to estimate the artemisinin-based and non-artemisinin-based AmE for treating falciparum malaria between 1991 and 2019. Bayesian spatiotemporal models were fitted and used to predict effectiveness at the pixel-level (5 km × 5 km). The median and interquartile ranges (IQR) of AmE are presented for all malaria-endemic countries. RESULTS The global effectiveness of artemisinin-based drugs was 67.4% (IQR: 33.3-75.8), 70.1% (43.6-76.0) and 71.8% (46.9-76.4) for the 1991-2000, 2006-2010, and 2016-2019 periods, respectively. Countries in central Africa, a few in South America, and in the Asian region faced the challenge of lower effectiveness of artemisinin-based anti-malarials. However, improvements were seen after 2016, leaving only a few hotspots in Southeast Asia where resistance to artemisinin and partner drugs is currently problematic and in the central Africa where socio-demographic challenges limit effectiveness. The use of artemisinin-based combination therapy (ACT) with a competent partner drug and having multiple ACT as first-line treatment choice sustained high levels of effectiveness. High levels of access to healthcare, human resource capacity, education, and proximity to cities were associated with increased effectiveness. Effectiveness of non-artemisinin-based drugs was much lower than that of artemisinin-based with no improvement over time: 52.3% (17.9-74.9) for 1991-2000 and 55.5% (27.1-73.4) for 2011-2015. Overall, AmE for artemisinin-based and non-artemisinin-based drugs were, respectively, 29.6 and 36% below clinical efficacy as measured in anti-malarial drug trials. CONCLUSIONS This study provides evidence that health system performance, drug quality and patient adherence influence the effectiveness of anti-malarials used in treating uncomplicated falciparum malaria. These results provide guidance to countries' treatment practises and are critical inputs for malaria prevalence and incidence models used to estimate national level malaria burden.
Collapse
Affiliation(s)
- Giulia Rathmes
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Susan F Rumisha
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Telethon Kids Institute, Perth, Australia.
| | - Tim C D Lucas
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Katherine A Twohig
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Andre Python
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Center for Data Science, Zhejiang University, Hangzhou, 310058, China
| | - Michele Nguyen
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Anita K Nandi
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Suzanne H Keddie
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Emma L Collins
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jennifer A Rozier
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Harry S Gibson
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Elisabeth G Chestnutt
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Katherine E Battle
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Georgina S Humphreys
- WorldWide Anti-Malarial Resistance Network (WWARN), Oxford, UK
- Infectious Diseases Data Observatory (IDDO), Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Punam Amratia
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Rohan Arambepola
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Amelia Bertozzi-Villa
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Institute for Disease Modeling, Bellevue, WA, USA
| | - Penelope Hancock
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Justin J Millar
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Tasmin L Symons
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - Ewan Cameron
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Telethon Kids Institute, Perth, Australia
- Curtin University, Perth, Australia
| | - Philippe J Guerin
- WorldWide Anti-Malarial Resistance Network (WWARN), Oxford, UK
- Infectious Diseases Data Observatory (IDDO), Oxford, UK
- Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Peter W Gething
- Telethon Kids Institute, Perth, Australia
- Curtin University, Perth, Australia
| | - Daniel J Weiss
- Malaria Atlas Project, Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Telethon Kids Institute, Perth, Australia
- Curtin University, Perth, Australia
| |
Collapse
|
7
|
Ashley EA, Shetty N, Patel J, van Doorn R, Limmathurotsakul D, Feasey NA, Okeke IN, Peacock SJ. Harnessing alternative sources of antimicrobial resistance data to support surveillance in low-resource settings. J Antimicrob Chemother 2020; 74:541-546. [PMID: 30544186 PMCID: PMC6406030 DOI: 10.1093/jac/dky487] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
One of the most pressing challenges facing the global surveillance of antimicrobial resistance (AMR) is the generation, sharing, systematic analysis and dissemination of data in low-resource settings. Numerous agencies and initiatives are working to support the development of globally distributed microbiology capacity, but the routine generation of a sustainable flow of reliable data will take time to establish before it can deliver a clinical and public health impact. By contrast, there are a large number of pharma- and academia-led initiatives that have generated a wealth of data on AMR and drug-resistant infections in low-resource settings, together with high-volume data generation by private laboratories. Here, we explore how untapped sources of data could provide a short-term solution that bridges the gap between now and the time when routine surveillance capacity will have been established and how this could continue to support surveillance efforts in the future. We discuss the benefits and limitations of data generated by these sources, the mechanisms and barriers to making this accessible and how academia and pharma might support the development of laboratory and analytical capacity. We provide key actions that will be required to harness these data, including: a mapping exercise; creating mechanisms for data sharing; use of data to support national action plans; facilitating access to and use of data by the WHO Global Antimicrobial Resistance Surveillance System; and innovation in data capture, analysis and sharing.
Collapse
Affiliation(s)
- Elizabeth A Ashley
- Myanmar-Oxford Clinical Research Unit (MOCRU), Yangon, Myanmar.,Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - Nandini Shetty
- National Infection Service, Public Health England, 61 Colindale Avenue, Colindale, London, UK
| | - Jean Patel
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Rogier van Doorn
- Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ha Noi, Vietnam
| | - Direk Limmathurotsakul
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Nicholas A Feasey
- The Liverpool School of Tropical Medicine, Liverpool, UK.,Malawi Liverpool Wellcome Trust Clinical Research Programme, Blantyre, Malawi
| | - Iruka N Okeke
- Department of Pharmaceutical Microbiology, Faculty of Pharmacy, University of Ibadan, Ibadan, Nigeria
| | | |
Collapse
|
8
|
Prosser C, Meyer W, Ellis J, Lee R. Evolutionary ARMS Race: Antimalarial Resistance Molecular Surveillance. Trends Parasitol 2018; 34:322-334. [PMID: 29396203 DOI: 10.1016/j.pt.2018.01.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 01/02/2018] [Accepted: 01/03/2018] [Indexed: 01/13/2023]
Abstract
Molecular surveillance of antimalarial drug resistance markers has become an important part of resistance detection and containment. In the current climate of multidrug resistance, including resistance to the global front-line drug artemisinin, there is a consensus to upscale molecular surveillance. The most salient limitation to current surveillance efforts is that skill and infrastructure requirements preclude many regions. This includes sub-Saharan Africa, where Plasmodium falciparum is responsible for most of the global malaria disease burden. New molecular and data technologies have emerged with an emphasis on accessibility. These may allow surveillance to be conducted in broad settings where it is most needed, including at the primary healthcare level in endemic countries, and extending to the village health worker.
Collapse
Affiliation(s)
- Christiane Prosser
- Molecular Mycology Research Laboratory, Centre for Infectious Diseases and Microbiology, Westmead Clinical School-Sydney Medical School, Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Sydney, NSW, Australia; Westmead Institute for Medical Research, Westmead, NSW, Australia.
| | - Wieland Meyer
- Molecular Mycology Research Laboratory, Centre for Infectious Diseases and Microbiology, Westmead Clinical School-Sydney Medical School, Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Sydney, NSW, Australia; Westmead Institute for Medical Research, Westmead, NSW, Australia
| | - John Ellis
- School of Life Sciences, University of Technology Sydney, NSW, Australia
| | - Rogan Lee
- Centre for Infectious Diseases and Microbiology Laboratory Services, Institute of Clinical Pathology & Medical Research, Westmead Hospital, Westmead, NSW, Australia
| |
Collapse
|
9
|
Pisani E, Botchway S. Sharing individual patient and parasite-level data through the WorldWide Antimalarial Resistance Network platform: A qualitative case study. Wellcome Open Res 2017; 2:63. [PMID: 29018840 PMCID: PMC5627501 DOI: 10.12688/wellcomeopenres.12259.1] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/10/2017] [Indexed: 11/20/2022] Open
Abstract
Background: Increasingly, biomedical researchers are encouraged or required by research funders and journals to share their data, but there's very little guidance on how to do that equitably and usefully, especially in resource-constrained settings. We performed an in-depth case study of one data sharing pioneer: the WorldWide Antimalarial Resistance Network (WWARN). Methods: The case study included a records review, a quantitative analysis of WAARN-related publications, in-depth interviews with 47 people familiar with WWARN, and a witness seminar involving a sub-set of 11 interviewees. Results: WWARN originally aimed to collate clinical, in vitro, pharmacological and molecular data into linked, open-access databases intended to serve as a public resource to guide antimalarial drug treatment policies. Our study describes how WWARN navigated challenging institutional and academic incentive structures, alongside funders' reluctance to invest in capacity building in malaria-endemic countries, which impeded data sharing. The network increased data contributions by focusing on providing free, online tools to improve the quality and efficiency of data collection, and by inviting collaborative authorship on papers addressing policy-relevant questions that could only be answered through pooled analyses. By July 1, 2016, the database included standardised data from 103 molecular studies and 186 clinical trials, representing 135,000 individual patients. Developing the database took longer and cost more than anticipated, and efforts to increase equity for data contributors are on-going. However, analyses of the pooled data have generated new methods and influenced malaria treatment recommendations globally. Despite not achieving the initial goal of real-time surveillance, WWARN has developed strong data governance and curation tools, which are now being adapted relatively quickly for other diseases. Conclusions: To be useful, data sharing requires investment in long-term infrastructure. To be feasible, it requires new incentive structures that favour the generation of reusable knowledge.
Collapse
Affiliation(s)
- Elizabeth Pisani
- Visiting Senior Research Fellow, The Policy Institute, King's College London, London, UK
| | | |
Collapse
|
10
|
Tennant JP, Dugan JM, Graziotin D, Jacques DC, Waldner F, Mietchen D, Elkhatib Y, B. Collister L, Pikas CK, Crick T, Masuzzo P, Caravaggi A, Berg DR, Niemeyer KE, Ross-Hellauer T, Mannheimer S, Rigling L, Katz DS, Greshake Tzovaras B, Pacheco-Mendoza J, Fatima N, Poblet M, Isaakidis M, Irawan DE, Renaut S, Madan CR, Matthias L, Nørgaard Kjær J, O'Donnell DP, Neylon C, Kearns S, Selvaraju M, Colomb J. A multi-disciplinary perspective on emergent and future innovations in peer review. F1000Res 2017; 6:1151. [PMID: 29188015 PMCID: PMC5686505 DOI: 10.12688/f1000research.12037.3] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/24/2017] [Indexed: 11/20/2022] Open
Abstract
Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
Collapse
Affiliation(s)
| | - Jonathan M. Dugan
- Berkeley Institute for Data Science, University of California, Berkeley, CA, USA
| | - Daniel Graziotin
- Institute of Software Technology, University of Stuttgart, Stuttgart, Germany
| | - Damien C. Jacques
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - François Waldner
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, VA, USA
| | - Yehia Elkhatib
- School of Computing and Communications, Lancaster University, Lancaster, UK
| | | | | | - Tom Crick
- Cardiff Metropolitan University, Cardiff, UK
| | - Paola Masuzzo
- Department of Biochemistry, Ghent University, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
| | - Anthony Caravaggi
- School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland
| | - Devin R. Berg
- Engineering & Technology Department, University of Wisconsin-Stout, Menomonie, WI, USA
| | - Kyle E. Niemeyer
- School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, USA
| | - Tony Ross-Hellauer
- State and University Library, University of Göttingen, Göttingen, Germany
| | | | | | - Daniel S. Katz
- School of Information Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | - Nazeefa Fatima
- Department of Biology, Faculty of Science, Lund University, Lund, Sweden
| | - Marta Poblet
- Graduate School of Business and Law, RMIT University, Melbourne, Australia
| | - Marios Isaakidis
- Department of Computer Science, University College London, London, UK
| | - Dasapta Erwin Irawan
- Department of Groundwater Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, Indonesia
| | - Sébastien Renaut
- Département de Sciences Biologiques, Institut de Recherche en Biologie Végétale, Université de Montréal, Montreal, QC, Canada
| | | | - Lisa Matthias
- OpenAIRE, University of Göttingen, Göttingen, Germany
| | - Jesper Nørgaard Kjær
- Department of Affective Disorders, Psychiatric Research Academy, Aarhus University Hospital, Risskov, Denmark
| | - Daniel Paul O'Donnell
- Department of English and Centre for the Study of Scholarly Communications, University of Lethbridge, Lethbridge, AB, Canada
| | - Cameron Neylon
- Centre for Culture and Technology, Curtin University, Perth, Australia
| | - Sarah Kearns
- Department of Chemical Biology, University of Michigan, Ann Arbor, MI, USA
| | - Manojkumar Selvaraju
- Integrated Gulf Biosystems, Riyadh, Saudi Arabia
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
| | | |
Collapse
|
11
|
Tennant JP, Dugan JM, Graziotin D, Jacques DC, Waldner F, Mietchen D, Elkhatib Y, B. Collister L, Pikas CK, Crick T, Masuzzo P, Caravaggi A, Berg DR, Niemeyer KE, Ross-Hellauer T, Mannheimer S, Rigling L, Katz DS, Greshake Tzovaras B, Pacheco-Mendoza J, Fatima N, Poblet M, Isaakidis M, Irawan DE, Renaut S, Madan CR, Matthias L, Nørgaard Kjær J, O'Donnell DP, Neylon C, Kearns S, Selvaraju M, Colomb J. A multi-disciplinary perspective on emergent and future innovations in peer review. F1000Res 2017; 6:1151. [PMID: 29188015 PMCID: PMC5686505 DOI: 10.12688/f1000research.12037.1] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/13/2017] [Indexed: 11/20/2022] Open
Abstract
Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of Web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform current models while avoiding as many of the biases of existing systems as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that, at least partially, resolves many of the technical and social issues associated with peer review, and can potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
Collapse
Affiliation(s)
| | - Jonathan M. Dugan
- Berkeley Institute for Data Science, University of California, Berkeley, CA, USA
| | - Daniel Graziotin
- Institute of Software Technology, University of Stuttgart, Stuttgart, Germany
| | - Damien C. Jacques
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - François Waldner
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, VA, USA
| | - Yehia Elkhatib
- School of Computing and Communications, Lancaster University, Lancaster, UK
| | | | | | - Tom Crick
- Cardiff Metropolitan University, Cardiff, UK
| | - Paola Masuzzo
- Department of Biochemistry, Ghent University, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
| | - Anthony Caravaggi
- School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland
| | - Devin R. Berg
- Engineering & Technology Department, University of Wisconsin-Stout, Menomonie, WI, USA
| | - Kyle E. Niemeyer
- School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, USA
| | - Tony Ross-Hellauer
- State and University Library, University of Göttingen, Göttingen, Germany
| | | | | | - Daniel S. Katz
- School of Information Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | - Nazeefa Fatima
- Department of Biology, Faculty of Science, Lund University, Lund, Sweden
| | - Marta Poblet
- Graduate School of Business and Law, RMIT University, Melbourne, Australia
| | - Marios Isaakidis
- Department of Computer Science, University College London, London, UK
| | - Dasapta Erwin Irawan
- Department of Groundwater Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, Indonesia
| | - Sébastien Renaut
- Département de Sciences Biologiques, Institut de Recherche en Biologie Végétale, Université de Montréal, Montreal, QC, Canada
| | | | - Lisa Matthias
- OpenAIRE, University of Göttingen, Göttingen, Germany
| | - Jesper Nørgaard Kjær
- Department of Affective Disorders, Psychiatric Research Academy, Aarhus University Hospital, Risskov, Denmark
| | - Daniel Paul O'Donnell
- Department of English and Centre for the Study of Scholarly Communications, University of Lethbridge, Lethbridge, AB, Canada
| | - Cameron Neylon
- Centre for Culture and Technology, Curtin University, Perth, Australia
| | - Sarah Kearns
- Department of Chemical Biology, University of Michigan, Ann Arbor, MI, USA
| | - Manojkumar Selvaraju
- Integrated Gulf Biosystems, Riyadh, Saudi Arabia
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
| | | |
Collapse
|
12
|
Tennant JP, Dugan JM, Graziotin D, Jacques DC, Waldner F, Mietchen D, Elkhatib Y, B. Collister L, Pikas CK, Crick T, Masuzzo P, Caravaggi A, Berg DR, Niemeyer KE, Ross-Hellauer T, Mannheimer S, Rigling L, Katz DS, Greshake Tzovaras B, Pacheco-Mendoza J, Fatima N, Poblet M, Isaakidis M, Irawan DE, Renaut S, Madan CR, Matthias L, Nørgaard Kjær J, O'Donnell DP, Neylon C, Kearns S, Selvaraju M, Colomb J. A multi-disciplinary perspective on emergent and future innovations in peer review. F1000Res 2017; 6:1151. [PMID: 29188015 PMCID: PMC5686505 DOI: 10.12688/f1000research.12037.2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/14/2017] [Indexed: 12/22/2022] Open
Abstract
Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.
Collapse
Affiliation(s)
| | - Jonathan M. Dugan
- Berkeley Institute for Data Science, University of California, Berkeley, CA, USA
| | - Daniel Graziotin
- Institute of Software Technology, University of Stuttgart, Stuttgart, Germany
| | - Damien C. Jacques
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - François Waldner
- Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Daniel Mietchen
- Data Science Institute, University of Virginia, Charlottesville, VA, USA
| | - Yehia Elkhatib
- School of Computing and Communications, Lancaster University, Lancaster, UK
| | | | | | - Tom Crick
- Cardiff Metropolitan University, Cardiff, UK
| | - Paola Masuzzo
- Department of Biochemistry, Ghent University, Ghent, Belgium
- VIB-UGent Center for Medical Biotechnology, Ghent, Belgium
| | - Anthony Caravaggi
- School of Biological, Earth and Environmental Sciences, University College Cork, Cork, Ireland
| | - Devin R. Berg
- Engineering & Technology Department, University of Wisconsin-Stout, Menomonie, WI, USA
| | - Kyle E. Niemeyer
- School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, Corvallis, OR, USA
| | - Tony Ross-Hellauer
- State and University Library, University of Göttingen, Göttingen, Germany
| | | | | | - Daniel S. Katz
- School of Information Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | | | - Nazeefa Fatima
- Department of Biology, Faculty of Science, Lund University, Lund, Sweden
| | - Marta Poblet
- Graduate School of Business and Law, RMIT University, Melbourne, Australia
| | - Marios Isaakidis
- Department of Computer Science, University College London, London, UK
| | - Dasapta Erwin Irawan
- Department of Groundwater Engineering, Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, Indonesia
| | - Sébastien Renaut
- Département de Sciences Biologiques, Institut de Recherche en Biologie Végétale, Université de Montréal, Montreal, QC, Canada
| | | | - Lisa Matthias
- OpenAIRE, University of Göttingen, Göttingen, Germany
| | - Jesper Nørgaard Kjær
- Department of Affective Disorders, Psychiatric Research Academy, Aarhus University Hospital, Risskov, Denmark
| | - Daniel Paul O'Donnell
- Department of English and Centre for the Study of Scholarly Communications, University of Lethbridge, Lethbridge, AB, Canada
| | - Cameron Neylon
- Centre for Culture and Technology, Curtin University, Perth, Australia
| | - Sarah Kearns
- Department of Chemical Biology, University of Michigan, Ann Arbor, MI, USA
| | - Manojkumar Selvaraju
- Integrated Gulf Biosystems, Riyadh, Saudi Arabia
- Saudi Human Genome Program, King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia
| | | |
Collapse
|