A wealth of scholarly research and real-world case studies demonstrate the myriad ways in which open access and open data benefit researchers and society alike. A representative sample is found below. If you have a suggestion for this list, please contact us.
PROFILES IN OPEN
How do researchers who have made their work openly available as a condition of their grant funding feel about their experiences? What advice would they give to their peers, and to philanthropic organizations considering the adoption of open policies? “Profiles in Open” present real world stories of open in action, as told by the researchers themselves.
Dorothy Bishop is a Professor of Development Neuropsychology at the University of Oxford, as well as a Wellcome Trust Principal Research Fellow. Her research is concerned with trying to understand the nature and causes of language impairments in children. Dr. Bishop and her colleagues make the entirety of their research cycle - from design to data to analysis - open in order to accelerate understanding of the best conditions for teaching language skills. Read her story here.
Michael Gottlieb served as the principal investigator for the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health and Development (MAL-ED) study. MAL-ED explored how the interaction among a variety of factors – including environment, nutrition, public health, and local medical issues – influenced physical and cognitive childhood developments around the world. Because of the gravity of the issues under examination, the MAL-ED team felt an urgency to share these data quickly and widely with qualified researchers around the world. Read his story here.
Rogier Kievit is a Sir Henry Wellcome fellow at the UK Medical Research Council's Cognition and Brain Sciences Unit. He is especially interested in periods of rapid change such as childhood and old age, as well as the neural mechanisms underlying these changes. He and his colleagues have made a range of research outputs openly available, including code, data, articles, and preprints. Open science has been beneficial to both Dr. Kievit and the field in which he works. Read his story here.
Karin Lapping is the Program Director of Alive & Thrive, a global nutrition initiative. In this capacity, she oversees a diverse array of research projects touching on areas such as social behavior change; policy advocacy; and the delivery of quality maternal, infant, and young child nutrition (MIYCN) services. Dr. Lapping brings a unique perspective to open science, that of a project coordinator working with multidisciplinary research teams. Read her story here.
David Ludwig, a professor at Harvard Medical School and Harvard School of Public Health, studies how the type of calories you consume may influence your likelihood of losing weight and keeping it off for the long term. The project has real-world ramifications for public health planning, treatment of obesity, and health care systems. Dr. Ludwig and his colleagues chose to make the underlying data behind their work openly available for others to test, replicate, challenge, and build upon. Read his story here.
Russ Poldrack is a professor of Psychology at Stanford University, member of the Stanford Neuroscience Institute and director of the Stanford Center for Reproducible Neuroscience. His work focuses on cognitive neuroscience, or, in lay terms, how the brain gives rise to the mind. Dr. Poldrack and his colleagues have not only shared their data openly -- they also developed open infrastructure to support its analysis and ongoing availability. He believes the open sharing of research outputs us critical to maximizing the potential benefits of research subjects' contributions. Read his story here.
David Yokum is an adjunct associate professor at Brown University, where he is establishing and directing a new center that will support applied public policy research with state and local governments. His research aims to embed the scientific method into the heart of day-to-day governance, so as to produce timely, relevant, and high-quality evidence for decisionmakers that, in turn, will improve communities. Dr. Yokum and his colleagues made their police body camera research plan available in the pre-analysis phase, part of a commitment to research transparency across the life cycle of the project. Read his story here.
Bertagnolli, Monica M., et al. "Advantages of a Truly Open-access Data-sharing Model." The New England Journal of Medicine 376.12 (2017): 1178-1181. This article argues that a key way to honor and reward the altruism of patients who participate in clinical trials is to share the data gathered in these trials with other researchers in a responsible and meaningful way.
Jain, Anubhav, Kristin A. Persson, and Gerbrand Ceder. "Research Update: The materials genome initiative: Data sharing and the impact of collaborative ab initio databases." APL Materials 4.5 (2016): 053102. This article examines data sharing in materials science. It observes that data sharing can drastically shorten the materials research cycle by reducing the burden of data collection for individual research groups, and by enabling more efficient development of scientific hypotheses and property prediction models. This, in turn, has the practical benefit of speeding the discovery and optimization of new materials.
Piwowar H, Priem J, Larivière V, Alperin JP, Matthias L, Norlander B, Farley A, West J, Haustein S. 2018. “The state of OA: a large-scale analysis of the prevalence and impact of Open Access articles.” PeerJ 6:e4375. This peer-reviewed article analyzes the citations of more than 300,000 articles. Its findings corroborate the “open-access citation advantage”, with OA articles found to receive 18% more citations than average.
Science, Digital; Hahnel, Mark; Fane, Briony; Treadway, Jon; Baynes, Grace; Wilkinson, Ross; et al. (2018): “The State of Open Data Report 2018.” This report from the Digital Science/figshare team contains a number of interesting findings about researcher attitudes and behaviors with respect to data sharing. Notably, it asserts that 64% of respondents made some of their data openly available in 2018.
Tennant JP, Waldner F, Jacques DC et al. “The academic, economic and societal impacts of Open Access: an evidence-based review [version 3; referees: 3 approved, 2 approved with reservations].” F1000Research 2016, 5:632. This review analyzes the scholarly literature on the impact of open access. It concludes that the overall evidence points to a favorable impact of open access on the scholarly literature through increased dissemination and reuse. It also finds that current levels of access in the developing world are insufficient and unstable, and only open access has the potential to foster the development of stable research ecosystems.
Yang S, Cline M, Zhang C, Paten B, Lincoln S.E. “Data Sharing and Reproducible Clinical Genetic Testing: Successes and Challenges. Pacific Symposium on Biocomputing Pacific Symposium on Biocomputing.” Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 22, 166–176. This conference proceeding examines the open sharing of clinical genetic data. It concludes that participation in the NIH ClinVar initiative has improved research reproducibility. This, in turn, positively impacts direct patient care in oncology, cardiology, neurology, pediatrics, obstetrics, and other clinical specialties.
Data Sharing and the Genetic Underpinnings of Alzheimer’s. Open data sharing among a range of research organizations facilitated the analysis of genetic details from almost 100,000 anonymized contributors. Giving multiple labs access to such a rich well of data allowed researchers to identify five new risk genes for Alzheimer's disease, and confirmed 20 known others.
The Value of Open Data Sharing. This report by the Group on Earth Observations (GEO) explores the economic, societal, educational, public policy, and research benefits of openly shared earth science data. It makes the case that researchers have much to gain by making their data available freely and openly, with wide reuse rights.
Open Data: Enabling Fact-Based, Data-Driven Decisions. The Global Open Data for Agriculture and Nutrition (GODAN) initiative is a collaboration between the United States Department of Agriculture and more than 700 partners across the public and private sectors. GODAN promotes the proactive sharing of open data to make information about agriculture and nutrition available, accessible, and usable worldwide. In doing so, GODAN has helped farmers around the world make evidence-based decisions related to agriculture and nutrition.
Online Epidemic Tracking Tool Embraces Open Data and Collective Intelligence. Researchers from the Wellcome Trust Sanger Institute and Imperial College London developed Microreact, a free, real-time epidemic visualisation and tracking platform used to monitor outbreaks of Ebola, Zika and antibiotic-resistant microbes. The Microreact team collaborated with the Microbiology Society to openly share data and metadata sets, which can then be visualised and explored dynamically by any researcher around the world. This collaboration is explicitly designed to democratise genomic data and resulting insights about disease outbreaks.
From Ideas to Industries: Human Genome Project. With openness as a core tenet, the Human Genome Project generated $965 billion in economic output between 1988 and 2012, creating more than $293 billion in personal income through wages and benefits, and nearly four million jobs.
Battling Disease with Open: Open Source Malaria Consortium. The Open Source Malaria Consortium invites scientists from around the around to freely share their research on anti-malaria drugs through a transparent, online platform. The hope is to accelerate discovery of new drug candidates to be entered into pre-clinical development. The Consortium has attracted more than a hundred contributors who post their drug discovery and development findings, discuss their work, and build on each other’s ideas for potential cures. The project serves as a repository of projects so researchers can see what molecules have and have not proven promising. All information is machine discoverable so others can locate the work and reuse the data.
Using Open Data to Predict Adverse Treatment Effects. As part of the NCBI "Dream Challenge" program, a group of scientists developed a crowdsourced, open data model with which to predict early discontinuation of docetaxel, a metastatic prostate cancer treatment. A total of 34 international teams analyzed open data from clinical trials in order to formulate a hypothesis regarding which patients were most likely to stop docetaxel treatment due to adverse side effects. Seven of the 34 teams identified a common set of predictive factors. An additional positive outcome was a decision by these seven teams to further collaborate to refine their models.
Sluggish Data Sharing Hampers Reproducibility Effort. The Reproducibility Project: Cancer Biology is examining the replicability of 50 high-impact cancer biology studies, published between 2010 and 2012. The project coordinators have found that free, unfettered access to the experimental data has been a major hurdle to overcome. Without this access, understanding whether promising research in cancer biology can reproduced and verified is a significant challenge. This may slow follow-on research, or, in a more dire outcome, lead scientists to pursue experiments that are, in fact, a dead-end.
How Open Data Can Help the World Better Manage Coral Reefs. Scientific divers from the US National Oceanic and Atmospheric Administration (NOAA) spent seven years collecting physical, chemical, and biological data on fish and coral reefs in the west central Pacific. By sharing these datasets openly, the researchers enabled valuable meta-analysis and follow-on research. Among the tangible results - development of fishing benchmarks and an assessment mechanism for reef management efforts.