Defining Success in Open Science [version 2; peer review:2 approved].
Sarah E Ali-KhanAntoine JeanEmily MacDonaldE Richard GoldPublished in: MNI open research (2018)
Mounting evidence indicates that worldwide, innovation systems are increasing unsustainable. Equally, concerns about inequities in the science and innovation process, and in access to its benefits, continue. Against a backdrop of growing health, economic and scientific challenges global stakeholders are urgently seeking to spur innovation and maximize the just distribution of benefits for all. Open Science collaboration (OS) - comprising a variety of approaches to increase open, public, and rapid mobilization of scientific knowledge - is seen to be one of the most promising ways forward. Yet, many decision-makers hesitate to construct policy to support the adoption and implementation of OS without access to substantive, clear and reliable evidence. In October 2017, international thought-leaders gathered at an Open Science Leadership Forum in the Washington DC offices of the Bill and Melinda Gates Foundation to share their views on what successful Open Science looks like. Delegates from developed and developing nations, national governments, science agencies and funding bodies, philanthropy, researchers, patient organizations and the biotechnology, pharma and artificial intelligence (AI) industries discussed the outcomes that would rally them to invest in OS, as well as wider issues of policy and implementation. This first of two reports, summarizes delegates' views on what they believe OS will deliver in terms of research, innovation and social impact in the life sciences. Through open and collaborative process over the next months, we will translate these success outcomes into a toolkit of quantitative and qualitative indicators to assess when, where and how open science collaborations best advance research, innovation and social benefit. Ultimately, this work aims to develop and openly share tools to allow stakeholders to evaluate and re-invent their innovation ecosystems, to maximize value for the global public and patients, and address long-standing questions about the mechanics of innovation.
Keyphrases
- public health
- healthcare
- minimally invasive
- artificial intelligence
- mental health
- quality improvement
- primary care
- machine learning
- big data
- end stage renal disease
- risk assessment
- newly diagnosed
- systematic review
- ejection fraction
- high resolution
- chronic kidney disease
- mass spectrometry
- climate change
- case report
- insulin resistance
- metabolic syndrome
- adverse drug
- patient reported
- human health
- adipose tissue