OCSDNet members believe that Open Science entails the collaboration and participation of diverse actors in a wide variety of institutional contexts, with widely different motivations, values and intentions. As such, we see Open Science as a conditional process operating within a highly complex socio-technical system. Understanding the principles and dynamics of collaboration and participation is central to OCSDNet’s activities. The network adopted “Open and Collaborative Science” (OCS) as an operating term to remind us of the centrality of ‘collaboration’ within the workings of the network.
Open Science moves beyond open access research articles, towards encompassing other research objects such as data, software codes, protocols and workflows. The intention is for people to use, re-use and distribute content without legal, technological or social restrictions. In some cases, Open Science also entails the opening up of the entire research process from agenda-setting to the dissemination of findings.
Open Science utilizes the prevalence of the Internet and associated digital tools to enable greater local and global research collaboration. Such collaboration need not be limited to traditional research communities, but could also include the participation of citizen scientists, both in partnership with traditional research institutions as well as those in non-traditional research locations, often using open software, hardware and other open technologies.
Given the diverse nature of Open Science actors, intentions and mechanisms for use, there is the potential that it may yield negative outcomes for some actors, perhaps exacerbating problems of inequitable participation, gender disparity and further excluding researchers who do not have the capacity to take advantage of tools and resources created by an OCS system.
Open and Collaborative Science (OCS) in the Global South/Developing Countries:
Rather than wasting resources in mimicking scientific establishments and policies of the pre-digital age, policy makers in developing countries should leverage networks by creating incentives for scientists to focus on research that addresses development concerns, and by finding ways to tie knowledge to local problem solving.
This approach is highly appropriate because many of the “grand” challenges facing humanity today – such as climate change, environmental degradation, emerging infectious diseases, inadequate access to clean drinking water and food insecurity – are global in nature but disproportionately hurt developing economies. Meeting these challenges requires not only appropriate local solutions but also rapid and sustainable deployment of new tools and approaches that draw from the global scientific and knowledge commons.
In addition to addressing these global-level problems, which require long term interventions, OCS also promises to increase visibility and impact of research at the local level, facilitate participation of researchers in local and international collaborations, encourage public engagement with science through activities such as citizen science, and promote the culture of knowledge sharing and new thinking on social innovations. These are seen to be short-term outcomes that have direct development benefits and could contribute to the strengthening of local research capacity through education and participation
While Open and Collaborative Science is lauded by many as a guiding principle, the practice is far from universal in the Global North, and awareness of its benefits and practices are even less prominent in the Global South. While many of the purported development benefits of Open and Collaborative Science are highly attractive, there is little empirical evidence at the moment to support or refute these claims.
We have a limited understanding of the institutional contexts and value framework within which open approaches to science take place, and equally little about the mechanisms linking Open Science practices with potential developmental outcomes.
The Open and Collaborative Science Development Network is designed to address these gaps through multi-stage data collection and theory building processes.