by Ricard Munné Caldés (ATOS)
The Science2Society project improves collaboration between science and industry by leveraging big research data through sustainable business models.
The Science2Society project (March 2016 ‒ February 2019) creates pilots and shares good practices, guidelines and training materials that improve awareness and practical performance in seven concrete university-industry-society interfacing schemes that are impacted by new practices derived from Science 2.0 and open innovation approaches and strategies. One of these schemes, led by the Aalto University and involving Atos Spain, Virtual Vehicle and the Joint Institute for Innovation Policy (JIIP) as main partners, is assessing the collaboration between research and industry through big data and science 2.0.
Big data can provide new economic, scientific and social value and new information can be extracted using big data technologies with the integration of additional datasets. The open data initiative together with the potential of big data are pushing many organisations from the government, industry and academia to open their data, so third parties can benefit from the analysis of this existing information. While the benefits of data openness are clear for organisations, the incentives for individual researchers to do so are not so obvious, although this is key to achieving the full potential of open science.
On one hand, this pilot aims to identify the obstacles preventing individual researchers from sharing their big research data and how they may be motivated to share them, and on the other hand, what needs to be done to enable industry to easily use these data. The overarching objective is then to identify what type of sustainable business models can best support both these issues: (i) the sharing of data and (ii) how to enable industry to take advantage of this data.
To this end, we conducted a literature review and examined two real-life cases where big research data are available. The first was a Finnish innovation database, which we used to investigate the challenges of opening the big data. Through a co-creation process based on interviews with database owners, potential users and open science experts, a proposal for opening the database was designed and validated, which resulted in a selection of different solutions as sustainable business cases. The second was the GCAT project, which is a biomedical research initiative with an open database with genetic information, environmental factors, medical records and biological samples from volunteers. In this case, through stakeholder interviews we learnt from the experience of an open big research database and extracted the specific business model underneath, deriving the best practices and lessons learnt.
The literature review revealed that the main obstacles to data sharing by researchers include: lack of perceived benefits, the effort required, and the risks of sharing data. Existing collaborative models in big data ecosystems must be promoted, paving the way for researchers to open their data.
Figure 1: Framework for opening big research database.
The conclusions from the two case studies were synthetised in two frameworks supporting the development of sustainable business cases. The framework for the Finnish invention database case starts with identifying the benefits of opening the database, the identification of potential users’ specific requirements, willingness to pay, and the potential user base. Following, it is important to investigate if there are any potential legal, functional or technical barriers that pose any constraints on data sharing. Finally, a business model consideration step is important to guarantee the sustainability of the process. For the GCAT use case, the framework is focused on the management of an existing open database. A successful collaboration can be achieved by minimising the data access fees, attracting the best researchers while allocating enough resources to ensure effective collaboration through data sharing. Privacy is an important factor and it should be reinforced through NDA agreements as part of the standardised informed consent protocols.
As final recommendations for the management of open big research data, researchers should develop a research data management plan prior to the start of the project. The decision to open the data should be based on a careful assessment of the underlying opportunities, barriers and alternative business models. We provide a generic process model for performing that assessment. Based on the GCAT case, lessons learnt and best practices for how to operate a big research database are provided. The key for a sustainable business model is to focus on developing a valuable proposition for data owners and users that benefits both parties.
For more information please refer to the Science2Society Knowledge Database, which contains case studies, methods and tools related to this pilot and the other pilots from the project. Additionally, the document “D3.2 Report on the implementation and evaluation of the UIS interface scheme pilots”, will be available soon in the downloads section of the project website.
The knowledge and studies on this collaborative schema and others will be maintained after the project ends with the setting of the Learning and Implementation Alliance.
Ricard Munné Caldés, Atos, Spain