This is part of a series of blogposts documenting the CREATe Symposium 2019. In this post, Methinee Suwannakit and Thomas Margoni report on the Information, (Research) Data and Open Science Workshop which took place on Thursday 10 October 2019.
Valerie McCutcheon discussing legal issues connected with research data management
The opening remarks were followed by a panel presentation and discussion that started with a brief but thorough overview of the regulatory framework and continued with two very insightful examples of how data and their (unclear?) legal status impact on science and society.
The panel started with Nicolas Jondet (University of Edinburgh), who discussed the evolution of the Text and Data Mining exception under EU/UK law (‘The Text and Data Mining Exception in the EU: Unfinished Business?’), following up on his 2018 law review article on the topic. Nicolas explained how the balance between TDM and copyright has been debated for more than a decade, with the UK becoming the first country in the EU to introduce a TDM exception for non-commercial research in 2014. This was followed by other countries, such as France in 2016, which limited it only to texts, and excluded audio-visual works. The EU framework for such exceptions has now been established by the CDSM Directive which includes two mandatory exceptions for Members States to implement: a relatively strong TDM exception for research conducted by research organisations (Article 3) and, for other uses, a weaker TDM exception which can be over-ridden by contract (Article 4).
Nicolas argued that although the EU TDM exception in Article 3 offers a strong and wide exception for research institutions, the overall framework for TDM exceptions is still limited compared with the US. He argued that the EU should have extended the benefits of Article 3 to cover every use and to benefit everyone. One strong TDM exception would have been better than two exceptions with different characteristics and beneficiaries. This distinction might create difficulties for users to have some legal certainty about their use of TDM. Furthermore, this distinction between the type of TDM exception from which users will be able to benefit, according to their status and purpose, will introduce practical problems for right holders too. For example, how can they distinguish covered uses (research organisation for research purposes) from other type of uses (e.g. journalism, criticisms, review, etc). Finally, some observations were made in relation to the potential TDM status in a post-Brexit framework, highlighting that the UK might choose a broader TDM exception not limited by the current EU copyright framework of Arts. 3 and 4 CDSM Directive and 5 InfoSoc.
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Following this effective overview of more than 10 years of legislative developments, Andrew McHugh from the Urban Big Data Centre (UBDC), offered an insightful perspective on what can actually be done with data in applied research and why “Social Data Science needs Data”. UBDC is a research centre aiming to promote innovative research methods and the use of big data to improve social, economic and environmental well-being in cities. Urban big data are collected and aggregated from a wide range of different sources, often publicly available on the Web. Nevertheless, there are major challenges in data acquisition and reuse, some of technical nature, but more often connected with legal and/or contractual uncertainty. Yet, these challenges are frequently the practical manifestation of a generalised scepticisms – if not reticence – of many organisations towards the idea of making their data available.
Motives are varied and can range from lack of capacity to disclose adequately structured and cleaned data, competitive advantage considerations, risks connected with legal uncertainty (e.g. data protection, ownership, etc), all the way up to the concern that openly divulging research data may lead to exposure to criticism (research design, methodology, etc). Andrew also discussed that, from a scientist point of view, innovation is often stifled by this legal uncertainty. Whether this conception of the role of legal rules is merely perceived (the law is too difficult to be understood by non lawyers) or is actually real (the law does not offer a proper answer) does not matter too much, as the result is fairly consistent: innovation is halted. In the field of data science in particular, copyright, licensing and data protection issues are often perceived as the most unclear, uncertain and risky areas with the consequence that they often act as obstacles to research and innovation.
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Finally, Valerie McCutcheon (Research Information Manager, University of Glasgow), discussed some of the legal issues connected with delivering a research data management service and the many benefits of an open environment. Valerie started with an overview of some of the Open Science advantages and opportunities for researchers. For example, strong access to knowledge on a public and non discriminatory basis, prestige and recognition, capability of policy influence, wider diffusion, and higher citation rates. However, Valerie stressed that while important improvements have been made, not all the difficulties related to the regulatory framework have been addressed. In addition to the legal issues already identified during the panel, Valerie added a few others which mainly look at the lack of standardisation and often coordination with funders, publishers, research organisations, institutional repositories and the connected contractual relationships.
create symposium October 2019
During the final panel discussion and closing remarks, it emerged how the concept of “data” has achieved a certain level of maturity that the law is still failing to recognise. Consequently, the fragmented regulatory framework that the law has created around the use and reuse of data is often a cause of uncertainty in its own right. In his final remarks, Thomas suggested that a more structured approach to the regulation of data, especially in areas such as ownership, access and reuse, is the way forward in order to implement some of the basic principles of Open Science in the field of data. One could even say, a “data in the public interest doctrine”. But this will be discussed in more detail in a future post!