Research and Data Reusability

Research data reuse is the quintessence of the open science and open data principles on which modern science is based. To make it feasible, first, all potential barriers, technological, political, legal, and economics must be identified. In a previous paper, we have described the technological barriers that hinder research data (re)usability. In this paper, we have described the conceptual foundations of research data (re)usability. This does not mean that we underestimate the importance of the policy and legal aspects and their power to hinder data reuse.

At present, the trend in the research data management practices is the creation of domain-specific data centers designed to ensure the stewardship and provision of quality-assessed data and data services to the international science community and other stakeholders. Each domain-specific data center has the responsibility for defining an appropriate Data Management Plan. In this DMP, a conceptual data usability scenario must also be included; it should contain:

• identification of the "usability relationships" between the data author and potential data users;
• transformation of the explicit and tacit knowledge accumulated during the data production process into mobile knowledge in order to be transferred and translated from the data author context to the data user contexts; and
• definition of appropriate levels of data abstraction and data representation to be communicated to the potential users.

In essence, in the context of a DMP, a Data Publication process must be put into action that will perform all the functions listed in Section 5.

There are three main contributions in this paper: first, it presents the problem of scientific data (re)usability in a structured and comprehensive form; second, it sets the conceptual foundations of data usability by borrowing basic concepts from other theoretical fields, i.e., relational thinking, levellism, and knowledge representation and applying them in the data usability field; and third, it identifies the data publication process as the enabler of data usability.

Therefore, in making scientific data reusable first, a conceptual data usability scenario must be defined; it includes:

• identification of the "usability relationships" between the data author and potential data users;
• transformation of the explicit and tacit knowledge accumulated during the data production process into mobile knowledge in order to be transferred and translated from the data author context to the data user contexts; and
• definition of appropriate levels of data abstraction and data representation to be communicated to the potential users.

Then, a Data Publication process must be put into action that will perform all the functions listed in Section 5 and will be implemented within the conceptual data usability scenario identified beforehand.

In conclusion, we foresee that the well-established model of scientific publishing will be increasingly complemented by a system of data publication and that many of the issues regarding research data sharing and reuse could be effectively addressed if the principles of Data Publication are applied within a Data Usability Conceptual Framework.