The Principles and Guidelines apply to research data gathered using public funds for the purposes of producing publicly accessible knowledge. The nature of “public funding” of research varies significantly from one country to the next, as do existing data access policies and practices at the national, disciplinary and institutional levels.
Institutional arrangements
Disseminating microdata files may be a new activity for many NSOs, and one that might lead to new and important uses of their data. In their publication, Principles and Guidelines for Access to Research Data from Public Funding, the Organization for Economic Co-operation and Development (OECD) defines a set of principles to which data providers should adhere:
- Openness
- Flexibility
- Transparency
- Legal conformity
- Protection of intellectual property
- Formal responsibility
- Professionalism
- Interoperability
- Quality
- Security
- Efficiency
- Accountability
Openness means access on equal terms for the international research community at the lowest possible cost, preferably at no more than the marginal cost of dissemination. (…)
Flexibility requires taking into account the rapid and often unpredictable changes in information technologies, (…), legal systems and cultures of each (…) country. (…)
Information on research data and data producing organizations, data documentation and specifications of conditions attached to the use of these data should be internationally available in a transparent way, ideally through the Internet. (…)
Data access arrangements should respect the legal rights and legitimate interests of all stakeholders. (…)
Data access arrangements should consider the applicability of copyright or of other intellectual property laws that may be relevant to publicly funded research databases. (…)
Access arrangements should promote explicit, formal institutional practices, such as the development of rules and regulations, regarding the responsibilities of the various parties involved in data related activities. These practices should pertain to authorship, producer credits, ownership, dissemination, usage restrictions, financial arrangements, ethical rules, licensing terms, liability, and sustainable archiving. (…)
Institutional arrangements for the management of research data should be based on the relevant professional standards and values embodied in the codes of conduct of the scientific communities involved. (…)
Technological and semantic interoperability is a key consideration in enabling and promoting international and interdisciplinary access to and use of research data. Access arrangements, should pay due attention to the relevant international data documentation standards. (…)
The value and utility of research data depends, to a large extent, on the quality of the data itself. Data managers and data collection organizations should pay particular attention to ensuring compliance with explicit quality standards. (…)
Specific attention should be devoted to supporting the use of techniques and instruments to guarantee the integrity and security of (…) data. (…)
One of the central goals of promoting data access and sharing is to improve the overall efficiency of publicly funded (data collection) to avoid the expensive and unnecessary duplication of data collection efforts. (…)
The performance of data access arrangements should be subject to periodic evaluation by user groups, responsible institutions and (…) funding agencies. (…)
Organisation for Economic co-Operation and Development (OECD) - 2007
It is likely that complying with these principles will require new procedures and objectives. In their Guidelines, OECD defines the major issues inherent in providing data access as follows (these same issues apply to statistical microdata generated for statistical purposes by official data producers):
- Institutional and managerial: While increased accessibility is important to all science communities, the diversity of the scientific enterprise suggests that a variety of institutional models and tailored data management approaches are most effective in meeting the needs of researchers.
- Financial and budgetary: Scientific data infrastructure requires continued and dedicated budgetary planning and appropriate financial support. The use of research data will not be maximized if access, management, and preservation costs are an add-on or afterthought in research projects. It is important to note, however, that the cost of storing and managing data has decreased dramatically in recent years, and lack of knowledge about such changes can, in itself, be a barrier to advancement.
- Legal and policy: National laws and international agreements, particularly in areas such as intellectual property rights and the protection of privacy, directly affect data access and sharing practices, and must be fully taken into account in the design of data access arrangements.
- Cultural and behavioral: Appropriate educational and reward structures are a necessary component for promoting data access and sharing practices. “These considerations apply to those who fund, produce, manage, and use (...) data. (...) Responsibility for the various aspects of data access and management should be established in relevant documents, such as descriptions of the formal tasks of institutions, grant applications, research contracts, publication agreements, and licenses.”
(OECD Principles and Guidelines for Access to Research Data from Public Funding. 2007)
An alternative: trusted data repositories
For some data producers, establishing and maintaining a data archive and dissemination service might be an unrealistic objective for budgetary, legal, or other reasons. An alternative is to entrust an existing data archive such as the UK Data Archive located at the University of Essex. It manages and disseminates data from statistical agencies, research organizations, and researchers themselves. Another example is the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan, which performs a similar function in the United States. These data archives not only provide competent license management but are also leaders in data curation and innovation. An example is the UK Data Archive’s new suite of web pages providing guidance on data management and sharing. These provide data creators, data managers, and data curators with best practice strategies and methods for creating, preparing, and storing shareable datasets.