3 Open Research Data (ORD)
We recommend handling research data through its life cycle as if it would become of public domain. Even if, for legal, ethical or other reasons the data cannot be made accessible to everyone without restrictions, the metadata describing the data can, almost always, be shared openly. This means managing research data with a focus on its external reusability, that is, with enough documentation to enable reuse by external collaborators outside one’s own research group. To achieve this, it is important to first understand what is meant by research data, the differences between research data management and open research data, and the different stages of the data life cycle.
3.1 Research data
According to the Organisation for Economic Co-operation and Development (OECD) (source from 2021) research data from public funding includes:
(…) actual records (such as numerical scores, textual records, images, and sounds) resulting from research that is partially or fully funded by public funds, used as primary sources for scientific research, and that are commonly accepted in the scientific community as necessary to validate research findings. This term does not cover laboratory notebooks, preliminary analyses, or drafts of scientific papers, plans for future research, peer reviews, personal communications with colleagues, or physical objects, (e.g., laboratory samples, strains of bacteria, or test animals).
3.2 Research Data Management (RDM)
RDM can be defined as
(…) the handling of research data (collection, organisation, storage, and documentation) during and after a research activity. (https://www.scienceeurope.org/our-priorities/open-science/research-data-management).
It is often conceptualized with reference to the research data life cycle illustrated in Figure 3.1. RDM is therefore a generic term that doesn’t necessarily imply open access to research data or alignment with best practices. For instance, RDM could be interpreted to refer to managing data internally without the curation efforts to make it reusable when shared.
3.3 Open Research Data (ORD)
ORD can be defined as
Data that can be freely accessed, reused, remixed and redistributed, for academic research and teaching purposes and beyond. Ideally, open data have no restrictions on reuse or redistribution, and are appropriately licensed as such (Open Science Training Handbook).
This definition focuses on open licensing and the absence of technical access barriers. In praxis, however, “openness” also implies a broader sense of accessibility, including things such as comprehensive documentation and metadata that are an essential prerequisite of any public sharing of research data.
Producing ORD is also required in SNSF funded projects (see SNSF policy on ORD). This policy follows the statement “research data are the evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (e.g. print, digital, or physical).” from the Concordat on Open Research Data. In addition, since 2017 the SNSF requires to have a Data Management Plan (DMP) outlining the data life cycle, including where and how they will be shared and preserved (cf. research policies). Other funders such as the European Union (Horizon Europe) make similar requirements (cf.open aire requirements).
The recent project recORD - recognise Open Research Data practices, with a focus on research assessment, acknowledged that ORD practices should take into account that “open”, and even “data”, are terms that can have different meanings across disciplines and epistemic cultures (Araujo, Bornatici, and Heers 2024). In the recORD project, practices are defined as integral components of the broader concept of open science. These practices are defined as
(…)practices aimed at facilitating access to and reuse of research data by any interested party, contingent upon specific agreements based on the type of data (Fecher and Friesike 2014).