Action Line D2.6 – Develop and disseminate discipline- or data community-specific codes of conduct with regard to ORD

Despite large volumes of data being generated in preclinical neuroimaging research, there is a lack of adequate support for processing them according to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This gap leads to inefficient data management and limited utility of the data that are made openly available. Thus, this project aims to develop a conduct for open research data (ORD) specifically targeting researchers working with preclinical (animal) neuroimaging data. The target community involves researchers using various imaging techniques to study the central nervous system in animals.

While there are comprehensive guidelines for planning, conducting and reporting animal experiments, as well as for managing data of different imaging modalities, the landscape of these resources is fragmented. This project will systematically compile and distil these resources to facilitate adoption of FAIR ORD practices by researchers. The project will be implemented by the Center for Reproducible Science at the University of Zurich. Fabio Molo MSc will coordinate the project and Dr. Gorka Fraga Gonzalez will develop the code of conduct in collaboration with different key stakeholders including animal neuroscientists.

The content of the code of conduct will be divided into two main parts: 1) metadata, and 2) sharing and publishing. The metadata part will involve a review of available standards, recommendations for content curation, and practical tools to handle metadata. The sharing and publishing part will include information on data archiving, policies, and ethical guidelines. This will benefit not only the 3R principles (Replacement, Reduction, Refinement) in animal research but also improve data reusability and harmonisation in the community.

Due to certain ethical and legal considerations, open science presents challenges for visual research. Key ethical concepts include informed consent, anonymity, confidentiality, and data anonymization/pseudonymization. Therefore, visual data, which frequently contains personal identification and make anonymization challenging, is considerably less accessible than verbal data. Preparing visual data in accordance with open research practices while taking the aforementioned ethical concepts into consideration is the primary challenge.

With the increasing number of social science research projects handling and analyzing visual data, the need for a code of conduct has become crucial. Thus, Dr. Anna Picco-Schwendener and CCdigitallaw team of the Università della Svizzera italiana together with Prof. Dr. Katharina Lobinger, expert in visual communication, aim to create a clear, understandable code of conduct for visual social research, integrating legal and ethical considerations with a focus on open science. It addresses legal questions on copyright, data protection, and licensing, while also addressing ethical challenges such as the trade-off between visibility and anonymity, ethical decision-making based on the type of visual data, and recommended practices for anonymizing visual materials.

The field of Indoor Positioning (IP) currently lacks formal guidelines and standards regarding its open research data. This absence of standardized practices has led to a fragmented landscape where data sharing and management practices vary widely. Moreover, sharing and using ORD to consistently compare methods still constitutes the exception rather than the de facto standard option in the publications of the field. As identified in Dr. Grigorios Anagnostopoulos previously lead project (CoORDinates), many datasets are stored in private repositories, lack completeness in terms of metadata, and are often published without clear licensing or versioning protocols.

CoORDinance aims to capitalize on these solid foundations to propose a clear Code of Conduct, in line with the Swiss National ORD Strategy and the FAIR principles.