Reflection & Resonance
Research findings are increasingly shaped by algorithms. All stakeholders require transparent and reproducible epistemological processes.
In order to establish trust in research that is shaped by algorithms, it is vital to ensure transparent, reproducible practices and clear communication of findings. This shift requires careful consideration from technical, societal and ethical perspectives.
Exploration & Knowledge Organisation
In the modern business world, accessing the wealth of information available today requires the use of search engines and sophisticated information processing applications. Semantic technologies play a crucial role in facilitating the Findability, Accessibility, Interoperability, and Re-usability (FAIR) of research data.
Knowledge organisation requires the implementation of robust methodologies to formally represent, organise, and manage domain-specific as well as procedural knowledge. Semantic technologies provide a formal representation of knowledge contained in research data, thus facilitating the efficient integration of heterogeneous data sources. The growing adoption of AI-based knowledge mining technologies requires comprehensible and trustworthy AI algorithms ("explainable AI"). A range of methods are applied, including statistical and linguistic analysis, as well as machine learning in combination with symbolic logic and interference mechanisms.
Legal & Ethical Challenges
The digital transformation is shaped by data ethics, data protection, copyright and data law.
It is essential to evaluate emerging legal framework conditions, as they may provide the means to make sensitive data collections available for re-use in a legally secure manner. This requires a thorough analysis of the involved research data and its legal and political context.
Tools & Processes
The goal of this dimension is assessing the acceptance and impact of digital tools that have been precisely tailored following the needs of the scientific community. This aspect also involves the design of measures to increase the security awareness of researchers developing scientific software.
The digital transformation is significantly impacting the entire research data lifecycle, from collection to publication and archiving. Smart tools such as Electronic Lab Notebooks (ELN) are supporting researchers to generate and provide interoperable and documented data, with the ultimate goal of a data continuum. At the same time, there is the need to intensify the security of both processes and the security awareness of those involved.