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Leibniz ScienceCampus –
Digital Transformation of Research (DiTraRe)

Research results are increasingly being shaped by digitalization processes - this applies both to research methods and to their communication in science and society. At the Leibniz ScienceCampus "Digital Transformation of Research" (DiTraRe), we are investigating the effects and potential of the increasing digitalization of scientific work in four interdisciplinary research clusters.

Purple-coloured data cables hanging in the sockets of a server.

Based on use cases from different disciplines, we develop concrete solutions for challenges arising from digitalisation, which are then generalised.

The "Protected Data Spaces" cluster is dedicated to the handling of sensitive data in sports science. 
"Smart Data Acquisition" deals with intelligent data acquisition using the example of "smart laboratories" in chemistry. 
The "AI-based Knowledge Realms" cluster is researching the effects of artificial intelligence in biomedical engineering. 
We are furthermore investigating the influence of new forms of publications based on large amounts of data using the example of climate research in the "Publication Cultures" cluster.

At a meta-level, we reflect on the effects of digitalization on the security of scientific work as well as the changed perception within and outside the scientific system.

The work programme of DiTraRe is organised as a matrix: Four research clusters (RC) each start from a scientific use case that raises concrete questions. These questions are examined along the four dimensions. Subsequently, (i) an accordingly coherent solution is developed which (ii) is evaluated by the use case partners, (iii) the questions are generalised and placed in the overall context of the DiTraRe in order to move from the concrete to a more abstract level, (iv) ensuring the transferability of the research results to other disciplines.

Dimensions
Research Cluster
01
Protected data spaces
Ethical issues in the handling of sensitive data, e.g. necessary negotiation processes and trade-offs between transparency and data protection, as well as the trust of data subjects and researchers in the completeness, integrity, anonymity and traceability of data
02
Smart Data Acquisition
Appropriate involvement of society in virtual spaces, e.g. define the conditions for acceptance of data from a stakeholders’ perspective in transdisciplinary research processes
03
AI-Based Knowledge Realms
Design and communication of decision-making processes in view of the uncertainty of knowledge, e.g. knowledge gained by AI methods, as well as on the applicability of machine learning methods with regard to data representation
04
Publication Cultures
Necessity of a cultural change with regard to the needs of research and society for mutual communication, especially in the light of Open Science, and new formats of science communication
01
Protected data spaces
Representation of (partially) protected information in open Knowledge Graphs and on interweaving protected with non-critical data
02
Smart Data Acquisition
Application of novel methods of data acquisition, analysis and interpretation, and their evaluation in comparison to the results gained by traditional intellectual processes
03
AI-Based Knowledge Realms
Explainability and explanatory components based on symbolic knowledge representation (combination of symbolic and sub-symbolic AI, explainable AI), on hybrid AI systems that complement humans, on automatically generated semantic relations in Knowledge Graphs
04
Publication Cultures
Massively parallel authoring and quality assurance of large Knowledge Graphs
01
Protected data spaces
Data protection and pseudonymisation/anonymisation of different categories of sensitive data and conceptualises re-use models by taking into account ideas such as data intermediation services and data altruism. Based on the results, we develop security and privacy awareness measures
02
Smart Data Acquisition
IP legislation and licences for cooperatively created data and data resulting machine-based analyses
03
AI-Based Knowledge Realms
Potential of synthetic training data for AI systems with regard to the challenges of data protection and legal questions regarding digital twins, e.g. in medicine
04
Publication Cultures
Impact and analysis of data laws, policies and data strategies, particularly with respect to Open Science
01
Protected data spaces
Requirements for secure storage of personal data with regard to integrity, confidentiality, authenticity and availability. We design security and privacy solutions that consider (socially) acceptable risks
02
Smart Data Acquisition
Automation and virtualisation of laboratory research (“smart lab”), including the design and implementation of next-generation ELN with innovative functions to facilitate accelerated research processes, such as directly connected digital measuring devices
03
AI-Based Knowledge Realms
Necessary infrastructure to generate, store and disseminate (synthetic) training data, with emphasis on interoperability and re-use
04
Publication Cultures
Publication and exploration of extensive datasets, on new publication formats, e.g. including actionable source code, partially generated text, software publications