Open Science II (OS II)

The project is implemented by the applicant (Charles University) in cooperation with 11 partners. The implementation team consists of an administrative team and an expert team.

The administrative team is led by the Chief Project Manager, who is responsible for the overall management of the project, coordination of the administrative and expert team, compliance with P JAC rules and the achievement of objectives and budget. The Project Manager and the Financial Manager oversee administrative and financial coordination at the level of the applicant and partners. Administrative staff oversee day-to-day operations.

The expert team is led by the Expert Project Manager and consists of guarantors of thematic and cross-cutting key activities, expert guarantors of outputs, expert researchers and other specialists according to the needs of individual activities.

The highest decision-making body is the Project Internal Management Authority. Coordination and supervision of the implementation of the project is overseen by the Project Executive Committee.

This structure supports effective management, flexible response to changes and the quality assurance of outputs in line with project objectives.

The aim of TKA B/H/F is to build repository infrastructure for the management, sharing and reuse of diverse types of biological, chemical and clinical data generated in basic and applied research in the fields of medicine, biology, chemistry and related sciences. Repository sub-activities share a common framework that is firmly anchored in FAIR principles, both in technical terms (standardized metadata, access interfaces, formats) and in procedural terms (curating, versioning, permission management, citation).

An essential feature of all repository systems created is to ensure interoperability with the National Repository Platform (NRP), the use of unified authentication/authorization through Life Science Login and the possibility of exporting metadata to national and European catalogues and infrastructures. FAIRification is not perceived as a one-off output, but as an ongoing and living framework that enables effective and sustainable data sharing and reuse across disciplines and institutions. For selected repositories, FAIRification is further extended to include direct support for advanced data processing tools (e.g. AI models in chemical biology, data annotation using ontologies).

The key activity does not represent an isolated effort, but a systematic change in access to data in the field of health, biology and chemistry in the Czech Republic, with an emphasis on international compatibility, repeatability of research, openness and sustainability. The goal is to create an infrastructure that will allow not only the storage, but also the full use of data for advanced research (meta)analysis, education, cross-domain collaboration and knowledge transfer.

TKA MATECH will create an environment for the high-quality management of FAIR data research in the field of material sciences and technologies in the Czech Republic. The central activity is the implementation of a new DANTE^c domain repository with an adequate metadata profile, selection of relevant licenses and a user interface that will help improve the storage, but also the searching and reuse, of research data. The repository will be connected to data management tools for users and within research infrastructures and a tool for subsequent work with data in the repository. This interconnection will contribute to the improvement of stored domain-specific data and will also facilitate the broad cross-domain use of the repository using modern ML and AI-based tools.

Thematic cluster Data Management for Artificial Intelligence and Machine Learning will ensure the creation of a new, domain-focused AI/ML (Artificial Intelligence/Machine Learning) repository known as Data Management for Artificial intelligence and Machine Learning based on the Clarin DSpace repository system. The repository aims to offer a unified platform inspired by the global Hugging Face application that will enable efficient sharing and management of AI/ML models, datasets and workflows, including the provision of advanced tools for working with data and the possibility of connecting to computing infrastructures through the LEXIS Platform.

With the TKA SOC, a domain repository platform for social sciences will be created based on the innovation of two existing CSDA and DataHub repositories supplemented by a newly built repository for sensitive data. The effectiveness of achievement of the goals is based on the connection of existing systems to the NDI EOSC in the Czech Republic and their supplementation with the necessary, previously missing element of the domain infrastructure. The comprehensive environment for the implementation of the Open Science policy in the social sciences aims at both the storage of data and their reuse in social science and cross-domain research. Existing systems are integrated into the international data services ecosystem; at the same time, the NDI will be connected to the European level of the domain data infrastructure. The KA will also focus on the systematic dissemination of project outputs and the development of educational capacities in the field of data management, and not only for the professional community in social sciences. The goal is to raise awareness of new services, analyses and educational materials created in the project through a targeted communication strategy and a newly created web platform.

Thematic cluster Physical Sciences is building a specialized branch repository known as "Physics" based on the implementation of the Invenio system in the National Repository Platform (NRP). The repository will offer robust storage, clearly defined metadata models and automated tools for the mass transfer and verification of large data packages from the ATLAS ITk, DUNE, CTAO SST-1M, Auger and crystallographic structural analysis experiments. This ensures that data generated today will be stored in accordance with FAIR principles from the very beginning and will be traceable and usable over the long term for future generations of researchers.

The technical part is followed by innovative services: a tool for automated metadata creation connected to Electronic Laboratory Logs (ELN), a web component for the direct visualization of multidimensional data (HDF5/NeXus, fits, etc.) in a browser and e-learning modules and materials for workshops that will quickly expand FAIR data management skills among both Czech and international teams. These open-source tools will also be immediately usable in other NDI clusters and will strengthen the interoperability of the entire Czech infrastructure.

Key Activity 7 will focus on the innovation of existing and the development of new repositories in the humanities cluster, as well as the development of tools and services for the development of the NDI.

The repositories are concentrated around four existing large field infrastructures for the humanities as central producers of research data and competence centres in the field of open science within the cluster (Archaeological Information System of the Czech Republic – AIS CR, Czech Literary Bibliography – CLB, Czech National Corpus – CNC and LINDAT/CLARIAH-CZ). The activity will utilise existing repository solutions, which will be supplemented by new repositories or repository communities in selected fields with significant research data production. The following repositories will be upgraded:

1. LINDAT/CLARIAH-CZ, which will extend its user community to the field of corpus linguistics by integrating data of the CNC research infrastructure, on the basis of which a separate collection/community of the repository will be created.
2. The Digitalia Muni ARTS institutional repository.
3. The ArchaeoVault archaeology repository.

Literary Bibliography research infrastructure and, depending on the results of internal analysis, will be operated as a separate collection/community within one of the existing repositories or as a separate instance.

Environmental Science Thematic Cluster will focus on several points:

• the creation of metadata models, standards and methodologies enabling the processing of mass spectroscopic data, photographic records for the purpose of studying biodiversity, the genetic bank of wildlife, zoological collections, toxicological and ecotoxicological data and GIS data. It will further focus on the introduction of metadata standards to ensure semantic interoperability (interconnection with controlled dictionaries, thesauri and ontologies) and the assignment of citable persistent identifiers to data objects or extracts;
• preparation of an application interface for the metadata exchange of managed datasets (DCAT) and an interface for data exchange;
• preparation of supporting materials, including instructions for the creation and validation of FAIRified datasets;
• analysis of other needs of the research community.

In all cases, the issue of ensuring the quality and interoperability of repositories and data in an international context, the issue of licencing and legal models and connections to external data sources will be addressed.

Thematic cluster Sensitive Data will add a layer of sensitive data management throughout the NRP and NDI space to the project. It will continue to support activities necessary for the FAIRification of data in repositories and work on licencing and other legal regimes/models. It will expand current capabilities with the tools and functionalities necessary for the management sensitive data. It will create detailed and guidelines for the FAIRification of sensitive data, tools or services applicable within the life cycle of sensitive data management and, last but not least, it will focus on the good practice of sharing and processing sensitive data generated from, among other things, cooperation between academia and the private sector. The TKA aims to create clear and harmonised rules for accessing sensitive data that cannot be shared under current conditions.

The key activity with cross-cutting themes responds to current fundamental challenges in the field of Open Science, the solutions for which, taking into account the very rapid current development, were not, or could not be, included in the forthcoming architecture of the NRP project. However, the Open Science II project cannot by its nature ignore them, and by addressing them, it will significantly contribute to the development of the NDI. In the context of the OS II project as a whole (in relation to the field KAs), the term "cross-cutting themes" must be understood in the sense of "complementary". If the NDI is to constitute a unified/standardized complex and an evolving structure, it is currently impossible to avoid the building of a secure entry portal providing the broadest and most effective technical and user support. This cannot be built and operated without the use of AI technology, taking into account the expected number and content width of cases processed. The emphasis on cybersecurity must then also be understood and directed in legal contexts, particularly in relation to all forms and modes of the handling of sensitive data, while not forgetting the issues associated with the generation and management of credible provenance in order to support the traceability of the predecessors of objects stored in repositories, or from laboratory journals or other SW and beyond. A further integral component of the KA is targeted communication with research communities and institutions. The effective sharing of information on the procedures and results of the project is key to promoting cross-domain collaboration, the involvement of professionals and increasing awareness of emerging services. The project focuses on topics such as the interoperability of research data, the benefits of FAIR principles, the usability of OS II services, vocational training and the wider context of open science within the EOSC European initiative. These topics are communicated with regard to the needs of individual scientific communities and current challenges in the field of data management.

In the key activity, the implementation of the EOSC initiative will be supported through calls for cooperation on OS II Mini-Projects. A complete grant scheme of calls for cooperation will be implemented.