Development of research infrastructure in the condition of globalization: the experience of the Czech Republic

Problem setting. The research is devoted to the analysis of the development of research infrastructures of the European Union based on the experience of the Czech Republic. The article analyzes the legal basis and practice of the functioning of research infrastructures in the European Research Area, considers the typology of large research infrastructures. The purpose of the article is to analyze the development of research infrastructures in the EU, in particular, on the example of the Czech Republic. Analysis of resent researches and publications. Today, aspects of the development of innovation systems and research infrastructures of the European Union are a topic for research of many domestic scientists. However, the issue of integration of the scientific and innovative system of Ukraine into the European Research Area remains urgent. Article's main body. Research infrastructures means a research facility necessary for conducting comprehensive research and development with high financial and technology demands, approved by the Government and established to be also used by other research organizations. The Czech Republic has responded to the increasing importance of research infrastructures and for the purpose of showing them as one of the key elements of the national research and innovation system. The Act on the Support of Research and Development is the principal document defining the support for R&D in the Czech Republic. It defines the key forms of financing research and development, the main governmental bodies responsible for R&D and the procedural steps for their assignment and use of this type of financial aid. According to the Roadmap of Large Research Infrastructures of the Czech Republic, the basic typology of research infrastructures divides facilities into three groups: single-sited research infrastructures situated in one place, distributed research infrastructures including a larger number of capacities situated in different places, and virtual research infrastructures. From the perspective of life cycle stages, research infrastructures are classified into research infrastructures in the preparatory phase, implementation/construction phase, operation phase and decommissioning phase. All of the above types of research infrastructures can also be found in the research and innovation system of the Czech Republic. Conclusions and prospects for the development. In recent years, the research infrastructure of the EU has undergone significant development, as evidenced by the example of the Czech Republic. As for Ukraine, which is just beginning its path in this direction, an important step was the adoption of the Concept of the State Target Program for Research Infrastructures in Ukraine until 2026, as well as the approval of the Roadmap for integration of Ukraine's research and innovation system into the European Research Area.

Electronic Research Infrastructure for Bulgarian Medieval Written Heritage: history and perspectives

The paper traces the history of the Histdict system, which turned into a basis for the new Electronic Research Infrastructure for Bulgarian Medieval Written Heritage, which was included into the National Research Roadmap at the end of 2020. Through this act the state declares its support to our resources, that have been so far created and supported by project funding. And of course, it is a big recognition of our efforts and achievements. On the other hand, this act coincided with two other events: the inclusion of RESILIENCE (Research Infrastructure on Religious Studies) in which Histdict is taking part, in the European Research Infrastructures Roadmap and the start of the updating and upgrading of the system. Given the situation the Infrastructure is now facing new challenges—not only the successful improvement of the services it offers, but also the inclusion of the Orthodox Cultural Heritage into European research exchange, which will promote and popularize the history and culture of Southeastern Europe.

Recommendations for connecting molecular sequence and biodiversity research infrastructures through ELIXIR

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth’s biodiversity.

DRŽAVNA POMOĆ ZA ISTRAŽIVANjE I RAZVOJ I INOVACIJE ZA KOJU SE PRETPOSTAVLjA DA JE KOMPATIBILNA SA UNUTRAŠNjIM TRŽIŠTEM

Capital for conducting R&D projects is relatively more expensive than for ordinary investment. That is why public support i.e. state aid is necessary. Preferred type of state aid for research & development and innovation is direct funding in the form of grants. This type of state aid generally belongs to state aids that may be considered to be compatible with the internal market. If a new state aid compatible with the internal market European Commission must find out separately for every notified aid. But if state aid for research & development and innovation is awarded under conditions laid down by Commission Regulation (EU) No 651/2014 of 17 June 2014 declaring certain categories of aid compatible with the internal market in application of Articles 107 and 108 of the Treaty, there is a legal presumption that state aid is compatible with the internal market and at the same time it is exempted from the notification requirement. State aid that is considered compatible with the internal market can be given for: research and development projects, research infrastructures, innovation clusters, innovation by SMEs, process and organisational innovation and research and development in the fishery and aquaculture sector.

Knowledge sharing and discovery across heterogeneous research infrastructures

Research infrastructures play an increasingly essential role in scientific research. They provide rich data sources for scientists, such as services and software packages, via catalog and virtual research environments. However, such research infrastructures are typically domain-specific and often not connected. Accordingly, researchers and practitioners face fundamental challenges introduced by fragmented knowledge from heterogeneous, autonomous sources with complicated and uncertain relations in particular research domains. Additionally, the exponential growth rate of knowledge in a specific domain surpasses human experts’ ability to formalize and capture tacit and explicit knowledge efficiently. Thus, a knowledge management system is required to discover knowledge effectively, automate the knowledge acquisition based on artificial intelligence approaches, integrate the captured knowledge, and deliver consistent knowledge to agents, research communities, and end-users. In this study, we present the development process of a knowledge management system for ENVironmental Research Infrastructures, which are crucial pillars for environmental scientists in their quest for understanding and interpreting the complex Earth System. Furthermore, we report the challenges we have faced and discuss the lessons learned during the development process.

Approaching Trust: Case Studies for Developing Global Research Infrastructures

Trust is a core component of collaboration. Trust is a local phenomenon, and scientific research is a global collaborative, its impact multiplied through open exchange, communication and mobility of people and information. Given the diversity of participants, local policies and cultures, how can trust be established in and between research communities? You need transparent governance processes, thoughtful engagement of stakeholder groups, and open and durable information sharing to build the “stickiness” needed. In this paper we illustrate these concepts through three trust building use cases: ORCID, Global Alliance for Genomics and Health, and SeamlessAccess, platforms sharing an identity and access technical service core, painstaking community building, and transparent governance frameworks.

The Principles of Data Reuse in Research Infrastructures

The principles known by FAIR abbreviation have been applied for different kinds of data management technologies to support data reuse. In particular, they are important for investigations and development in research infrastructures but applied in significantly different ways. These principles are recognized as prospective since, according to them, data in the context of reuse should be readable and actionable by both humans and machines. The review of solutions for data interoperability and reuse in research infrastructures is presented in the paper. It is shown that conceptual modeling based on formal domain specifications still has good potential for data reuse in research infrastructures. It allows to relate data, methods, and other resources semantically, classify and identify them in the domain, integrate and verify the correctness of data reuse. Infrastructures based on formal domain modeling can make heterogeneous data management and research significantly more effective and automated.

Infraestrutura de Investigação para a Ciência e Tecnologia da Linguagem - PORTULAN CLARIN

This paper presents the PORTULAN CLARIN Research Infrastructure for the Science and Technology of Language, which is part of the European research infrastructure CLARIN ERIC as its Portuguese national node, and belongs to the Portuguese National Roadmap of Research Infrastructures of Strategic Relevance. The PORTULAN CLARIN includes a helpdesk, a repository, where resources, such as corpora, lexicons and processing tools are deposited for long-term archiving and can be searched and retrieved, and a workbench, where Language Technology tools and applications are made readily available online and can be used in different types of interfaces. Its goal is to contribute to the technological development of natural languages and for their preparation for the digital age, with a special focus on the Portuguese language in all its varieties and modalities.

ADT2FHIR – A Tool for Converting ADT/GEKID Oncology Data to HL7 FHIR Resources

Harmonized and interoperable data management is a core requirement for federated infrastructures in clinical research. Institutions participating in such infrastructures often have to invest large degrees of time and resources in implementing necessary data integration processes to convert their local data to the required target structure. If the data is already available in an alternative shared data structure, the transformation from source to the desired target structure can be implemented once and then be distributed to all participants to reduce effort and harmonize results. The HL7® FHIR® standard is used as a basis for the shared data model of several medical consortia like DKTK and GBA. It is based on so-called resources which can be represented in XML. Oncological data in German university hospitals is commonly available in the ADT/GEKID format. From this common basis we conceptualized and implemented a transformation which accepts ADT/GEKID XML files and returns FHIR resources. We identified several problems with using the general ADT/GEKID structure in federated research infrastructures, as well as some possible pitfalls relating to the FHIR need for resource ids and focus on semantic coding which differs from the approach in the ADT/GEKID standard. To facilitate participation in federated infrastructures, we propose the ADT2FHIR transformation tool for partners with oncological data in the ADT/GEKID format.