HubScience is an innovative knowledge discovery platform designed for the life sciences and healthcare sectors, to process and analyze vast amounts of scientific text from multiple sources. It enables researchers to efficiently extract, organize, and understand complex data for faster and more insightful research outcomes. Our platform transforms unstructured text into structured data, revealing connections between texts and generating new hypotheses that might be overlooked through manual processing. HubScience uses advanced technologies and offers a user-friendly interface, enabling researchers to conduct comprehensive literature reviews and gain deeper insights into their research questions within a relevant context. HubScience is built on a robust scientific foundation combining several advanced technologies tailored for the complexities of scientific language. We have developed a proprietary natural language processing (NLP) system specifically for scientific texts, utilizing named-entity recognition (NER) and matching algorithms to accurately identify and extract quantitative and qualitative data, including parameters like active substances, measurement units, and biological experiment results. In addition, we employ ontology-based knowledge graph technology to create structured representations of data, facilitating deeper insights and the mapping of complex relationships within the literature. For hypothesis generation, we leverage Literature-Based Discovery (LBD), enabling researchers to uncover novel connections and generate new insights from existing scientific knowledge. This integrated approach ensures precision, depth, and a comprehensive understanding of scientific data.

Sustainable nutrition is a complex, holistic concept that encompasses various dimensions, including economic, socio-cultural, and environmental considerations. In environmental assessments of food products and diets, the integration of nutrition and health aspects is essential. The aim of our research project is to develop suitable and simple scoring systems to characterize the healthiness and sustainability of the current Hungarian dietary pattern. Another objective is to apply system dynamics simulation models—based on Hungarian and international data—to evaluate the macroeconomic consequences of shifting dietary patterns toward more sustainable nutrition. As part of the project, we will use advanced bibliometric methods to analyze the current scientific literature and uncover hidden relationships in the fields of sustainability, food science, and health. To assess the macroeconomic impacts of dietary transitions, we will employ system dynamics modeling, a method well-suited for exploring the complexities of building a sustainable food system. The findings of the research will support decision-making related to the revision of national food-based dietary guidelines and the development of a more sustainable food chain, ultimately contributing to the reduction of the environmental burden of the food system. The research is carried out within the framework of project no. FK 147390, with the support of the National Research, Development and Innovation Fund of the Ministry of Culture and Innovation, financed under the FK_23 “OTKA” Young Researcher Excellence Programme.

In general, the presence and performance of women in science have increased significantly in recent decades. However, gender-related differences persist and remain a global phenomenon. Women make a greater contribution to multidisciplinary research, which renders anti-doping science (ADS) a compelling area for investigating the gendered aspects of academic research. This project aims to investigate the gender-related trends in anti-doping sciences by exploring the relational structure of gender aspects of authorial, topical, and methodological features, and give recognition to women’s contribution to anti-doping research. In addition, the goal of the project was to reveal whether gender in a specific field (ADS) has an effect on different aspects of research impact, including (1) the size of citation impact obtained by the research output, (2) the impact on the development of the knowledge base of ADS, expressed as the capacity of integrating knowledge from different research areas, and (3) the (expected) type of research impact targeting either societal or scientific developments (or both). The data source used for the research is the Web of Science databases, altogether 1341 anti-doping-related publication were included in the analyses.

The highly complex issue of the COVID-19 epidemic is being studied by thousands of researchers around the world, who publish their research in qualified publications. The amount of professional and scientific information on coronavirus diseases is growing week by week, but much of the available knowledge is latent and fragmented. The ever-increasing amount of scientific knowledge poses fundamental information management challenges to the professional community. The COVID knowledge map and knowledge base platform have been set up to support the scientific and expert work needed to control the epidemic. The portal presents a systematic mapping and structuring of the multidisciplinary knowledge base related to the COVID-19 epidemic, as well as exploring the internal organization of this global knowledge asset. As a first step in the project, we collected published research results on COVID using specialized search strategies, relying on the constantly updated real-time Web of Science, Scopus, and PubMed databases. Subsequently, we carried out a bibliometric analysis, as a result of which it is possible to find out which countries, which scientific community play a decisive role in generating the results achieved in different fields, the connection, how efficiently they search and find answers in different parts of the world. As a result of bibliometric mapping methods, the best and most effective practices related to COVID will become known, the defining research directions of each topic will be identified, and the most successful research communities and researchers will be identified. The platform demonstrates the organization of scientific knowledge related to COVID and how the literature base that can be linked to the pandemic as broadly as possible is being built. The knowledge map created as a result of the project combining bibliometric expertise and software engineering knowledge can be viewed on the public web application www.covidscimap.org. As part of the project, it will be possible to review and synthesize international best practices in COVID-related communication, healthcare logistics and patient care systems, and to make decision-making proposals. The first phase of the research intelligence system was implemented in cooperation with the voluntary academy of industry, Pro-Sharp Hungary Kft. And the Department of Science Analysis and Science Policy of the Library and Information Center of the Hungarian Academy of Sciences.

• Background:
  “Values in sport” is a theme of dual nature: on one hand, it is interpreted in the sport science community in a specific manner, as being related to the concepts of integrity and clean sport. On the other hand, it is a vaguely defined notion with broad disciplinary background, the latter involving psychology, philosophy and many other fields. However, seeking for codification of the content and professional foundations of this concept requires filling the gap between the narrow and the vague interpretation. This codification is unavoidable for policy makers, managers and other actors in the international arena of sport to support their organization activities.
• Research goals:
  The main goal of the proposed research is to explore and uncover the scholarly discourse on “values in sport”, addressing the thematic and disciplinary complexities involved in the topic. The detailed objectives are (1) to identify the relevant corpus, including latent contributions to the topic as well, (2) to explore and map the internal thematic and institutional organization of the literature, and (3) to extract conceptual relationships (a concept map) that underlie the view on how sport value notions are being structured and connected.
• Method:
  Uncovering the organization of the literature is a matter of the study of how documents are being related, given their topics, methods, authors, etc. Bibliometric methods are highly suited to uncover the large-scale patterns of document relatedness, a methodological framework often referred to as science mapping. For the systematic exploration of the “values in sport” discourse at many levels of the publication output we apply state-of-the art methods from bibliometric science mapping and network analysis.
• Outcomes and outputs:
  Science mapping results are rendered into an on-line interactive knowledge map with various functionalities, such as (1) quick access to the organization of the knowledge base related to the scholarly discourse on values in sport (2) effective map-based navigation in the publication set and access to relevant publications, (3) showcasing the most important contexts and knowledge claims.