The aim of the project is to improve PID support into the Hungarian National Data Repository, known as ARP (https://researchdata.hu/en), which has been operational since March 2024. The ARP initiative is devoted to furnishing Hungarian researchers with a comprehensive and adaptable data repository service, capable of accommodating all research disciplines practiced in Hungary.
The aim of the project is to integrate RO-Crate support into the Dataverse repository system as a component of the Hungarian National Data Repository initiative, known as the ARP project. The ARP initiative is devoted to furnishing Hungarian researchers with a comprehensive and adaptable data repository service, capable of accommodating all research disciplines practiced in Hungary.
W3C, the World Wide Web Consortium was founded in October 1994 to lead the World Wide Web to its full potential by developing common protocols that promote its evolution and ensure its interoperability. W3C has more than 400 Member organizations from around the world and has earned international recognition for its contributions to the growth of the Web.
The aim of the ELKH Data Repository project is to establish the basis for a repository infrastructure service that supports the continuous, long-term management of research data for the whole ELKH research network. It will provide a solution for the secure, digital storage, usage and sharing of research data, as valuable data assets, for research and also, for example, the commercial sector.
The aim of the project is to provide Robert Bosch Ltd. with knowledge graph technologies, so that internal industrial or research contacts and information could be accessed, shared and used within the organisation. Ensuring data security and privacy as well as maintaining high quality of data are also in focus of the project.
The Research Documentation Centre (KDK) of the Centre for Social Sciences runs two archives of social science research, which preserve the primary research data for qualitative social science in Hungary. A need emerged to annotate and enrich interviews collected in these archives with assigned keywords, topics and recognised named entities (places, persons and organisations). KDK and SZTAKI launched a pilot project on using NLP and AI for automated text enrichment.
The aim of the iToBoS project is to train an AI system able to integrate information from different sources, assessment of individual moles while considering the specific characteristics of each patient. With systematic successive explorations of a patient, the system will be able to also robustly determine the changes occurring in the individual moles, a key feature held as one of the most informative in the detection of skin cancer. The proposed holistic approach will enable physicians to diagnose skin diseases earlier and with higher accuracy, thus increasing effectiveness and efficiency in personalized clinical decision making.
