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DKG

2020. 09. 23.-2024. 09. 22.

The Distributed Knowledge Graphs (DKG) EU COST project, started in the fall of 2020 aims at creating knowledge graph technologies that are standard-based, meet the FAIR principles, open, maintain data privacy and enable decentralized publication of high quality data.

CONCORDA

2020

The goal of the project is to establish a Hungarian research data repository supporting the COVID-19 pandemic related research initiatives.  The research data repository serves as a data store and repository solution both for international and national uses, and provides a definite (peer-to-peer) controlled reliable data sharing platform.

MTMT2

2014-2018

The Hungarian Scientific Bibliography (MTMT) is a comprehensive national bibliographic database of scientific publications and citations. Since 1999 MTMT collects data from researchers and institutions, and serves more than 30 thousand users. Furthermore, MTMT also provides national and educational institutions with scientific statistical data. The quality of the bibliographic records and the management of institutional data are supervised by a country-wide network of MTMT administrators. The Department of Distributed Systems at MTA SZTAKI (Institute for Computer Science and Control, Hungarian Academy of Sciences) has developed the new version called MTMT2.

W3C-HU

2002-2020

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.

DSD opened the Hungarian Office of the World Wide Web Consortium at 1st September, 2002. W3C-Hu promotes the activities of W3C in the region.

ARP

2021. 11. 01.-2023. 04. 30.

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.

DBK

2021. 07. 01.-2022. 07. 01.

The dhupla platform of the Centre for Digital Humanities (DBK) serves the critical processing and publishing of Hungarian literature. The processing format of works is based on TEI XML. In order to support editors in their work, we develop a plugin for Oxygen XML Editor by the suggestions of DBK. The editing framework provides a readers’ view (without XML tags), context menu for the input of new XML tags and forms for metadata input. Editors can also check the correctness of XML using schematron validation.

DIWAS

2019. 08. 01.

The goal of the DIWAS project is to implement a cloud service, which can be used in an Industry 4.0 setup to provide production line workers with suitable assembly instructions.

MILAB

2021. 03. 01.-2022. 03. 01.

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.

iToBoS

2021. 04. 01.-2025. 24. 01.

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.