| Full name: | Hungarian Scientific Bibliography 2.0 development |
| Start date: | 2014. 01. 07. |
| End date: | 2018. 01. 11. |
| Participants: |
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| Project homepage: | http://m2.mtmt.hu/gui2/ |
| Coordinator: | András Micsik |
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.
MTMT2 is a modern API-based platform, with a backend, an editors' frontend and a public frontend. The backend provides a usual REST API with JSON, XML or HTML output, and uses ORM for database storage. There are more than 200 object types handled by the backend.
The public frontend or public GUI is dedicated for the dissemination of Hungarian scientific publishing activity. One can browse and search publications by author, institute or topic. Open access publications can be read with a single click. There are also charts showing simple statistics for authors and institutes.
MTMT2 is an extensible system: new clients can be built using its API, and it also supports OAI-PMH and Sword protocols. Users can fetch their publication metadata directly using a DOI, a Web of Science id or a PubMed id. They can also import their citation metadata as a RIS file. The system supports various widgets of author/institute data and publication lists for embedding into other web pages, and various reporting facilities in PDF, ODT, CSV, etc. formats.
The editors' frontend is a web app built with Sencha ExtJS supporting the daily tasks of managing publication, author and institute data with the feeling of a desktop app. The frontend can run multiple importing and reporting tasks in the background while the user can continue her/his work.
