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Built in 2013 at the Warsaw University of Technology, OMEGA-PSIR is the first non-commercial system that integrates the functionality of the Current Research Information System (CRIS, sometimes referred to as RIMS), the Open Institutional Repository (OIR) and the Researcher Profiling System (RPS). As such, the system becomes the research knowledge base for the university community, playing many important roles in the university's IT ecosystem - the most important of which are:

• being an important tool for the university authorities, responisble for strategic plannng of research development;

• serving the university research community as an information source and networking platform;

• building image of the university by showing research activities and the outcomes.

Now it is used by more than 40 univertsities. Its core component is the institutional open access repository collecting not only traditional documents like publications, patents, theses, reports, but also other research outputs, in particular research data.

As CRIS it also stores all necessary data about projects - starting with information about competitions and awards, project applications, and ending with projects that just sarthave started, are run runing or are have been completed.

As RPS the system stores profiles of researchers, university units, laboratories and research teams.

Having all kinds of data makes the system very attractive, not only because of reducing the maintenace cost for the IT systems, but also making it easier to link various types of data, like e.g. projects with outcome of the project, such as publications, patents or research data. All this gives a better view of research activities at the university, and additionally makes the system an important tool in scientific research management.

The basic features of the system are:

• its flexible data model, making it very easy to change the data structures or add new object types;

• easiness in defining various dictionaries, making possible to expand the system ontology by specific dictionaries, including taxonomies, which have additional feature of inheriting attributes;

  • a good example is incorporating the MeSH thesaurus as a tool for indexing medical objects (documents, projects, activities, etc), and then thesaurus-based information retrieval (which in this case becomes language symetricsymmetric);

  • another good example of using dictionaries is a possibility to define variety of persisten identifiers (e.g. , which can then be used to provide the ID value for the given ID type, so the dictionary may contain the values like ORCID, RoR), as well as proprietary identifies (Scopus ids, WoS ids), SCOPUS, WoS, SNN, for which identifiers can be assigned to the object.

  • one can also define dictionary of Linked Open Data sources and use them to enrich the LOD representation of data;

• compliance with international standards and good practices, such as, inter alia:

  • Open Access repositories (OAI-PMH, Dublin Core, CERIF format)

  • compliance with ORCID (seehttps://info.orcid.org/vendors-and-service-providers/orcid-certified-service-providers-list/ )

  • compliance with OPENAIRE guidelines - OMEGA-PSIR was one of the first CRIS system communicating with OPENAIRE (see https://dspacecris.eurocris.org/handle/11366/660)

  • COAR princiles for next generation repositories

  • FAIR recommendations

  • DataCite recommendations.

The idea of integrating CRIS, OIR and RPS makes it possible that once entred data and/or deposited object (publication, research data, multimedia) can serve various purposes, inter alia:

• giving rise to high visiblity of the university research results on the web, which in turn influences the University image

• providing tools to the university authorities for the purposes of research management;

• as a side effect, one can use the gathered data to report to the national authorities

All the object types are linked to each other, building an ontology representing knowledge on the university research activities and outputs. Once the reserchers profiles are defined, adding the research activity results to the database automaticaly updates the profile of the researcher, as well as the profiles of the researcher affiliation unit along with all the units that are higher in the university structure hierarchy.