Building an AI-CRIS Platform: Multilingual, Contextual, and Predictive Research Data Access

15 pages•Published: October 19, 2026

Ecenaz Usta, Tugkan Tuglular, Gultekin Gurdal, Ahmet Şemsettin Özdemirden and Otmane Azeroual

Abstract

Current Research Information Systems (CRIS) have become essential tools for universities and research institutions to manage, analyze and disseminate information about research activities, outputs and collaborations. However, traditional CRIS platforms often operate retrospectively and rely on manual data retrieval, limiting their ability to provide dynamic, context-aware and predictive insights. Addressing these challenges, this study presents the development of an AI-enhanced Current Research Information System (AI-CRIS), named GCRIS AI, implemented for the İzmir Institute of Technology. The GCRIS AI module introduces a novel approach to research information management by integrating artificial intelligence capabilities directly into the CRIS environment. Its primary component is a multilingual chatbot, which serves as an intelligent assistant for researchers, administrators and institutional leadership. The chatbot leverages natural language processing (NLP) and semantic understanding to interpret user queries, retrieve relevant information from the institutional GCRIS database enriched with external sources such as ORCID and Scopus and provide precise, contextual and actionable responses. By providing multilingual, contextual and predictive access to research data, the platform enhances the efficiency, transparency and strategic value of CRIS infrastructures. The pilot demonstrates that AI-enhanced CRIS platforms can bridge the gap between complex data infrastructures and end-user needs, fostering adoption and satisfaction among diverse stakeholders.

Keyphrases: artificial intelligence (ai), data driven decision support, multilingual chatbot, predictive analytics

In: Pablo de Castro and Joachim Schöpfel (editors). Proceedings of 17th International Conference on Current Research Information Systems, vol 5, pages 118-132.

Links:	https://easychair.org/publications/paper/pD37
	https://doi.org/10.29007/mmq8

BibTeX entry

@inproceedings{CRIS2026:Building_AI_CRIS_Platform,
  author    = {Ecenaz Usta and Tugkan Tuglular and Gultekin Gurdal and Ahmet Şemsettin Özdemirden and Otmane Azeroual},
  title     = {Building an AI-CRIS Platform: Multilingual, Contextual, and Predictive Research Data Access},
  booktitle = {Proceedings of 17th International Conference on Current Research Information Systems},
  editor    = {Pablo de Castro and Joachim Schöpfel},
  series    = {EPiC Series in Technology},
  volume    = {5},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2322},
  url       = {/publications/paper/pD37},
  doi       = {10.29007/mmq8},
  pages     = {118-132},
  year      = {2026}}

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