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Vyacheslav Tykhonov

Publications and source records attributed to Vyacheslav Tykhonov.

3 recordsLinked to original sources

Co-creation of AI technology, empowering curators of cultural heritage information and guarding research commons

The substance of this paper is the description of the use of Retrieval-Augmented Generation (RAG) for specific digital collections of cultural assets. The collections are provided by institutions operating in the cultural sector. The topical areas are the humanities and social sciences. More concretely, most of the work presented here was enabled by a European-funded research project MuseIT which is clearly situated in the realm of fostering new technologies for Cultural Heritage. We adhere to this interaction by presenting a sequence of our experimentations. This sequence is narrated as a specific journey of engineering all executed around a specific data-sharing and archiving platform Dataverse. Implementing a local chatbot for collections - a method also known as RAG in Information Retrieval - is the current culmination of this journey. The engineering journey we describe in the core of the paper starts from "archives for everyone" and ends with "local chatbots for specific collections".

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Chatting with Papers: A Hybrid Approach Using LLMs and Knowledge Graphs

This demo paper reports on a new workflow \textit{GhostWriter} that combines the use of Large Language Models and Knowledge Graphs (semantic artifacts) to support navigation through collections. Situated in the research area of Retrieval Augmented Generation, this specific workflow represents the creation of local and adaptable chatbots. Based on the tool-suite \textit{EverythingData} at the backend, \textit{GhostWriter} provides an interface that enables querying and ``chatting'' with a collection. Applied iteratively, the workflow supports the information needs of researchers when interacting with a collection of papers, whether it be to gain an overview, to learn more about a specific concept and its context, and helps the researcher ultimately to refine their research question in a controlled way. We demonstrate the workflow for a collection of articles from the \textit{method data analysis} journal published by GESIS -- Leibniz-Institute for the Social Sciences. We also point to further application areas.

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A Knowledge Base for Arts and Inclusion -- The Dataverse data archival platform as a knowledge base management system enabling multimodal accessibility

Creating an inclusive art environment requires engaging multiple senses for a fully immersive experience. Culture is inherently synesthetic, enriched by all senses within a shared time and space. In an optimal synesthetic setting, people of all abilities can connect meaningfully; when one sense is compromised, other channels can be enhanced to compensate. This is the power of multimodality. Digital technology is increasingly able to capture aspects of multimodality. To document multimodality aspects of cultural practices and products for the long-term remains a challenge. Many artistic products from the performing arts tend to be multimodal, and are often immersive, so only a multimodal repository can offer a platform for this work. To our knowledge there is no single, comprehensive repository with a knowledge base to serve arts and disability. By knowledge base, we mean classifications, taxonomies, or ontologies (in short, knowledge organisation systems). This paper presents innovative ways to develop a knowledge base which capture multimodal features of archived representations of cultural assets, but also indicate various forms how to interact with them including machine-readable description. We will demonstrate how back-end and front-end applications, in a combined effort, can support accessible archiving and data management for complex digital objects born out of artistic practices and make them available for wider audiences.

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