Tampere University
At Tampere University, the DARIAH local node is situated in the Faculty of Information Technology and Communication Sciences, where technology and the humanities come together in a unique way. Their research mission is to ensure socially responsible digitalisation and transformation of work. Particularly, the local node focuses on widening the user community of DARIAH, lowering the threshold of the RI and guaranteeing successful uses for researchers. This is done in collaboration with the rest of the DARIAH nodes. The local node is associated with the InfUSE group, internationally established as conducting high-quality research on task-based and interactive information retrieval.
Contact
Sanna Kumpulainen
Faculty of Information Technology and Communications
Affiliated Groups
InfUSE (Information interaction and use) is a group of multidisciplinary researchers in information interaction and use. The group studies all aspects of information searching, information use in various contexts, interactive information retrieval and information interaction. InfUSE is interested in how the current information environment and changes in it are augmenting human behavior and performance.
Expertise
Contact
DARIAH node
Tools
UX questionnaire developed within DARIAH-FI to test and evaluate tools, datasets or workflows developed for the project. The questionnaire was created and updated in several phases between 2022-2023 from a literature review, semi-structured interviews, and tests with end-users.
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Guideline for collecting user experiences from workshops and training sessions 
This document is intended to serve as an initial guide for collecting user experience data from workshops and training sessions related to the resources developed by the FIN-CLARIAH consortium.
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This document includes information regarding the educational materials relevant to the DARIAH-FI research infrastructure and guidance on which courses might be relevant to use its resources more efficiently. The document also includes an overview of the state of the digital humanities and computational social sciences education in Finland.
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Recommender system for NLF data
This resource provides code for developing recommender systems to assist information retrieval in digital libraries based on log data gathered from their use. The resource was developed by Tampere University in partnership with CSC and the University of Helsinki. Collaborators: National Library of Finland, University of Turku.
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Educational resource development
This document provides an updated report on the educational resource development in DARIAH-FI for the 2024–2025 funding period.
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Training and Teaching
Digital Libraries and Open Science
The course literature includes types and tasks of digital libraries, both in the non-profit and commercial sectors. Other topics of the course are open science, open data and data archives.
Bachelor’s level, Master’s level
Statistical Methods for Text Data Analysis
This course teaches various statistical methods for modeling and analysing text data. Contents are planned to include models for representing text including vector space models and neural embedding models; document content processing stages such as lemmatization and keyphrase extraction; probabilistic models of content variation including n-grams and topic models; neural models of text; and methods for various text analysis tasks.
Bachelor’s level, Master’s level
Information Search and Generation with Large Language Models 
Information retrieval, matching and generation, large language models, query construction and prompt engineering techniques, retrieval-augmented generation, collaborative topic creation and fine-tuning, evaluating information retrieval and generation.
Bachelor’s level; Master’s level
Fine-tuning Large Language Models (LLM)
This course provides a detailed exploration into the practical application, ethical considerations, and open-source landscape of fine-tuning large language models (LLMs) for students with basic programming skills.
Bachelor’s level; Master’s level
Digital humanities and social sciences
The course introduces a number of current digital methodologies for different types of Humanities- and Social sciences research, suitable for PhD level research.
Doctoral level
Computational Methods in Research on Social, Political, and Economic Issues
The course examines the ongoing computational turn in social, political, and economic sciences.
Doctoral level