Tampere University
Visit websiteAt 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.
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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.
Tools
Educational material
Information regarding educational materials relevant to the DARIAH-FI research infrastructure and guidance on which courses might be relevant to use its resources more efficiently. Also includes an overview of digital humanities and computational social sciences education in Finland.
Educational resource development
An updated report on the educational resource development in DARIAH-FI for the 2024–2025 funding period.
Guideline for collecting user experiences from workshops and training sessions
A guide for collecting user experience data from workshops and training sessions related to the resources developed by the FIN-CLARIAH consortium.
Recommender system for NLF data
Code for developing recommender systems to assist information retrieval in digital libraries based on log data gathered from their use. Developed by Tampere University in partnership with CSC and the University of Helsinki.
In collaboration with: CSC, University of Helsinki, National Library of Finland, University of Turku
User Experience Questionnaire
UX questionnaire developed within DARIAH-FI to test and evaluate tools, datasets or workflows developed for the project. Created and updated in several phases between 2022-2023 from a literature review, semi-structured interviews, and tests with end-users.
Trainings
The course examines the ongoing computational turn in social, political, and economic sciences.
The course introduces a number of current digital methodologies for different types of Humanities- and Social sciences research, suitable for PhD level research.
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.
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.
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.
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.