Workflows

Workflows in the HUM Data Lab

Here you can find workflow descriptions by researchers in the HUM Data Lab that help make the research process more understandable, transparent, and reproducible. The workflows show step by step how a research question develops into data selection, analysis, and interpretation. In the future, these workflow descriptions, together with the code and tools needed to carry them out, will be available in a separate environment.

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It is also possible to publish your own workflow description in the HUM Data Lab. To do so, please use the workflow description form. All submitted workflows receive feedback from reviewers before publication.

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  • Literary Network of the National Awakening Based on the Correspondence of Koidula and Kreutzwald

    This workflow was created to analyse the correspondence between Friedrich Reinhold Kreutzwald and Lydia Koidula from the years 1867–1873 and to map which people appear most frequently in the literary network of the National Awakening on the basis of these letters. The correspondence is one of the most important sources in Estonian literary history, reflecting the development of the national movement, cultural contacts, and relationships between authors. The workflow makes it possible to automatically identify personal names in a text corpus, clean and standardise name forms, and...

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  • Past Lives in Estonian Cultural Data – Developing Interactive Exhibits with 19th Century Parish Court Records and Bibliographical Data

    The workflow addresses how 19th-century Estonian parish court records and bibliographical data can be transformed into interactive digital exhibits for the general public. Although these datasets contain rich historical and cultural elements, they are not immediately accessible to non-specialist audiences in their original structured forms. The workflow therefore explores how cultural heritage data can be cleaned, extracted, linked, and redesigned as interactive applications....

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  • Interactive map of Building Designs in Tartu

    This workflow was created during the HUM Hackathon and focuses on building an interactive map application based on the Tartu Building Designs database. The main purpose of this project was to visualise building projects in Tartu between 1870 and 1920. The workflow describes data processing and creating a map application.

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  • Analysis of the Distribution of Estonian Runo Songs Related to Grains

    We are working with the Estonian runosongs' database, which contains runosong texts and the metadata associated with them. The aim of the project is to study the geographical distribution of work songs containing references to cereals and to analyse which cereals are mentioned most frequently in different regions. Through the analysis, we aim to identify possible regional patterns and examine how and whether runosongs might reflect historical agriculture.

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  • Analysis of Tale Type 0567A in the Corpus of Seto Folk Tales

    This workflow describes the aim of analysing tale type 567(A), the tale of the magic bird, in a dataset of Seto folk tales, in order to understand how and to what extent the variants of this type differ from one another. Gretta Nikolajeva was responsible for the qualitative analysis, while Aleksander Amos Nigesen was responsible for data processing in R.

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  • Analysis of Regional and Temporal Patterns in Estonian Instrumental Folk Music

    This workflow enables the analysis of the regional and temporal distribution of instruments and instrumental tunes in a dataset of Estonian instrumental folk music. During the workflow, the metadata of the archival dataset are cleaned, instrument and place names are standardised, and broader analytical instrument categories are created as needed. The frequencies of instruments and folk tunes are then calculated by county and time period. The results are presented as frequency tables, diagrams, and maps, which help make visible patterns that would be difficult to detect by looking at individual records.

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  • Tunes of the World map: Exploring Estonian and Ukrainian Folk Song Heritage

    The project aims to create an interactive digital map for exploring Estonian and Ukrainian folk-song traditions through geographical, thematic, emotional, and structural perspectives. Developed during the HUM Hackathon 2026. The current prototype focuses primarily on Ukrainian folk-song materials, while future versions will integrate Estonian datasets and enable cross-cultural comparison. The workflow combines digital humanities methods, natural language processing, cultural heritage data management, and interactive visualisation. Two large folk-song corpora 85,550 Estonian songs and 56,726 Ukrainian songs were prepared, harmonised, analysed, and transformed into a searchable map interface. Users can navigate from ethnographic regions to individual singers and complete song texts, explore emotional and thematic patterns, and investigate the geographical distribution of oral traditions.

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  • Spatial and Temporal Patterns of the Photograph Collection of the EFA

    The aim of this workflow is to study the spatial and temporal patterns of the photograph collection of the Estonian Folklore Archives (EFA) and to make a large and difficult-to-grasp dataset easier to explore through an interactive visualisation tool. The project focuses on the first 10,000 black-and-white photographs from the EFA photograph collection, which contains approximately 88,000 photographs in total, together with their metadata. On the basis of this material, the distribution of photographs is analysed across time, space, keywords, collection projects, persons, and photographers.

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  • Large-scale study of attention change trends using ngrams

    The workflow enables the analysis of mention frequencies across different categories over long time periods or with dense data, in order to reveal similarities and emerging patterns. Data is aggregated into matrices, which are used to createheatmapsthat allow large datasets to be presented visually in a clear and comparable manner. These visuals can be read both across time and across categories, enabling the comparison of different periods and topics, and combining intuitive qualitative visual analysis with quantitative methods.

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  • Use cases for working photos of material culture researchers

    This project investigates how working photographs collected by material culture researchers can be used to automatically identify objects and assess their condition, and how such a large collection can be published under FAIR principles in a user-friendly way. Researchers of material culture may take thousands of photos of objects within the scope of each research topic, but in most cases, the use of photos is limited to typological identification, visual comparison of finds, and...

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