Publish your Data! Preparing and modelling historical research material to make it available and reusable for others

General Information
Formal Information
Subject Matter Classification
Assessment
Addressed Students
Prior Knowledge
Learning Outcomes and Competencies
Didactic concept
Learning/teaching methods

General Information

Contact information of the lecturer

Philipp Schneider (philipp.schneider.1@hu-berlin.de)

Office Hours

General Consultation: max. 30 min (Book an appointment)
Code Consultation for support with concrete assignments: 45 min (Book an appointment)
Email

Participating Institutions

Professorship for Digital History

Resources for the Course

Moodle Course

Formal Information

Publish your Data! Preparing and modelling historical research material to make it available and reusalbe for others – 51350
Excercise
Thursday: 12:00-14:00
In-Person (with the possibility of hybrid teaching in exceptional cases)
Place: Dorotheenstraße 26, Room 117 (Flexpool)
Start Date: October 23th 2025

Course Description

Historical research increasingly generates substantial data – from transcriptions and Excel sheets to databases and machine learning models. Yet this data often remains forgotten on hard drives after publication, despite representing valuable scholarly work. Publishing research data not only makes our efforts visible but enables other researchers to comprehend, reproduce, and directly reuse our work – much like sharing a transcription or translation with a colleague.

But how do we publish data so it’s actually reusable for others and not just dumped somewhere on the internet? And how do we make it work as historical data, dealing with ambiguity, incompleteness, and historicity?

This hands-on course teaches students to model and transform their research materials into well-documented, standards-compliant datasets ready for publication. We cover the complete workflow: FAIR principles, legal considerations, reusing and applying ontologies (particularly CIDOC-CRM), mapping to cultural heritage standards, and selecting publication platforms. Each session combines theory with practical exercises using real historical datasets.

Although by no means mandatory, students are encouraged to work with their own research data, making this an ideal opportunity for structured support in preparing research materials for publication. No technical experience required, as necessary skills are built progressively throughout the semester. The course culminates in a practical project contributing to the growing landscape of open historical research data.

The syllabus of the course can be found at: https://hu.berlin/wise2026-syllabus-publish-your-data

Literature:

Cremer, Fabian, Silvia Daniel, Marina Lemaire, Katrin Moeller, Matthias Razum, and Arnošt Štanzel. ‘Data Meets History: A Research Data Management Strategy for the Historically Oriented Humanities’. In Band 21 Cultural Sovereignty beyond the Modern State: Space, Objects, and Media, edited by Gregor Feindt, Bernhard Gissibl, and Johannes Paulmann, 1st ed., 155–78. Berlin, Boston: De Gruyter Oldenbourg, 2021. https://doi.org/10.1515/9783110679151-009.
Baca, Murtha, ed. Introduction to Metadata. Los Angeles, 2016. http://www.getty.edu/publications/intrometadata.

Scheduled Sessions

16 Sessions á 1,5 hrs.
Attendance time: 25 hours
Self-study time: 65 hours for the preparation and follow-up of the course and the special assignment
Total: 90 hours

(acccording to module description M-02 Methodik und Theorie)

Working Language

English

Subject Matter Classification

Subject Matter

Hands-on learning how to structure and publish historical research data and how to reuse existing models in the form of ontologies by considering modelling implications, inherent to historical studies.

According to module description M-19 Geschichte als Praxis

Praktisch ausgerichtete Übung und Exkursion zu möglichen Berufsfeldern

Erkundung möglicher Berufsfelder oder praktische Tätigkeiten einer Historikerin bzw. eines Historikers im Rahmen des Studiums. z.B. EDV-Erfahrungen, Kommunikations- und Medienkompetenzen, Präsentationstechniken, Moderationstechniken und weitere Anwendungsmöglichkeiten historischer Theorien, Methoden und Techniken

English version

Practical exercise and excursion to possible occupational fields

Exploration of possible professional fields or practical activities of a historian as part of the degree programme. e.g. IT experience, communication and media skills, presentation techniques, moderation techniques and other possible applications of historical theories, methods and techniques

Curriculum integration

See Structure Tree in AGNES

Assessment

According to Appendix 2 of the study and examination regulations, the following options to gain creadit points are possible:

Term papers (approx. 10 pages/25,000 characters including spaces; depending on the respective study and examination regulations)
Presentations
Term paper: Document the preparation of a research dataset for publication (5 CP)
Term paper or presentation: Preperation, documentation, and discussion of a research dataset for publication and structuring it by reusing an existing ontology (10 CP)
Term paper or presentation: Presentation of a model and discussion of its applicability for an area of historical research (5-10 CP)

ECTS

2-3 CP

Course requirements (ungraded)

The points for the academic credit are calculated as follows:

1 CP for participation

Handing in all homework assignments

+ 1 CP (overall 2 CP):

Prepare a historical research dataset for publication (fully or partly, depending on its size and extent) and document the process in a term paper.
- Extend according to the study and examination regulations (example: module Methodik und Theorie): ca. 12,500 characters
OR Term paper or presentation of a model, including a discussion of its applicability for an area of historical research

+ 2 CP (overall 3 CP):

Prepare a historical research dataset for publication (fully or partly, depending on its size and extent) AND structure it by reusing an existing ontology or data model. Document and discuss the process in a term paper.
- Extend according to the study and examination regulations (example: module Methodik und Theorie): ca. 25,500 characters
OR Term paper or presentation of a model, including a discussion of its applicability for an area of historical research
The usual requirements for academic work apply, also with regard to spelling, bibliography, and references.

Module completion exam (Modulabschlussprüfung) (graded)

For a module completion examination (Modulabschlussprüfung) with 2 CP e.g. in the modules Methodik und Theorie or Geschichte als Praxis, the following achievement must be fulfilled in addition to the ungraded coursework:

Prepare a historical research dataset for publication (fully or partly, depending on its size and extent) AND structure it by reusing an existing ontology or data model. Document and discuss the process in a term paper.
- Extend according to the study and examination regulations (example: module Methodik und Theorie): ca. 25,500 characters

The usual requirements for academic work apply, also with regard to spelling, bibliography, and references.

Example for combining an ungraded requirement with a MAP: Discuss and reflect upon the usability of an ontology in your field of research in a presentation or term paper. For the MAP, reuse this ontology to prepare your own dataset for publication.

Addressed Students

Master students who work with historical material and are interested in publishing their research material or results as data in a reusable way.

Prior Knowledge

Aside from an undergraduate level of knowledge on historical source criticism, no prior knowledge is required to complete the course successfully, although an existing understanding comprehension on historical research data is helpful.

Heterogenity of the addressed students

Different levels of knowledge in the area of data literacy are to be expected.
Different levels of familiarity with computers are to be expected.
Different levels of familiarity with the goals and research paradigms of Digital History and Digital Humanities are to be expected.
In the area of learning preferences, it can be assumed that there will be different types of learners. In addition, different learning media may be favoured: Text/textbook, learning videos/tutorials, classroom discussion.

Number of Learners

between 15 and 25

Learning Outcomes and Competencies

What learning outcomes are intended with the learning programme?
Which specific competences should learners develop at which level as part of the learning offer?

Learning Outcomes

This course introduces students to the fundamental principles of publishing historical research data in a reusable and sustainable manner. Students will learn to evaluate and apply existing data models and ontologies to structure historical research data, gaining hands-on experience with linked data technologies. The course covers the research data lifecycle from collection to publication, developing competencies in assessing ontologies for historical datasets, understanding model reuse and entailment, and making informed decisions about publication strategies and repository selection. Through practical exercises, students will gain the skills necessary to transform their historical research into structured, interoperable data that contributes to the broader scholarly community.

Learning Goals:

Overall learning goal: Learn how to publish historical research data in a reusable way by reusing existing models and ontologies to structure them

The students are able to:

Know and comprehend the implications of data culture for historical studies
Apply the research data life cycle on their own projects
Comprehend the basics of structuring data with RDF
Evaluate ontologies for their suitability to structure a specific set of historical research data
Apply ontology and model reuse for historical research data
Know and comprehend consequences of model reuse and entailment for historical research data
Know how to choose the right publication strategy, license, and repository for research data publication

Learning objectives and competency levels

Professional Competencies

Familiarity with the basics of research data management in the context of the historical humanities
Select suitable repositories and licenses for research data publication
Select and evaluate ontologies and other existing data models for reuse to structure a specific historical data set
Prepare historical research datasets for publication

Social Competencies

Collaboration and exchange when doing course assignments
Collaborate in an international EMI setting

Didactic concept

Learning/teaching methods

Project work
Class discussion with presentations
Hands-on modelling work in person
Group work phases
Individual work phases
Literature Review

Syllabus