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Graphentechnologien in den digitalen Geisteswissenschaften
Graphentechnologien in den digitalen Geisteswissenschaften
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Description

This book, which is being developed as an open book project on GitHub Pages, provides an introduction to graph technologies for researchers in the humanities. As it provides step-by-step instructions on data import, modelling and analysis of humanities research data in graphs with Neo4j, therefore it has been included as teaching material in the Educational Resource Finder.

Details

Digital Text Editing with TEI
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Digital Text Editing with TEIThe tutorial 'Digital Text Editing with TEI' consists of a series of chapters that build on each other to introduce the coding and editing of texts according to the guidelines of the Text Encoding Initiative (TEI). The tutorial is designed for use in teaching, but can also be used for self-study. It is therefore not tailored to a specific user group, but is suitable for anyone who wants to edit digital text using TEI. TEI itself, i. e. the free accessibility and use of the coding, as well as the recommendation of freely accessible repositories, correspond at least in part to the FAIR principles. The tutorial is a technical training in TEI and does not contain instructions or recommendations concerning RDM.
File Format
Unknown
Languages
German
Publication Date
2014-06-01
License
CCBY
Authors
Keywords
#metadata#editing#teaching#text
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Research Data Management - an Online Introduction (HeFDI Data Learning Materials)
6
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Research Data Management - an Online Introduction (HeFDI Data Learning Materials)The self-study course is characterised by a clear structuring of nine blocks (Introduction to FDM; The Life Cycle of Research Data; DMP; Metadata and Metadata Standards; FAIR and CARE Principles; Data Quality; Data Organisation; Data Storage and Archiving; Law). The individual chapters contain different media (text, image and video files), tasks and are designed to build on each other thematically. The contents are supported by examples from different disciplines with literature references and links to further platforms and sources (e.g. DFG) and the learning objectives are successively recorded.
File Format
Unknown
Languages
German
Publication Date
2022-03-01
License
CCBYSA
Authors
Keywords
#metadata#research data management#data life cycle#data management plan#organizing#dataquality#authority data#care principles#fair#longterm preservation#preserving
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Open Science Advanced Course
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Open Science Advanced CourseThis course is based on the "Basic Course" offer of the KIM Open Science Center of the University of Konstanz. It offers a collection of seven modules aiming at research and training related aspects around Open Science, like Policies and Strategies, Research Data Management and perspectives across ERUA countries and Planning Data Management, Models and Publishing, Citizen Science, Legal Aspects and Alternative Measures of Research Impact in the context of Open Science and Open Educational Resources.
File Format
Unknown
Languages
English
Publication Date
2023-08-23
License
CCBY
Authors
Keywords
#research data management#data management plan#organizing#dataquality#academic publishing#digital publishing#publishing#storing
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KIM Open Science: Von Daten zu Publikationen
4
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KIM Open Science: Von Daten zu PublikationenThe "Open Science: From Data to Publications" online self-study course offers a clear overview of selected topics. Since the focus is on "Open Science", no claim is made to offer a comprehensive overview of Research Data Management. The videos and specific content from different input providers are presented in a structured and clear way.
File Format
Unknown
Languages
German
Publication Date
2020-09-08
License
CCBY
Authors
Keywords
#research data management#academic publishing#digital publishing#publishing
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RDMLA – Research Data Management Librarian Academy
9
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RDMLA – Research Data Management Librarian AcademyThe Research Data Management Librarian Academy (RDMLA) is a free online training program for librarians, information professionals and other professionals working in a data-intensive environment worldwide. Within this framework, a wide range of different topics and content is offered, consisting of eight asynchronous self-paced learning units: introduction to RDM, research data lifecycle and “research culture and ecosystem”, stakeholders, project management, data visualization tools such as R and Tableau, introduction to data analysis, programming skills in Python and Jupyter Notebook, copyright, licensing and privacy issues, and curation and archiving of data. Each unit includes several components of the following three features: On an informational level, learning objectives are taught and provided in the form of video lectures, presentation slides and reading material. Case studies and interactive formats can be used to supplement the content. And after each learning unit, discussion questions and quizzes on the concept can be used as assessment methods.
File Format
Unknown
Languages
English
Publication Date
2019-10-01
License
CCBYNCSA
Authors
No Authors
Keywords
#research data management#data life cycle#data management plan#organizing#analyzing#archiving#copyright#data curation#data visualization#license#programming#project management#python#r#repository#visualization
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Knowledge Graphs Course
6
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Knowledge Graphs CourseThe course provides an introduction to the topic of knowledge graphs. The basics of graph theory and the semantic web are covered. Knowledge representation through ontologies with OWL (Web Ontology Language) and queries with SPARQL are discussed. As the course follows a modular structure, it can be started according to the individual level of knowledge and can also be cancelled at certain points according to individual learning goals.
File Format
Unknown
Languages
German
Publication Date
2020-12-15
License
CCBYNCSA
Authors
Keywords
#dataquality#artificial intelligence#conceptualizing#data ingestion#data modeling#integrating#knowledge extraction#modeling#natural language processing#relational analysis#semantification
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