Skip to main content

Data management

Data Management is a set of practices and techniques used by researchers to ensure that their data is organised, structured and easily reusable for future research

Resources

  • FAIR Data in SSH Training

    EN
    This training event from the TRIPLE Project was devoted specifically to FAIR Data in SSH and provided answers to the following questions, among others: How is research data defined in SSH; Why are FAIR principles important for the management of research data in SSH; How can FAIR principles be implemented in SSH.
    Authors
    • Elena Giglia
    • Arnaud Gingold
    • Iraklis Katsaloulis
    Read more
  • Research Data Management Bootcamp

    EN
    The SSHOC-DARIAH Train-the-Trainer Research Data Management Bootcamp ('Research Data Management Bootcamp' for short) took place over two half-day workshops that gave access to experts in the field and allowed for real-time activities between the sessions. It was co-organised by the SSHOC project and the DARIAH 'Research Data Management' Working Group.
    Authors
    • Joy Davidson
    • Kerstin Helbig
    • Annalisa Montesanti
    Read more
  • Data Protection in Research Practice

    EN
    Since May 2018, the GDPR (General Data Protection Regulation) has been in force in all European member states. This affects not only the private sector, but also the academic one. With this tutorial, we would like to introduce you to the most important terms and concepts of the GDPR and also to the ELDAH Consent Form Wizard, a tool that allows you to easily create GDPR-compliant consent forms for personal data collection in a research context.
  • CARE Principles in DH

    EN
    Prof. Dan O'Donnell (University of Lethbridge) discusses the CARE principles, how they sit alongside the FAIR Principles, and how (digital) humanists can apply them in their research. He presents examples from his own research, particularly around studies of historical artefacts in small rural communities in Scotland.
  • Open Research Europe Training

    EN
    This training event from the TRIPLE Project was devoted specifically to the Open Access publishing platform Open Research Europe (ORE) and provided technical details on how ORE works and what benefits it has for researchers.
  • MaDiH: Research Software Engineering Training

    EN
    Hosted by King’s Digital Lab (KDL) at King’s College London, the workshop introduced participants to best practices in project management, the Agile Dynamic System Development Methods (DSDM) as well as various theoretical and practical approaches to digital cultural heritage.
  • Transformations: What are the Big Challenges and Opportunities for Data-intensive Research?

    EN
    What are the big challenges and opportunities for data-intensive research over the next ten years? This panel discusses digital transformations in the humanities and arts, data ethics and sovereignty, and infrastructure with impact. It features presentations by Dr James Rose (Indigenous Studies Unit, Melbourne School of Population and Global Health) on Data Sovereignty in a Colonial Context: Towards an Integrated National Governance Framework for Australia, Dr James Smithies (Director, King’s Digital Lab) on Integrating DH into the longue durée: Research Laboratories, History, Methods.
  • What Are We Talking about When We Talk about Data in the Humanities?

    EN
    Data as a term is too flat an ontology for the kinds of things that we are all dealing with, argues Sally Wyatt in this keynote lecture. It reduces people, events, objects to things, bits, to be imagined as impersonal, scientific and neutral. Also, she contends, the use of the word 'data' tends to assume that everything is digital. In this keynote, she explains her argument that this is wrong and asks: 'what are we talking about when we talk about data in the humanities?'
  • What Does Data Want?

    EN
    Many academic disciplines use data science to analyze contemporary culture. The question posed by Lev Manovich in this lecture is: shall we continue to aggregate big cultural data and reduce it to a small set of patterns? Or shall we refuse this dominant paradigm instead and focus on diversity, variability and differences (including tiny ones), i.e., work on big cultural data without aggregation and with attention to what is infrequent and outliers?
  • Applying Modern Data Analytics to Classical Questions in the Humanities

    EN
    Mikko Tolonen was the first keynote speaker at the DARIAH Annual Event 2016. His talk was entitled 'Applying modern data analytics to classical questions in the humanities: a perspective from Finland'. It drew attention to the benefits of interdisciplinarity and effective communication between 'centred' disciplines for research in the digital humanities