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
This is a record of a webinar dedicated to the phase of the research life cycle “Plan Research Project”. It first introduces the participants to an understanding of the advantages and practicalities of research collaboration in and with Research infrastructures. It then dives into details of project planning, touches upon the basics of the FAIR principles, and focuses especially on the importance of using standards in Digital Humanities and Cultural Heritage research and how to identify relevant standards for the participants’ own research. This webinar gives an introduction to the Standards Survival Kit that is developed within PARTHENOS. It also cross-links to other materials developed within PARTHENOS and by the PARTHENOS Cluster Partners.
This is a record of a webinar dedicated to the phase of the research life cycle “Develop Research Questions”. It dives into details of the topic of developing research questions with RIs, especially on finding, working with and contributing data to RI collections, using Virtual Research Environments, and tools.
This is a record of a webinar dedicated to the phases of the research lifecycle “Carry out Research” & “Analyse Data” in the context of a research infrastructure. Carrying out research and analysis in the context of a research infrastructure requires a change in approach to research, where the harmonization of data and the ability to access and deploy interoperable services is crucial. This webinar gives an overview of the necessary elements required to set up a sustainable research infrastructure with regards to the management of data and services.
DARIAH Winter School 2016 explored the evolution of publication issues in social sciences and humanities in a context of Open Access, with the underlying goal of promoting open science through the question of open data citation.
This module looks at emerging trends and best practice in data management, quality assessment and IPR issues. It looks at policies regarding data management and their implementation, particularly in the framework of a Research Infrastructure.
This module is specifically aimed at those who are not yet familiar with ontologies as a means of research data management, and will take you through some of the main features of ontologies, and the reasons for using them.
