CSC – IT Center for Science provides data management services and tools for computing, storing as well as opening and sharing data. As the amount of data is increasing all the time, it is important that services support the workflows and enable easy data handling.
”I think open research data promotes honesty and transparency in science. Once a data set is well described, citable and available on clear terms, it is easy to discover and to reuse, and studies done on the data set are easier to replicate and to improve on”, says Mietta Lennes, Project Planning Officer for FIN-CLARIN consortium, which coordinates the Language Bank of Finland (Kielipankki). Lennes is one of the speakers at the webinar event ”What it takes: Open your research data” that takes place on 25 March 2021.
The new issue of Think Open Digest concentrates on the basics of research data management (RDM) and data management planning (DMP). ”Know Your Data” contains six articles and is aimed at all researchers – especially those who doubt the usefulness of RDM and DMP.
The digital environment requires new skills from researchers. For example, a researcher has to understand the complexities of the relevant legislation, or know how to choose suitable IT solutions to keep their data secure. Fortunately, researchers are not left to navigate these issues alone, as we have several services available for data management.
Data management planning (DMP) is too often considered a burden and a bureaucratic procedure. However, a data management plan is a useful tool that helps researchers prepare more effectively for the research process and identify the potential risks. DMP also has significant pedagogical potential and, in collaboration with DMP organisations, can develop the infrastructure and services needed to conduct research.
Every aspect of research data management (RDM) is equally important and all parts of the process need to be properly discussed and planned. Poor data management planning (DMP) is a risk that can potentially cause problems for the research project. This fourth section of the ”Know your data” article series highlights the importance of planning ahead.
In the first few sections of this blog series, we answered the question: What is research data management (RDM)? In this post, we will provide more detail on the changes in the research process that relate to RDM and explain why it has become increasingly important to understand the significance of RDM.
The key components of research data management (RDM) consist of the following: knowing and describing your data, following ethical and legal principles, and understanding the workflows related to securing, storing, sharing, archiving, opening, and publishing your data. Here, we take a closer look at these RDM components and their relationship with the scientific research process and the basic services provided by a researcher’s home organisation.
This new article series presents the basics of research data management (RDM). The opening section of the series provides an overview of RDM: what it is, why it concerns all researchers, and how the RDM life cycle relates to the research life cycle.
”You should act like every measurement you start is going to continue forever, but the people in charge of the measurements and data flow would move on to different tasks the next week,” says Pasi Kolari, university researcher at the University of Helsinki. In this blog interview, Kolari, who works as a data liaison for SMEAR stations (Station for Measuring Ecosystem-Atmosphere Relations), sheds light on the real life challenges of collecting, processing and opening data. The article is part of the Think Open article series on open science research infrastructures.