Determining the best data storage solution for your research can be cumbersome. To make the selection process easier, University of Helsinki researchers can now use the Data Storage and Sharing Table, which describes the various options available for storing research data. This blog post explains the criteria for choosing your research data storage solution.
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.
Last year, the National Library of Finland launched the Digital Open Memory project, which aims to develop the data driven services for researchers, especially in digital humanities. According to a survey conducted in the project, reading and interpreting texts, were still the major ways of using digital material among researchers in the humanities, and the pressure to provide more services for text and data mining is obvious.
Kansalliskirjastossa alkoi viime vuonna Digitaalinen avoin muisti (DAM) -hanke, joka tähtää kirjaston digitaalisten aineistojen laajempaan ja monipuolisempaan käyttöön erityisesti digitaalisten ihmistieteiden tutkimuksessa. Ensi vuonna päättyvän hankkeen tulosten pohjalta määritellään, millaisia datapalveluja Kansalliskirjasto jatkossa tarjoaa. Tutkijoille viime keväänä tehdyn kyselyn mukaan erityisesti tiedonlouhinnan mahdollistaville lisäaineistoille on kysyntää. Tässä blogiartikkelissa esitellään kyselyn tuloksia ja Kansalliskirjaston suunnitelmia Louhokseksi nimetyn palvelukonseptin kehittämisessä.