Research data and data management are integral parts of research. This guide provides instructions and resources for the planning, organising, storing, sharing and opening of research data. The guide also offers information about ethical and legal issues as well as about organisational services.
By Planning your data management well
The structure of this guide is based on the data life cycle, and we recommend using the guide throughout the research project. The start of the data management of a research project is done well when the various stages of the data life cycle of research data are considered already when creating the research plan. Writing a data management plan is a practical tool to make your own research work easier and better planned.
Some research data are still gathered and handled non-digitally. Examples of such data might include e.g. paper-based data, biospecimen, fossil specimen, art samples, artefacts or other concrete objects that either cannot be converted to digital form at all or such processing would require too much labor or other resources to be feasible.
Regardless of whether research data are digital or non-digital, proper data management is always crucial. Non-digital data require different approaches, methods and tools for preservation and management than digital data. Non-digital research data might require e.g. filing cabinets, archive-friendly filing systems, physical storage solutions, specific climate conditions and other special tools and instructions for preservation.
Metadata production is a key element in non-digital research data management. Different types of metadata (e.g. descriptive, structural, process-related, administrative etc.) are required to ensure the proper care and preservation of non-digital research data. The principles of data documentation will be explained in Metadata & Documentation -section. In addition to this, Tampere University Archives also give further instructions on metadata guidelines regarding non-digitally preserved research data.
For more information and advice, please contact:
Data Service at Tampere higher education community helps you manage your research data. Our service comprehends library, IT-support, research and innovation services, document management and law department together with Tietoarkisto (FSD).
We offer service, tools and training for gathering, documenting, storing and sharing the data. Our service supports the implementation of FAIR in all phases of your research project. You can contact us at email@example.com
Tampere higher education community promotes responsible and open science, access to digital research data, scientific publications and research methods, and the use of open source codes, standards and interfaces in research. According to the higher education community's Open Science and Research policy:
Tampere higher education community promotes open science and research in data management but also in publishing activities. The goal is to increase visibility and availability of scientific research.
Research data should be "as open as possible, as closed as necessary", which is the guideline by the European Commission on Data Management. The Guidelines of FAIR Data Management in Horizon 2020 (pdf) was released in July 2016.
See also Tampere higher education community's Research Strategy.
Tampere University of Applied Science: Open Science Action Plan (Coming soon)
In this guide, research data refer to digital datasets, which are generated, processed and used in scientific research, and used as the basis for research findings. In addition to datasets, research data include information describing the context, contents and structure of the data (metadata), along with its lifetime management and processing. The research data produced at Tampere University and Tampere University of Applied Sciences are in principle shared and open.
At Tampere University of Applied Sciences (TAMK) research data refer to all the materials, methods and results produced and used in the TAMK research, development and innovation (RDI) projects.
Research data produced within Tampere higher education community should be:
Familiarise yourself with these FAIR-principles and take them as guideline of your research data management. Check also services produced by CSC - IT for science, and use them to improve the level of FAIRness of your research.