If the empirical basis for an article or book cannot be reproduced, of what use to the discipline are its conclusions? What purpose does an article like this serve? (King: “Replication, Replication” 1995)
Long-term ordering, saving and archiving research data is of crucial importance. Its necessity is increasingly recognised and universities are formulating policies on how to deal with research data. Published datasets enhance a publication and the world of science in general. The growing popularity of open-access publishing concerns not just the contents of publications, but provides opportunities to make raw research data available and thus enrich publications.
The UvA/AUAS Library is glad to offer support in ordering, describing, saving, sharing, archiving and publishing your research data.
Two important collaborations in the field of research data in economics are based in England and Germany. They are champions of open data and transparence in research and research output. They both have a programme running to map and stimulate open data in economic research.
The first step in responsible data management is to draw up a Data Management Plan (DMP). In this document the researcher(s) describe(s) what type of data are collected, how and where they are stored, and who will have access to them. A DMP is increasingly often made mandatory when submitting a funding application for a research project.
On the Data management plan page you can find the kind of questions which must be covered by a DMP. Here you also find links to templates, checklists and online DMP tools which may help during the writing of a DMP.
Please note: a DMP must be written by the researchers themselves, but an information specialist from the library can offer advice and support during the process.
The descriptions of the raw data are called metadata. It concerns such information as who collected the data, where, when, what type of data, within which subject, etc. When you deposit a dataset in a repository, you will also be asked to enter information which describes the dataset. A much-used standard for metadata is Dublin Core. This standard allows for a wide choice of disciplinary fields and can handle many types of data.
The person who deposits the dataset is responisible for the metadata. An information specialist from the library can help you select the most appropriate metadata.
In order to store data, most research groups use their own server, space on the shared network drive, Dropbox or external hard disks. Below are some more reliable and solid alternatives.
In UvA/AUAS figshare you can store your research data safely and still have access: your files are stored on ISO certified servers in Switzerland, and you can access them from any computer with an internet connection.
You can also safely share, archive and publish your research data. Your file is assigned a Digital Object Identifier (DOI), a unique permanent link you can use in articles and presentations.
DANS allows you to archive your data securely and durably via their online archiving system EASY. It is you who determine under which conditions your data will be accessible to others.
4TU.ResearchData is a collaboration of the three technical universities in the Netherlands. UvA researchers can use 4TU.ResearchData for the long-term archiving of data.
The following repositories offer datasets which may be reused for new research.
If you have any questions or need advice, please contact your information specialist.