The KIM and the Team Open Science support you in publishing your data. In addition to general support with questions concerning the use of KonDATA, we offer you comprehensive and accompanying data curation when publishing each dataset. On this page we inform you what this curation looks like and what limits there are. General information on the publication of data can also be found on the information platform forschungsdaten.info.
If you have any questions or a specific request for publication, please contact us or take the opportunity to visit our KonDATA consultation hour at the KIM Media Lab BA440, on Mondays, 1 - 2 p.m. No prior registration is necessary.
Feel free to drop by on the following dates:
November 4th | November 18th | November 25th
Not on-site at the moment? An appointment during the same period is also possible by video call. Please send us an email in advance (kondata@uni-konstanz.de) to sign up.
Data Curation
Formal and Technical Curation
Formal and technical curation means looking at the dataset without getting into the content. Is the metadata correct and complete? Do certain values (e.g. name, date) correspond to the format specifications? Is the file format correct and can the record be opened? Is the character encoding correct? Is an appropriate file format used?
Some of this curation, especially on technical points, is done automatically by the repository. We will look at the other formal criteria together with you. Personal contact persons will be available to assist you. You will receive a detailed protocol of the curation from us, together with information on what still needs to be changed before the data can be published and where we recommend a change.
This process can take several iterations, but in our view curation is necessary to guarantee reasonable data quality.
Content Curation
Content curation means taking a closer look at the data. Do the descriptions of the variables fit? Are subject-specific vocabularies used in the description? Are the ranges of values given correct? Are the data plausible? One quickly realises that content curation can reach a very large scale and requires a precise knowledge of the data. We at KIM cannot and do not want to do this, especially because we do not have the necessary scientific expertise.
Nevertheless, we would discuss these questions with you and go as far together as both sides consider necessary. In the end, content curation improves data quality and we aim for the highest possible quality.