Ein Angebot von
After research data have been received at your RDC, they are subsequently reviewed on the basis of different criteria. These criteria and the granularity of the review depend on FDZ-internal agreements.
In this case, it is helpful to have a checklist in which all details of the verification can be listed and processed in a structured manner. A distinction is made between formal and content-related aspects of the incoming data check. If relevant information is missing or documents are not submitted in full, the data provider may have to make corrections.
1) Readability of files: |
Answer options |
Can all files (data and documentation) be rendered? |
Yes / No |
Are all files in preferred formats? |
Yes / No / Not checked |
If not, which files are not in preferred formats? |
Free text |
In which formats are the files and which software is required to render the files? |
Free text |
Were all files checked for viruses and other malware? |
Yes / No / Not checked |
Further comments on the readability of files: |
Free text |
1) Intellectual Property Rights, licenses, usage rights: |
Answer options |
Does the data depositor and/or your institute have all the necessary Intellectual Property Rights and/or usage rights to publish the data? |
Yes / No |
Was secondary (i.e. re-used) data submitted?? |
Yes / No / Not checked |
If yes: Has the publication of the data been authorized by the rights holder(s)? |
Yes / No / Not checked |
Was automatically generated data submitted (e.g. with data mining or web scraping)? |
Yes / No / Not checked |
If yes: Is the publication of the data allowed according to the terms of service/term of use of the data source? |
Yes / No / Not checked |
Have all submitted supplementary documents (e.g. articles, reports) been authorized by the respective authors? |
Yes / No / Not checked |
Does the submission contain any other material that could be subject to copyright issues? |
Yes / No / Not checked |
If yes: Found in: |
Free text |
File name(s) |
Free text |
Further comments on Intellectual Property Rights, licenses and usage rights: |
Free text |
2) Data Protection: |
Answer options |
Does the data contain personal data (e.g. names, addresses, IP or e-mail addresses)? |
Yes / No / Does not apply |
If yes: was consent for publication sought from the data subjects? |
Yes / No / Does not apply |
Does the data contain specific categories of personal data (so-called sensitive data), e.g. data concerning health, secuality, or ethnicity? |
Yes / No / Does not apply / Not checked |
Does the data contain very small-scale regional units? |
Yes / No / Does not apply / Not checked |
Does the data contain very fine-grained classifications of occupations? |
Yes / No / Does not apply / Not checked |
Are the data subjects from a special and/or very small population? |
Yes / No / Does not apply / Not checked |
Are combinations of variables possible that would lead to a de-anonymization/re-identification of data subjects (e.g. occupation and geo-information)? |
Yes / No / Does not apply |
Could linking with other datasets lead to a de-anonymization of data subjects? |
Yes / No / Does not apply / Not checked |
Do the responses to open-ended questions contain sensitive information falling under data protection regulations? |
Yes / No / Not checked |
Does the submission contain qualitative data? |
Yes / No / Not checked |
If yes: has the data been completely anonymized? |
Yes / No / Not checked |
Does the assigned access class comply with data protection requirements? |
Yes / No / Not checked |
Further comments on dataprotection |
Free text |
1) Data ingest: |
Answer options |
Are the data in scope for inclusion in SowiDataNet|datorium (research data from social or economic sciences)? |
Yes / No |
Does the submitted data files match the described project? |
Yes / No |
Are all data sets included that are described in the documentation? |
Yes / No / Does not apply |
Does the number of cases in the data match the number of cases stated in the documentation? |
Yes / No / Does not apply |
Are all variables included that are described in the documentation? |
Yes / No / Does not apply |
Do the variables match the survey instrument, e.g. the questionnaire? |
Yes / No / Does not apply |
Further comments on ingest: |
Free text |
2) Data preparation: |
Answer options |
Are unique IDs included? |
Yes / No / Does not apply / Not checked |
Are there coding mistakes and/or implausible variable values? |
Yes / No / Does not apply / Not checked |
Are there variable labels? |
Yes / No / Does not apply / Not checked |
If so: |
Free text |
Are they understandable? |
Yes / No / Does not apply / Not checked |
Are the labels correct with regard to content? |
Yes / No / Does not apply / Not checked |
Are there value labels? |
Yes / No / Does not apply / Not checked |
If so: |
Free text |
Are they understandable? |
Yes / No / Does not apply / Not checked |
Are the lables correct with regard to content? |
Yes / No / Does not apply / Not checked |
Are there missing values? |
Yes / No / Does not apply / Not checked |
If so: |
Free text |
Are they understandable? |
Yes / No / Does not apply / Not checked |
Have they been coded correctly? |
Yes / No / Does not apply / Not checked |
Does the data contain skip patterns? |
Yes / No / Does not apply / Not checked |
If so: |
Free text |
Is the skip pattern correct? |
Yes / No / Does not apply / Not checked |
Is the skip pattern documented? |
Yes / No / Does not apply / Not checked |
Do the data contain weighting factors? |
Yes / No / Does not apply / Not checked |
If so: |
Free text |
Is the weighting plausible? |
Yes / No / Does not apply / Not checked |
Is the weighting documented? |
Yes / No / Does not apply / Not checked |
Further comments on the data preparation: |
Free text |
3) Metadata: |
Answer options |
Were all mandatory fields filled correctly? |
Yes / No |
Were institution-specific mandatory metadata fields filled completely and correctly? |
Yes / No / Does not apply |
Do the metadata values match the data? |
Yes / No / Not checked |
Do the metadata values match the corresponding information in the documentation? |
Yes / No / Does not apply / Not checked |
Does the access class match the institution-specific policy (if applicable)? |
Yes / No / Does not apply / Not checked |
Does the license match institution-specific policies (if applicable)? |
Yes / No / Does not apply / Not checked |
Are version numbers and references to preceding or following versions stated correctly? |
Yes / No / Does not apply / Not checked |
Further comments on metadata: |
Free text |
4) Documentation: |
Answer options |
Is the data accompanied by documentation files? |
Yes / No / Not checked |
If so: |
Free text |
Questionnaire or other measurement instrument? |
Yes / No / Not checked |
Codebook? |
Yes / No / Not checked |
Methods report? |
Yes / No / Does not apply / Not checked |
Project report or Technical Report? |
Yes / No / Does not apply / Not checked |
Scripts or syntax files? |
Yes / No / Does not apply / Not checked |
Are there further documents? |
Yes / No / Not checked |
Are there references to further documentation on external websites? |
Yes / No / Not checked |
If so: |
Free text |
Do the URLs resolve at the time of publication? |
Yes / No / Not checked |
Are there references to other data publications and/or other repositories? |
Yes / No / Not checked |
If so: |
Free text |
Were persistent identifiers used? |
Yes / No / Not checked |
Do the URLs/Persistent Identifiers resolve correctly? |
Yes / No / Not checked |
Are there references to publications related to the data? |
Yes / No / Not checked |
If so: |
Free text |
Are these described with adequate bibliographical information? |
Yes / No / Not checked |
Are they referenced with Persistent Identifiers? |
Yes / No / Not checked |
Do the URLs/Persistent Identifiers resolve correctly? |
Yes / No / Not checked |
Further comments on documentation: |
Free text |
Summary: |
Answer options |
Are the data quality and the quality of the documentation sufficient for data re-use? |
Yes / No |
Are the data quality and the quality of the documentation sufficient for including the study in SowiDataNet|datorium? |
Yes / No |
Final comments: |
Free text |
[Quelle: GESIS – Leibniz Institut für Sozialwissenschaften, Checkliste für Institutskuratorinnen und -kuratoren von SowiDataNet]
Formal review of the resources received includes, for example, the following steps:
For the content check of the received resources you have to look at the files in detail. How granular this check is done depends on the FDZ-specific regulations and the Data types (quantitative or qualitative Data). Checking the content of the resources is of particular relevance and a prerequisite for subsequent use by other researchers. For example, the following criteria are checked:
In the event that the submission of resources is incorrect or incomplete, you must contact the Data curator. It is important to clarify whether these are minor changes that can possibly be made by you as Data curator. If the changes are major, it may be advisable for the Data provider to make them themselves in order to avoid erroneous changes on your part. In this case, the resources sent should be permanently deleted. A new review will now take place with the renewed and corrected submissions.
The research data policy of a publisher or funding agency often specifies whether and which data should be retained. If this is not the case, the researchers themselves must weigh up which Data are relevant for possible archiving and/or publication. This decision should depend on potential re-use and data quality.
For the selection and evaluation of research data it is helpful if some aspects are already considered in the research and or submission process. Therefore, advisory services may also be required in this step of the process.
For guidance on relevant advisory topics, see the “How to Advise Researchers” help bar.
[According to: Ludwig, Jens; Enke, Harry (Eds.) (2013): Leitfaden zum Forschungsdaten-Management. Handreichungen aus dem WissGrid-Projekt. Glückstadt: VWH Verlag Werner Hülsbusch Fachverlag für Medientechnik und -wirtschaft (translated by KonsortSWD).]
FDM-Hinweise für Ihre Beratungspraxis
When selecting research data for archiving in a research data center, the purpose for further use is crucial. Possible decision-making approaches for the selection of data are, for example:
In the end, researchers and Data curators must decide for themselves which Data are actually relevant for potential reuse. The following checklist can help researchers decide whether Data is worth archiving:
[Source: Weber, Andreas and Piesche, Claudia. "4.2 Datenspeicherung, -kuration und Langzeitverfügbarkeit". Praxishandbuch Forschungsdatenmanagement, edited by Markus Putnings, Heike Neuroth and Janna Neumann, Berlin, Boston: De Gruyter Saur, 2021, pp. 327-356. https://doi.org/10.1515/9783110657807-019 (translated by KonsortSWD)]