Archive data
Your research project is completed, and the collected data has been documented. Do you want to archive the existing data in compliance with the DFG and store it for ten years with good scientific practice? Our recommendation: Sort data, select those worth archiving, save them in sustainable file formats, label them meaningfully and unambiguously with metadata, and store them in a secure and accessible location.
Archival file formats
Whether you choose to publish your data or not, you should save your data in file formats that can be used over the long term and include documentation. For selecting a future-proof file format, the following questions will help:
- Is the file format widely used, even outside the technical community?
- Is the format open source and usable without software requiring a license?
- How complex is the data format? When in doubt, simpler ones are preferable.
- Does the data format use data compression that may be lossy?
We recommend the following archivable formats for research data in a tabular overview:
| Content | Recommended format |
|---|---|
| Text | PDF (ideally: PDF/A) with no formatting: TXT for editability: ODT, RTF, HTML with formulae: LaTeX (TEX) |
| Tables | CSV / TSV numerical data: HDF5 |
| Graphics | raster graphics: PNG, TIFF (baseline) vector graphics: SVG, EPS |
| Multimedia | container: MKV, WebM, OGG video-codec: AV1, VP9 audio-codec: FLAC, WAV (PCM data), Vorbis, Opus |
| Relational Databases | SIARD, Dump, XML, see also formats in the row tables |
| Structured data | XML, JSON, YAML |
Archive solutions
Visit the website of the Leibniz Supercomputing Centre (LRZ) to learn more about archiving solutions in the Munich Scientific Network.
Get in touch!
Archiving research data can feel daunting - we are happy to support! Contact us at researchdata(at)tum.de.
Further information Submit application & planning, Store & manage data, Publish & share data, Reuse data