Publishing data has an overall positive impact on the quality and availability of scientific data. It is essential for the transparency of scientific work and also provides the necessary incentives for data producers. Existing procedures are varying and cannot be seen as final. Crucial is that data sets are consistently structured, that they are citable and fully documented, so the quality can be estimated and usage of data is reliable and efficient. Citability includes usage of persistent identifiers (as Digital Object Identifiers – DOI) for referencing published data entities, which may either be supplementary to a traditional publication or standalone data publications. To ensure the data quality peer-review like procedures for publishing data are indicated. Data publication services need to be integrated into the traditional science publication process. They require a coherent system consisting of libraries, science publishers and certified data repositories as e.g. supplied by the new ICSU World Data System (WDS).

Presentations might address one or more of the following topics
- Data publication workflows (incl. cross-linking issues between journals & data archives)
- Trustworthiness of data archives (certification and accreditation)
- Peer review models and QA/QC procedures
- Persistent identifier & Catalogues
- Bibliometrics
- Data citation issues (syntax, granularity etc.)
- Intellectual Property Rights & Licensing
- Metadata & data exchange standards
- Editorial systems for data
- Business models
- User experiences, expectations, and needs
- New concepts (linked data, open data, clouds)