The deadline to submit something to our workshop ‘Data Privacy Controls and Vocabularies’ is 28 February 2018.

The workshop is organised jointly by W3C and SPECIAL, and its subtitle is ‘A workshop on Privacy and Linked Data’. Those facts together already hint at the premise of the workshop: that various aspects of privacy, such as giving consent, comparing privacy policies and checking compliance, can be done at least partly by computer, which saves people's time, but also helps people understand them. Machine-readable models help to create smart user interfaces, both for end users (the people whose data is collected) and for people managing or validating the data.

What would machine-readable models for the various aspects of privacy look like? What vocabularies (‘ontologies’ in the Semantic Web) exist or have to be created? Are there common aspects that can be standardised and thus contribute to a common user interface?

There are various technologies already that address small parts of the problem or of related problems, such as Tracking Protection (‘DNT’), Permissions and ODRL. How can these and other technologies work together? Can we share (or buy & sell) common solutions, so that the work both of data controllers and data subjects (users) becomes easier?

The workshop will be in Vienna on 17 & 18 April 2018. The workshop page in particular, but not exclusively, invites the following people:

  • people dealing with Linked Big Data
  • privacy advocates
  • data protection authorities
  • security and privacy researchers
  • developers of Privacy Enhancing Technologies

it is not necessary to submit a full paper. A position statement of 500–1000 words is enough. And to make it even simpler, we have also provided an online form, where you can write your position statement by answering five questions.

The deadline is 28 February 2018.

Horizon 2020 - European Union Funding for Research & Innovation.

This project receives funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 731601

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