Technology is playing a progressively important key role in enabling effective governance structures, processes, and frameworks. As society becomes increasingly dependent on complex systems ranging from simple' decision support systems' to 'systems of systems' and 'semi-autonomous systems,' data and algorithmic governance are of utmost importance.

When it comes to data and algorithmic governance tools and techniques, there are still many open questions. For instance, to what extent do these systems safeguard against privacy violations and honor intellectual property rights? Can granular consent be granted, and will the consequences be understood by its users? How can biases, discrimination, and censorship be identified and acted on? Do transparency and explainability lead to greater accountability? How can trust be woven into the fabric of these systems?

Towards this end, this special issue aims to explore the development and evaluation of semantic technologies with respect to the data and algorithmic governance mechanisms, processes, and methodologies that are critically needed to support the development of trust-centric social and business applications alike.

== Topics of Interest ==
We welcome original high-quality submissions on (but are not restricted to) the following topics:

Findable, Accessible, Interoperable, and Reusable (FAIR) data management
Techniques for enabling ownership, control, and access
Identifying fake news and misinformation
Managing bias and ensuring fairness
Enabling transparency, explainability, and accountability
Methods for policy governance
Information flow control and accountability
Measuring data quality
Managing the data life cycle
Metrics for assessing the effectiveness of governance algorithms
Data privacy, regulations and compliance
Provenance, trust, and metadata for authoritative sources
Privacy and security enforcement
Methods for information flow control and accountability
Frameworks and systems for personal data storage and control
Ensuring data authenticity and integrity
Privacy-preserving data mining and machine learning methods
Protecting against identity theft and data falsification
User-friendly interface design for data and algorithmic governance
Standards for data and algorithmic governance
Tackling legal issues with respect to data and algorithms
Law and governance in e-democracy and e-participation
Benchmarking approaches to data and algorithmic governance
Building trust and transparency mechanisms in the fabric of the Web
Participatory frameworks for fair and efficient algorithmic governance

== Deadline ==
November 15, 2020 - Paper submission deadline.
Papers submitted before the deadline will be reviewed upon receipt.

== Author Guidelines ==
Submissions shall be made through the Semantic Web journal website at http://www.semantic-web-journal.net. Prospective authors must take notice of the submission guidelines posted at http://www.semantic-web-journal.net/authors.

Note that you need to request an account on the website for submitting a paper. Please indicate in the cover letter that it is for the "Semantic Technologies for Data and Algorithmic Governance" special issue. All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process.

Submissions are possible in the following categories: full research papers, surveys, application reports, and case studies. While there is no upper limit, paper length must be justified by content.

== Guest editors ==

* Michel Dumontier, Maastricht University, The Netherlands
* Sabrina Kirrane, Vienna University of Economics and Business, Austria
* Oshani Seneviratne, Rensselaer Polytechnic Institute, USA

The guest editors can be reached at swjgovernance@googlegroups.com.