A Workshop @ WebSci19, Boston MA, Sunday June 30th 2019 – Call for papers

AsSalam and hi all,

If you find this event is suitable for you, or your friends; Check the official site at https://generic.wordpress.soton.ac.uk/datatrustsworkshop/ .

 

Relevance, Motivation & Goals

Open Data has been a goal pursued primarily by governments, to unlock previously inaccessible value and accelerate growth of digital businesses. This has been tremendously successful in the US as well as across Europe. While open data is open to all, there is also benefit in sharing data that is not public. Existing examples of this include data marketplaces such as Dawex, or funding programmes like the European Data Incubator or Data Pitch where shared data creates innovation. However, the process of sharing closed data frequently involves complex negotiations and legal agreements. With the introduction of the European General Data Protection regulation (GDPR) in May 2018, considerations of privacy and data protection have become more important, as data subjects gained more explicit, and enforceable rights, while sharing data across borders became easier. Businesses in Europe are already embracing data trusts such as Trūata to ensure compliance, but more institutions are required to address the complications of these processes, and consolidate the interests of data subjects, processors and owners.

This consolidation could happen through the – still conceptual – frameworks of Data Trusts, Data Collaboratives or Data Cooperatives. These institutions are intended to simplify the use of data by enabling an environment in which is can be shared while maintaining the trust of all parties involved. While Data Collaboratives are an idea born in the US-based GovLab (Verhulst & Sangokoya, 2015), Data Trusts have been brought into focus in the UK by an Independent Review on AI (Hall & Pesenti, 2017). Their goals are broadly the same: Institutionalised oversight of the handling and sharing of different types of data, such as government data, but also corporate, industrial, research, or aggregate personal data, which is not intended for the public domain (McDonald, 2018; Hardinges, 2018, Verhulst, 2018).

Due to their potentially central role in data sharing environments, these institutions are also of particular interest for academics from a broad variety of fields, including Computer Science, Law, Political Science, and Sociology. There is very little published research treating them as an object of study in their own right and placing them in a broad socio-technological context.  This workshop aims to investigate the potential for coherent multidisciplinary research into the institutional frameworks that enable the sharing of data, what their development means for society as a whole, why this matters, and how they might work.

Such research should address questions such as:

What are these institutions? Are Data Trusts, Collaboratives, and Cooperatives the same, or different? Is there one kind of institution or many? How should they function and make decisions? What skills, knowledge and attitudes are required to set them up? What existing frameworks can be drawn upon to deliver them?

Why do we need them? What are their legal, technical, socio-technical challenges and implications? Which issues they can address?

How should they be established? What organisational structure is best suited to achieve their goal: Charities, government institutions, or privately owned companies?  Are existing legal concepts sufficient?

Who should be involved? Are these institutions meant to increase trust of data subjects, data controllers, or data processors, or a combination of all of the above? How are the parties’ interests represented, and how can this work at scale?

What are the practical implications? In what form should private and public sector organisations be working with these institutions? How should they be connected to education and research?

What are the broader political, social and philosophical implications? How should these institutions go about establishing trust, e.g. through certification or control? What are the implications of these decisions in the near and distant future?

Objectives

  • Convene members of the academic community from multiple disciplines with an interest in Data Sharing
  • Evaluate the state of current research into Data Sharing institutions – understand which areas have an interest in the subject and the thrust of their research
  • Investigate the potential for a future research agenda.

It is beyond the scope of the workshop itself to design a common research agenda although it is to be hoped that the workshop will lead to such a framework.

Expected Outcomes

  • Document the current state of research in this area.
  • Identify an emergent research agenda.
  • Identify and agree two or more multidisciplinary research projects to take forward research in this area.
  • Create an on-going community of people interested in research in this area with a forum for sharing interests.

Target Audience

Academics with an interest in the socio-technical development of data sharing institutions and associated topics such as open data, data sharing platforms, or privacy and data protection, who:

  • want to build networks to promote and coordinate research
  • Are looking for a forum to publish their research in this area

A recent workshop on data trusts at the Alan Turing Institute in London was attended by over 50 people.

 

The workshop will take place on the 30th June.

 

Call for Papers

This year WebSci19 will include a workshop on Data Sharing, with the aim of establishing the institutions that enable data sharing as a topic of academic study.

Open Data has been a goal pursued primarily by governments, to unlock previously inaccessible value and accelerate growth of digital businesses. This has been tremendously successful in the US as well as across Europe. In the scientific community, there has also been extensive work on the infrastructure required to support the sharing and use of vast amounts of data through Data Commons. While open data is open to all, there is also benefit in sharing data that is not public. To enable the uptake of the new opportunities arising with data sharing, new institutions are required. These should address the complications of data sharing processes, and consolidate the interests of data subjects, processors and owners. This consolidation could happen through the – still conceptual – frameworks of Data Trusts, Data Collaboratives or Data Cooperatives, which are intended to simplify the use of data by enabling an environment in which is can be shared while maintaining the trust of all parties involved. Due to their potentially central role in data sharing environments, they are also of particular interest for academics from a broad variety of fields, including Computer Science, Law, Political Science, and Sociology. There is very little published research treating data sharing institutions as an object of study in their own right and placing them in a broad socio-technological context. This workshop aims to investigate the potential for coherent multidisciplinary research into the institutional frameworks that enable the sharing of data, what their development means for society as a whole, how they might work, and why this matters.

The workshop will take place on the 30th June.

Important Dates

All deadlines are midnight AoE time on the date specified.

  • Papers submitted by: 10th April
  • Notification to authors: 17th April
  • Camera ready submission: 1st May

Topics

We invite submissions of papers on the following topics:

What are data sharing institutions? Are Data Trusts, Collaboratives, and Cooperatives the same, or different? Is there one kind of institution or many? How should they function and make decisions? What skills, knowledge and attitudes are required to set them up? How do they differ from scientific Data Commons? What existing frameworks can be drawn upon to deliver them?

Why do we need them? What are their legal, technical, socio-technical challenges and implications? Which issues they can address?

How should they be established? What organisational structure is best suited to achieve their goal: Charities, government institutions, or privately owned companies? Are existing legal concepts sufficient?

Who should be involved? Are these institutions meant to increase trust of data subjects, data controllers, or data processors, or a combination of all of the above? How are the parties’ interests represented, and how can this work at scale?

What are the practical implications? In what form should private and public sector organisations be working with these institutions? How should they be connected to education and research?

What are the broader political, social and philosophical implications? How should these institutions go about establishing trust, e.g. through certification or control? What are the implications of these decisions in the near and distant future?

Submission

Submissions can be of two types:

  • Completed long papers (8-10pp)
  • Short papers (experience related, position papers, research in progress; 3-5pp)

All papers should be submitted through EasyChair.

The programme committee will select the best papers to be presented at the workshop. All accepted papers will be published on the workshop website. This will be done several days before the workshop in order to facilitate discussion in the plenary section of the workshop. All accepted papers will also be included in the proceedings of the ACM Web Science 2019 conference proceedings

Selection criteria

The selection criteria are adapted from the Springer LNCS. Submissions should:

  • Be written in English;
  • Fit with the workshop theme;
  • Have a clear motivation (why the problem is interesting theoretically and/or practically);
  • Conceptual development and grounding in prior literature (given the nascent nature of the topic it is not expected that the prior literature is about data sharing institutions);
  • Methodological adequacy (if relevant);
  • Adequate list of references to related work and grounding theories;
  • Interesting findings;
  • Well-structured and clearly written paper;
  • Maximum length of paper: 10 pages for full papers, 5 pages for short papers; and
  • Conform to WebSci 2019 (SIGCONF) rules for formatting.

Papers will be subjected to double blind review by 2 reviewers for rigour, relevance, originality and clarity of presentation and then the accepted papers will be chosen by the programme committee based on the reviewers’ assessment. Papers should be anonymised, i.e. all information identifying the authors removed, before submitting via Easychair.

Contact: gefion.thuermer@soton.ac.uk

Acknowledgments

The workshop is supported by the H2020 projects Data Pitch, euBusinessGraph, EW-Shopp, and TheyBuyForYou.