The Data for Policy conference series is the premier global forum for multiple disciplinary and cross-sector discussions around the theories, applications and implications of data science innovation in governance and the public sector. The conference series has also entered into a new open-access peer-reviewed journal venture, Data & Policy (cambridge.org/dap), published by Cambridge University Press and supported by the Alan Turing Institute, the Office for National Statistics and UCL, in order to capture, assess and disseminate scholarly discussions in this fast-growing field.
Deadline: April 20, 2020
Convening for the fifth time in September 2020, the International Organisation Committee for the conference invites Paper and Panel Session proposals at the conference to be also considered for potential post-conference publications in Data & Policy (subject to peer-review).
Topics covered include but are not limited to the following:
- Data, Governance and Policy: Digital era citizenship, governance and democracy; data and sustainability, data and politics, evidence and information, data-algorithm-policy interactions, public-private sector collaborations, best practices;
- Governance Technologies (GovTech): Machine Learning (ML) / Artificial Intelligence (AI), Big Data, Blockchain Distributed Ledger and Smart Contract Technologies, Behavioural and Predictive Analytics, Internet of Things, Information Security, location-based technologies, user-interaction technologies (chatbots, platforms etc.), and other relevant technologies;
- Systems & Infrastructure: Data collection, capture, storage, sharing/transactions, processing and visualization systems, mobile applications and web services, high performance computing, distributed and decentralized systems, and other relevant topics;
- Data Processing & Knowledge Generation: Data representation and pre-processing, data integration, real-time and historical data analysis, mathematical and statistical models, ‘data-driven’ analysis, mixed methodologies, secondary data analysis, web mining, Randomised Controlled Trials (RCTs), gaps in theory and practice, other relevant topics;
- Policy for Data & Management: Data governance and regulatory frameworks; General Data Protection Regulation (GDPR); data ownership, curation, sharing and linkage; meta-data, standards and interoperability, responsible innovation in governance;
- Trust, Privacy, Ethics & Law: Personal data sharing, data integrity, algorithm agency and accountability, ‘trustworthiness’ of autonomous systems, algorithmic transparency and interpretability, citizen-government-private sector interactions, citizen/public rights and free speech, other social/ethical concerns and technology responses.
In addition to these Standard Tracks, submissions can also be made to the following Special Tracks that have been shortlisted for this year’s conference.
Contributors should follow the instructions on the conference website in order to submit an abstract for their paper or session proposal, or their poster presentation.
Abstract submissions will be assessed according to the criteria outlined on the website. Contributors will be notified on 18th May whether they have been accepted into the conference.
Those accepted to present at the conference will be given two mutually compatible, open-access options for disseminating their full paper and/or any related materials.
The Data for Policy community platform on Zenodo (https://zenodo.org/communities/dfp17), an open-access repository, can be used to share the paper ahead of the conference, along with any related materials such as posters, slides, audio, video, protocol, data sets and code that you think others may wish to view or re-use.
In addition, there is the option of submitting a full paper to Data & Policy (cambridge.org/dap), the open access journal launched in collaboration with Cambridge University Press (CUP). As outlined on the website the journal considers several article types: research papers, commentaries, replication studies and Data & Policy reports. Authors will receive feedback from editors and reviewers with expertise in different domains, as a result of the peer-review process overseen by the Editorial Board. If accepted, the paper will receive greater impact as a result of formal publication, curation and promotion from our partners at CUP.
Neither of these dissemination options are required for presenting at the conference, but we encourage contributors to consider the advantages of using them to help build the community and knowledge base concerned with impact of data science on policy and governance.
Contacts: For all questions related to conference submissions, please contact email@example.com; and for questions relating to publication in Data & Policy, please contact firstname.lastname@example.org .