Overview:

The Data for Policy community is looking to appoint additional members to its six Area Committees. These committees contribute to the activities of the Data for Policy conference and Data & Policy journal, enabling and promoting global dialogue and research dissemination into the impact and potentials of data in governance and government. Both conference and journal are deepening knowledge of how policy and data relate to each other, building a new, highly interdisciplinary and cross-sectoral field of research.

In 2021, we appointed the first tranche of Area Editors, working in committees across six areas of interest for journal and conference. We now wish to expand the membership of the committees to further develop their role in the community.

Key tasks:

• Associate Editor for Data & Policy: Taking submitted papers through peer review to decision recommendation.
• Programme Committee Member for Data for Policy: Work with a team of experts to develop the conference programme through soliciting submissions, peer review, and speaker suggestions.
• Community Research: Opportunity to author reports commissioned by the journal.
• Community Development: Build knowledge of and connect with relevant individuals, institutions and events to introduce to the community.
• Community Advocacy: Disseminating information about community activities to own networks.

These tasks may be distributed, so that not all committee members perform all tasks.

About the Community:

The centre of the community is the Data for Policy Community Interest Company, registered in 2018, which is supported by key stakeholders in academia and government. Its main project is the global Data for Policy conference.

The peer-reviewed, open-access journal Data & Policy is owned by Cambridge University Press and published in association with Data for Policy.

Person specification

Essential:

• An understanding of data science and associated technologies (AI, IoT, Blockchain etc.) and their impact on policy, public service provision and societal and ethical questions.
• A PhD or proven research skills and engagement experience in a relevant field.
• Having or being part of a network of peers and experts on data and policy that could be leveraged for the journal
• Ability to work collaboratively within a distributed team
• Capacity to contribute consistently to committee’s activities

Desirable:

• A demonstrable track record in the area, e.g. in the form of publications, presentations at conferences, involvement in relevant working groups and initiatives.
• Prior experience of acting as part of an editorial team.
• An interest in Open Research and the ways in which the research and publishing process can be made more transparent and collaborative.

We welcome applications from any discipline, sector, or location. We particularly encourage applicants from outside the UK and USA, who are currently underrepresented on our committees.

There may also be opportunities for those who do not meet the essential criteria to join the committees in an operational support capacity. Please indicate this in your cover letter, when applying.

Term

An initial one-year term, which may be extended.

How to apply

CV and covering email explaining how you meet the person specification, and the general categories that interest you, to team @ dataforpolicy.org (removing spaces).

Deadline: 18 March

Benefits

Area Editors will be recognised on the website, marketing materials and communications related to the journal and conference. Commissioned articles will also credit the Area Editor.

Time commitment is expected to be the equivalent 1-2 days/month with approximately monthly meetings held by video call.

Areas of Interest

Candidates should indicate an interest in developing one of the following broad, non-domain specific areas (expertise across all components of an area is not essential, or expected). The interrelatedness of all categories is undeniable, and the categorization does not indicate siloed activity. It is rather an articulation of the breadth and depth of the vision and mission for improved data-driven decisions and policymaking, which is the ethos of the Data for Policy community.

Area 1: Data-driven Transformations in Governance and Policy

The area focuses on the high level vision for philosophy, ideation, formulation and implementation of new approaches leading to paradigm shifts, innovation and efficiency gains in collective decision making processes. These include but not limited to the following categories:

• Data-driven innovation in public, private and voluntary sector governance and policy-making at all levels (international; national and local): applications for real-time management, future planning, and rethinking/reframing governance and policy-making in the digital era;
• Data and evidence-based policy-making;
• Government-private sector-citizen interactions: data and digital power dynamics, asymmetry of information; democracy, public opinion and deliberation; citizen services;
• Interactions between human, institutional and algorithmic decision-making processes, psychology and behaviour of decision-making;
• Global policy-making: global existential debates on utilizing data-driven innovation with impact beyond individual institutions and states;
• Socio-technical and cyber-physical systems, and their policy and governance implications

Area 2. Data Technologies and Analytics for Policy and Governance

The area is concerned with data in its variety of forms and sources, and infrastructure and methods for its utilisation in policy and governance:

• Data sources: Personal and proprietary data, administrative data and official statistics, open and public data, organic vs designed data, sensory and mobile data, digital footprints, crowdsourced data, and other relevant data;
• Digital Twins, Visualisation and User Interaction Technologies, data and analytics infrastructures, cloud and mobile technologies;
• Methodologies and Analytics: Mathematical and Statistical models, Computational Statistics, Machine Learning, Edge Analytics, Federated Learning, theory and data-driven knowledge generation, multiple disciplinary methodologies, real-time and historical data processing, geospatial analysis, simulation, gaps in theory and practice.

Area 3. Policy Frameworks, Governance and Management of Data-driven Innovations

The area focuses on governance practices and management issues involved in implementation of data-driven solutions:

• Data and algorithm design principles and accountability;
• Local, national and international governance models and frameworks for data and associated technologies;
• Data and algorithms in the law;
• General Data Protection Regulation (GDPR) and other regulatory frameworks;
• Data intermediaries, trusts and collaboratives;
• Meta-data, interoperability and standards;
• Data ownership, provenance, sharing, linkage, curation and expiration.

Area 4. Focus on Ethics, Equity and Trust in Policy Data Interactions

The area examines the issues which must be considered in technology design and assessment:

• Digital Ethics: Data, algorithms, models and dynamic interactions between them
• Digital trust, and human-data-machine interactions in policy context
• Responsible technology design and assessment
• Privacy and data sharing
• Digital identification, personhood, and services
• Uncertainties, bias, and imperfections in data and data-driven systems
• Algorithmic behaviour: equity and fairness, transparency and explainability, accountability, and interpretability
• Human-machine collaboration in strategic decision making and algorithm agency
• Human control, rights, democratic values, and self-determination

The following are areas which fall within the above categories, but are highlighted as being of special interest:

Area 5. Algorithmic Governance

The area focuses on:

• Data-driven insights in governance decision making, black-box processing;
• Algorithm agency along with human and institutional decision-making processes;
• Government automation: citizen service delivery, supporting civil servants, managing national public records and physical infrastructure, statutes and compliance, and public policy development;
• Algorithmic ‘good’ governance: participation, consensus orientation, accountability, transparency, responsiveness, effectiveness and efficiency, equity and inclusiveness, and the rule of law.

Area 6. Data to Tackle Global Issues and Dynamic Societal Threats

The area considers:

• Human existence and the planet;
• International collaboration for global risk management and disaster recovery;
• Global health, emergency response, Covid-19 and pandemics;
• Sustainable development, climate change and the environment;
• Humanitarian data science, international migration and gender-based issues;
• International competition and cultures of digital transformation.