Data & Policy

Scope & Guideline

Bridging Data Science and Public Policy.

Introduction

Explore the comprehensive scope of Data & Policy through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore Data & Policy in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN-
PublisherCAMBRIDGE UNIV PRESS
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationDATA POLICY / Data Policy
Frequency1 issue/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressEDINBURGH BLDG, SHAFTESBURY RD, CB2 8RU CAMBRIDGE, ENGLAND

Aims and Scopes

The journal 'Data & Policy' focuses on the intersection of data utilization, governance, and policy-making, emphasizing how data can be leveraged to improve public decision-making and governance frameworks. It serves as a platform for research that explores innovative methodologies, frameworks, and implications of data-driven approaches in various sectors.
  1. Data Governance and Policy Frameworks:
    The journal examines the policies and frameworks that govern data use, focusing on creating trustworthy, inclusive, and effective data governance that aligns with public interests.
  2. Data Analytics and Machine Learning Applications:
    A significant emphasis is placed on the application of advanced analytics and machine learning techniques in public policy, aiming to enhance decision-making processes and predict outcomes in various domains.
  3. Interdisciplinary Approaches to Data Utilization:
    The journal promotes interdisciplinary research that integrates insights from social sciences, technology, and public administration to address complex societal challenges through data.
  4. Public Engagement and Citizen Participation:
    Exploration of how data-driven initiatives can enhance citizen engagement and participation in governance processes, ensuring that policies are reflective of public needs and expectations.
  5. Sustainability and Ethical Data Use:
    The journal underscores the importance of ethical considerations in data use, particularly in relation to sustainability and social equity, advocating for responsible data practices.
The recent publications in 'Data & Policy' highlight several emerging themes that reflect the current trends and future directions of research in the field of data governance and policy-making.
  1. AI and Ethics in Public Policy:
    There is a notable increase in research addressing the ethical implications of AI applications in public policy, emphasizing the need for transparency and accountability in algorithmic governance.
  2. Data Collaboratives and Partnerships:
    Emerging studies focus on the establishment of data collaboratives that foster partnerships between public and private sectors, highlighting their role in addressing societal challenges.
  3. Impact of COVID-19 on Data Practices:
    The pandemic has catalyzed a surge in research exploring the role of data in crisis response, emphasizing innovative uses of mobile and public health data during emergencies.
  4. Integration of Citizen Data in Decision-Making:
    Increasing attention is being paid to how citizen-generated data can inform public decision-making processes, promoting a more participatory approach to governance.
  5. Smart Cities and Data-Driven Innovation:
    A growing interest in how data can facilitate the development of smart cities, focusing on urban planning, mobility, and infrastructure challenges, is evident in recent publications.

Declining or Waning

While 'Data & Policy' continues to evolve, certain themes have shown a decline in prominence, indicating shifts in research focus and emerging priorities within the field.
  1. Traditional Data Collection Methods:
    There seems to be a waning interest in conventional data collection techniques, as more innovative and technology-driven approaches become prevalent in the discourse.
  2. Overly Technical Governance Models:
    Research that solely focuses on highly technical aspects of data governance without considering real-world implications and stakeholder perspectives is becoming less frequent.
  3. General Discussions on Digital Transformation:
    Broad discussions around digital transformation in public sectors without specific focus on data-driven outcomes and policies are receiving less attention in recent publications.

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