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CALL FOR PAPERS: 52nd HICSS 2019, Maui, Hawaii
DATA-DRIVEN GOVERNMENT: CREATING VALUE FROM BIG AND OPEN LINKED
DATA MINITRACK
In the Digital Government Track
Web:
http://hicss.hawaii.edu/tracks-52/digital-government/
<http://hicss.hawaii.edu/tracks-52/digital-government/>
Author instructions and submission details:
http://hicss.hawaii.edu/tracks-and-minitracks/authors/
<http://hicss.hawaii.edu/tracks-and-minitracks/authors/>
Submission Deadline: June 15, 2018 | 11:59 pm HST
Notification of Acceptance/Rejection: August 17, 2018
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The opening of more and more data and the ability to collect more
and more data using low-cost devices enabled by Internet of Things
(IoT) result in a data-driven government. Nevertheless, data is
useless unless it is used to create value from it. For this, data
needs to be shared, processed and analyzed with traditional and
advanced methods towards operational and strategic
decision-making.
Data-driven government refers to sensing and the subsequent
collecting of all kinds of data using machine-readable data
formats. This data can be used for internal purposes, but also for
opening the data to the public to create transparency, and
accountability or to enable participation and even business
innovation. Open data can be combined with all kind of data
sources to infer and generate value. This can result in
recommendations for improving the public sector, business model
innovation and the creation of transparency. These developments
are resulting in drastic changes of the public sector.
The rise of all kinds of data has resulted in the demand for new
approaches for organizing, storing, processing, analyzing,
curating, linking and visualizing results of data. These
approaches all form part of data value chains, which enable data
users to extract value from the data. Although there is a huge
potential, how the exploiting of data should be accomplished and
what is the impact of public organizations is not understood. All
these developments impact the operation of governments and their
relationship with the public. There are changes at the technical,
organizational, managerial and political level that impact the
capabilities needed, the making of policies and traditional
institutional structures.
This minitrack is aimed at discussing theories, methodologies,
experience reports, literature and case studies in the field of
Big & Open Linked Data (BOLD), Information Processing, Data
Analytics, and Data Value in Government. We solicit for papers
covering both organizational and technical aspects and combining
theory and practice. Papers taking interdisciplinary approaches
and covering a multitude of aspects are strongly encouraged.
Furthermore, we promote a diversity of research methods to study
the challenges of this multifaceted discipline including best
practices, case studies, design approaches, literature reviews and
interviews.
Minitrack topics include, but are not limited to:
Open Data Practices, Technologies and Applications in Government
Impact of data-driven government and society on the technical,
organizational and institutional level
Big & Open Linked Data (BOLD)
Metadata and semantic approaches
Data value, data value chains, and data governance
Data analytics, processing, intelligence and visualization
Data-driven strategies and policies
Data quality, privacy, trust and security
Internet of Things (IoT) for data-driven government
Changing relationship between government, private organizations
and society
Methods and technologies leading to enhanced digital public
services
Data-driven public sector innovations and applications
Architectural standards, principles and frameworks
Technical, semantic, organizational, managerial and legal/policy
aspects of interoperability
System development, implementation and agile approaches for
digital public services
System, user, data and process-based integration
Co-creation using data and citizen engagement
Information and cloud infrastructures, shared services, cloud
providers
Reuse and data quality and ownership
Semantic ontologies, web services and modeling for governmental
infrastructures
Cloud computing, Software as service (SaaS), ICT-services,
scalability, reliability, flexibility
Data platforms, interoperability, information sharing and public
business models
Cross-organizational modeling and visualization ranging from the
organizational to technical level
Service-oriented architectures, web services, semantic web
services, orchestration and composition
Citizen-driven and entrepreneurial approaches based on open data
Adoption, failure and success factors and organization of a
data-driven government
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Minitrack Co-Chairs:
Marijn Janssen (Primary contact)
Delft University of Technology
m.f.w.h.a.janssen@tudelft.nl
<mailto:m.f.w.h.a.janssen@tudelft.nl>
Judie Attard
Trinity College, Dublin
judie.attard@adaptcentre.ie
<mailto:judie.attard@adaptcentre.ie>
Charalampos Alexopoulos
University of the Aegean
alexop@aegean.gr <mailto:alexop@aegean.gr>
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