Description

Contemporary societies are characterized from the dramatic explosion of digital data (big, open and linked) in the public and private sector. The opening of more and more data and the ability to collect them using low-cost devices enabled by Internet of Things (IoT) constitute a changing force towards 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 newest generation of e-government calls for automated and evidence-based decision making and policy support. Artificial Intelligence (AI) and associated algorithms support this new vision of data-driven government dealing with the vast amount of data and their associated devices, such as Internet of Things (IoT) applications. AI techniques have been extensively used to support and enhance the quality of decision making and complex problem solving in different industries for many years through the exploitation of various types of machine intelligence, including natural language comprehension, robotics, expert systems, neural networks and machine learning.

On the other hand, the rise of all kinds of data including text 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. Moreover, the application of AI in e-government posse numerous ethical and legal considerations. Ethics and responsible research is now of major importance for the utilization of artificial intelligence in e-government that shapes the future of our democratic societies.

This minitrack is aimed at discussing theories, methodologies, experience reports, literature and case studies in the field of Big & Open Linked Data (BOLD) Processing and Analysis through Artificial Intelligence techniques, towards Policy Analytics, automated Decision-Making and Value creation 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.

Submission Deadline: 15 June 2019

Read more @ HICSS2020