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Chapter1- intro to policy making in the digital Age
Chapter2-Educating Public managers and policy analysts in the
era of informatics
Chapter3-The Quality of social simulation: An example from
research policy modeling
Chapter Goals and Objectives
Overall – students will learn and understand why:
▪ the explosive growth in data, computational power, and social
media create new opportunities for innovating governance and
policy-making ▪ global information and communications
technology (ICT) developments affect policy-making cycle and
result in drastic changes in the policy development
▪ organizations need the digital developments, new approaches,
concepts, instruments, and methods as they operate in the
complex and uncertain societies
▪ e-government policy, e-policy, policy informatics, and data
science are different
1. Intro to Policy-Making in the Digital Age
❖ Identification of complexity and uncertainty in policy-making
▪ policy-making is driven by the need to solve societal problems
❖ Developments
▪ developments that influence the traditional way of policy-
making
❖ Availability of Big and Open Linked Data (BOLD)
▪ Learn and understand the needs for multiple perspectives to
stimulate new practices
❖ Rise of hybrid simulation approaches
▪ allows decision-makers to understand the essence of a
policy…
❖ Ubiquitous user engagement
▪ considerable complexities encountered in the design of public
policy
❖ Combining disciplines in e-government policy-making
▪ practice driven, employs modeling techniques, needs
knowledge from various fields, and maintains focus on
governance and policy-making
2. Why educate public managers and policy analysts in the era
of informatics
❖ Types of practitioner orientations to policy informatics
▪ two “ideal types” of policy informatics practitioner, require
greater and greater levels of technical mastery of analytics
techniques and approaches
❖ Policy informatics-savvy public managers
▪ need to know what kinds of questions that policy informatics
projects or programs can answer or not answer
▪ need to know how to contract with and/or manage data
managers, policy analysts, and modelers
❖ Second type of practitioners – policy informatics analysts
▪ need for policy analysts – move beyond basic surveys of
research methods
❖ Applications to professional masters programs
▪ PA 301: Foundations of Public Administration
▪ PA 306: Policy Systems ▪ PA 308: Decision-Making Models ▪
PA 317: Systems Analysis and Strategic Management
3. The quality of social simulation: An example from research
policy modeling
❖ Communicative skills, patience, willingness to compromise
▪ policy-making is driven by the need to solve societal
problems
❖ Quality in social simulation
▪ develop models from a simulation as “an illusory appearance
that manages a reality effect” (cf. Norris 1992)
❖ Assessing quality: the example – the SKIN approach
▪ policy modeling of SKIN – birth of the SKIN inspired by the
idea of bringing theory on innovation networks stemming from
innovation economics and economic sociology, onto the
computer— a computer theory instantiated, calibrated, tested,
and validated by empirical data
❖ INFO-SKIN – the constructivist view
▪ ability to use scenario-based modeling as a worksite for
“reality constructions
❖ INFO-SKIN – the user community view
▪ stakeholders must learn about the scope and applicability of
the methods; researchers get acquainted with the problems
policy makers have to solve

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  • 1. Chapter1- intro to policy making in the digital Age Chapter2-Educating Public managers and policy analysts in the era of informatics Chapter3-The Quality of social simulation: An example from research policy modeling Chapter Goals and Objectives Overall – students will learn and understand why: ▪ the explosive growth in data, computational power, and social media create new opportunities for innovating governance and policy-making ▪ global information and communications technology (ICT) developments affect policy-making cycle and result in drastic changes in the policy development ▪ organizations need the digital developments, new approaches, concepts, instruments, and methods as they operate in the complex and uncertain societies ▪ e-government policy, e-policy, policy informatics, and data science are different 1. Intro to Policy-Making in the Digital Age ❖ Identification of complexity and uncertainty in policy-making ▪ policy-making is driven by the need to solve societal problems ❖ Developments ▪ developments that influence the traditional way of policy- making ❖ Availability of Big and Open Linked Data (BOLD) ▪ Learn and understand the needs for multiple perspectives to stimulate new practices ❖ Rise of hybrid simulation approaches ▪ allows decision-makers to understand the essence of a
  • 2. policy… ❖ Ubiquitous user engagement ▪ considerable complexities encountered in the design of public policy ❖ Combining disciplines in e-government policy-making ▪ practice driven, employs modeling techniques, needs knowledge from various fields, and maintains focus on governance and policy-making 2. Why educate public managers and policy analysts in the era of informatics ❖ Types of practitioner orientations to policy informatics ▪ two “ideal types” of policy informatics practitioner, require greater and greater levels of technical mastery of analytics techniques and approaches ❖ Policy informatics-savvy public managers ▪ need to know what kinds of questions that policy informatics projects or programs can answer or not answer ▪ need to know how to contract with and/or manage data managers, policy analysts, and modelers ❖ Second type of practitioners – policy informatics analysts ▪ need for policy analysts – move beyond basic surveys of research methods ❖ Applications to professional masters programs ▪ PA 301: Foundations of Public Administration ▪ PA 306: Policy Systems ▪ PA 308: Decision-Making Models ▪ PA 317: Systems Analysis and Strategic Management 3. The quality of social simulation: An example from research policy modeling ❖ Communicative skills, patience, willingness to compromise ▪ policy-making is driven by the need to solve societal problems ❖ Quality in social simulation
  • 3. ▪ develop models from a simulation as “an illusory appearance that manages a reality effect” (cf. Norris 1992) ❖ Assessing quality: the example – the SKIN approach ▪ policy modeling of SKIN – birth of the SKIN inspired by the idea of bringing theory on innovation networks stemming from innovation economics and economic sociology, onto the computer— a computer theory instantiated, calibrated, tested, and validated by empirical data ❖ INFO-SKIN – the constructivist view ▪ ability to use scenario-based modeling as a worksite for “reality constructions ❖ INFO-SKIN – the user community view ▪ stakeholders must learn about the scope and applicability of the methods; researchers get acquainted with the problems policy makers have to solve