The document discusses establishing a science base for digital governance through identifying key components and artifacts. It proposes that digital governance can be considered a science if independent experts analyzing the same problem arrive at the same diagnosis and proposed solutions. Components of a digital governance science base include a domain structure, research roadmap, knowledge base, problem space analysis, assessment tools, and solution methods. Neighboring domains that could inform its development include ICT, management science, political science, economics, and law. Assessments methods may evaluate levels of service transactions or apply indicators and evaluation methodologies. Establishing standardized components and relationships between problems and solutions aims to formalize digital governance as an evidence-based field.

1. ERASMUS+
Knowledge Alliance
Scientific foundations training and
entrepreneurship activities in the domain of ICT –
enabled Government
Workshop IV on Science Base Creation in
Digital Governance
Yannis Charalabidis, University of the Aegean
Zoi Lachana, University of the Aegean

2. Workshop Objectives
§ The main focus of this workshop is to identify the setup of a science base based on a
specific methodology, deliberation and consensus.
§ Identify the prominent artifacts in each component
§ How ?  by creating a structure to establish the scientific foundations of Digital Governance
which is expected to be evolved over time
§ Why ?  in order to formalize the problems so digital government experts will provide
solutions within specific patterns and tools
The Charalabidis Test
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3. The “Charalabidis Test” on Digital Governance
Science Base
Digital Governance is a science if:
Whenever 2 independent, randomly selected Digital Governance experts (practitioners or DG
science) are exposed to the same administration situation – problem, and working separately,
they:
 Come to the same diagnosis for the situation – problem of the administration (from a technical,
semantic, organizational, legal and policy or other aspects)
 Propose the same set of actions so that the administration will reach the desired state.
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4. Why?
§ There are hints, since Plato times, that governance has to be treated as a science (Plato,
Politikos: “… the science of governance, this most difficult but also the most important of all …”
§ There are a lot to be gained, by systematically organizing knowledge and practice in this
important domain, for administration and societies (time, cost, quality of life)
§ The convergence of the governance science with other, formulated scientific domains like
computer science, or management science or law, brings more value to the experiment
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5. Software Engineering Science Base
§ Software Engineering (SE) started as a practice.
§ It is recognized as a sub domain of computer science
§ The broad set of notations, tools and analysis techniques of SE provide guidance for complex software design
and development.
HOW?
Through the following 6 typical phases:
1. Basic research
2. Concept formulation
3. Development and extension
4. Internal enhancement and exploration
5. External enhancement and exploration
6. Popularization
(Redwine, W. RiddleSoftware technology maturation, Proceedings of the 8th International Conference on Software Engineering, IEEE CS Press (1985), pp. 189-200)
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6. Previous Work – Enterprise Interoperability
Science Base
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Charalabidis, Y. (Ed.). (2014). Revolutionizing enterprise interoperability through scientific foundations. IGI Global.

7. Digital Governance Science Base
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-Rationale
-Structure of the
Domain in areas
(appr. 100)
-Research Roadmap
-Neighboring
domains (e.g.
management,
political science, ICT,
etc)
-Training curricula and
material
-Problem space
analysis
-Assessment tools
and methods
-Solution paths (best
practices and cases
knowledge)
-Solution methods
and tools
A. Ontology and
Evolution (why,
what)
B. Scientific
practice
(observation,
hypothesis, how)

8. Digital Governance Science Base – Our
view
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Laws / Rules/Theories
WHY
WHAT
HOW
Research Roadmap
Domain
Structure (Areas)
Neighboring
Domains
Training
Curricula

Solution Paths
Knowledge Base
(cases)
Ontology,
Evolution
Problem Space
(Diagnosis)
MultidimensionalVector
Assessment
Methods &Tools
Solution Methods
&Tools

Rationale

9. Digital Governance Science Base
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§ Neighboring Domains
 Recognized interdependencies among Digital Governance and other scientific
disciplines
 Digital Governance needs to be analyzed together with a selection of established
and emerging sciences amongst the neighboring scientific domains that can inspire
the development of the scientific base

10. Digital Governance Science Base - Neighboring
Domains
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Digital Governance
ICTs Management Science
Societal Sciences &
Humanities
Political ScienceEconomics
Law Science

11. From the Problem Space to the Solution
Path
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As-is situation
Taxonomy of
recognized
problems
Fit to the
specific
problem
typology
Recognize
Problem –
Solution Paths
Utilize
Appropriate
solutions
To-be situation
Problem Space Solution Path
Iterative Process
Multidimensional
Vector

12. Examples: From the Problem Space to the Solution
Path
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Problems / Issues Typology Possible Solutions
Data Standards Incompliance Interoperability Unified data schemas
Data Standardisation
Openness: publish open data Open data (e.g.
Tim Berners Lee
Stage Model)
Open and free flow of information
DCAT compliance
URI
Linked data
Openness: citizens sentiment
analysis
Social Media Facebook channel for communication
Facebook channel for opinions
Social Impact measurement Social Media
Open Data
Application of developed financial and public
opinion models
Pro-active government Interoperability ProcessAlignment etc.
Unified data schemas
ESB creation

13. Assessments Methods & Tools
Examples
§ 5 levels of services transactions
 Information
 Interaction
 Two-way interaction
 Transaction,
 Targetization, Personalization
§ Maturity Models
 Andersen, K. V., & Henriksen, H. Z. , 2006
 Layne and Lee Maturity Model, 2001
 United Nations Maturity Model, 2012
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14. Assessments Methods & Tools
§ Established Indicators - Evaluation Methodologies
 DESI (Digital Economy & Society Index)
 eGov Factsheet
§ Research Theories
 Structuration theory
 Theory of planned behavior
 Theories of trust
§ Application of new technologies in addressing current problems / new ways of
service provision
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15. § Q1: Can you identify more components in the Digital Governance
Science Base?
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16. § Q2: What other Neighboring Domains would you like to include?
 Can we set up their priorities and topics?
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17. § Q3: What other «Assessments Methods & Tools» would you
recommend for Digital Governance Science Base?
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18. Contact us:
 Website: https://gov30.eu
 Twitter: @Government_30
Yannis Charalabidis
Zoi Lachana