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DGSB Domain Structure samos2020summit

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DGSB Domain Structure samos2020summit

  1. 1. Workshop Digital Governance Science Base: Domain Structure and Neighboring Domains Yannis Charalabidis Professor of Digital Governance University of the Aegean yannisx@aegean.gr Zoi Lachana Researcher, Ph.D. Candidate University of the Aegean zoi@aegean.gr Panos Keramidis Student University of the Aegean icsd16067@icsd.aegean.gr
  2. 2. PART A INTRODUCTION TO DGSB INITIATIVE (Workshop number #09 on the subject)
  3. 3. Why do we need a “science base” for Digital Governance?  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: minimization of solution time and cost, maximization of administration productivity, avoidance of failure, better quality of life for citizens  The neighboring of the Digital Governance domain with other, well – formulated scientific domains like computer science, management science or law, brings more value to the experiment
  4. 4. When will Digital Governance be considered a scientific domain ? An example ? How to test if we have a method The “Yannis Test” on Digital Governance Science Base Digital Governance is a well-structured and manages scientific domain, 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. Input from epistemology and various DGSB workshops says: “Science means METHOD, defined, applied and evolving in a systematic way”
  5. 5. What are the elements of the Science Base ? Rationale (justifications on the need for a science base supported by evidence) WHY
  6. 6. What are the elements of the Science Base ?  Research Roadmap (new research directions, evolution scenarios) Domain Structure (ontology of scientific areas, sub-areas, terms, sectors, etc) Neighboring Domains (domains, “points of connections”, structure, tools, methods, ideas, laws, etc) Training Curricula (training programmes, training courses, material) WHAT Solution Space (solution paths, cases, knowledge base of successes and failures) Problem Space (problem classifications, multidimensional vector definitions) Assessment Tools (assessment frameworks, assessment tools, KPI’s) Solution Methods & Tools (frameworks, methodologies, toolsets, applications, algorithms) HOW Rationale (justifications on the need for a science base supported by evidence) WHY
  7. 7. What are the elements of the Science Base ?  Research Roadmap (new research directions, evolution scenarios) Domain Structure (ontology of scientific areas, sub-areas, terms, sectors, etc) Neighboring Domains (domains, “points of connections”, structure, tools, methods, ideas, laws, etc) Training Curricula (training programmes, training courses, material) WHAT Solution Space (solution paths, cases, knowledge base of successes and failures) Problem Space (problem classifications, multidimensional vector definitions) Assessment Tools (assessment frameworks, assessment tools, KPI’s) Solution Methods & Tools (frameworks, methodologies, toolsets, applications, algorithms) HOW Rationale (justifications on the need for a science base supported by evidence) WHY
  8. 8. What are the elements of the Science Base ?  Research Roadmap (new research directions, evolution scenarios) Domain Structure (ontology of scientific areas, sub-areas, terms, sectors, etc) Neighboring Domains (domains, “points of connections”, structure, tools, methods, ideas, laws, etc) Training Curricula (training programmes, training courses, material) WHAT Solution Space (solution paths, cases, knowledge base of successes and failures) Problem Space (problem classifications, multidimensional vector definitions) Assessment Tools (assessment frameworks, assessment tools, KPI’s) Solution Methods & Tools (frameworks, methodologies, toolsets, applications, algorithms) HOW The big picture (Rules, Theories, Laws) Rationale (justifications on the need for a science base supported by evidence) WHY The correct application (Code of Ethics)
  9. 9. Comparing Digital Governance and Medical Science
  10. 10. PART B ON DIGITAL GOVERNANCE DOMAIN STRUCTURE (Workshop number #03 on the subject)
  11. 11. On DG Domain Structure : Characteristics DG Domain Structure is a Key Element of DGSB There are lexicons (many) / taxonomies (several) / ontologies (few) of how DG domain is structured : Our approach should be inclusive The DG domain structure is expected to evolve over time : We should plan for this evolution (collaborative tools, flexibility) The domain structure should be simple but also convincingly deep if need (allow for different levels of analysis / abstraction) There will always be different views on some issues, by experts of the domain (allow myriads of different viewpoints)
  12. 12. Domain Structure - Areas  An Area corresponds on a specific topic of the domain (e.g. interoperability, open data)  An area can be analysed in sub-areas, at an infinite level  The view of Areas as a tree corresponds to the Digital Governance Area Taxonomy  All areas have title, definition(s), links, etc Upper Level Interoperability Legal Interoperability Organisational Interoperability Semantic Interoperability Technical Interoperability Lower Levels
  13. 13. Domain Structure - Streams  Streams are elements where Areas are classified into (Streams and Areas are orthogonal / they do not share common terms)  Each Area is connected (belongs to) one or more Streams.  Streams correspond but also enlarge to Information Systems elements – Process & Regulation: series of activities, rules, or regulations controlling efforts to achieve a desired outcome or goal – Data: semantic elements, raw or organized information of any type and form – People: the human element, users, citizens, employees, etc – Infrastructure: a rage of technologies, systems, devices and applications, a combination of software, hardware, networks etc. (including all IT related equipment) – Intelligence: specific combinations of processes, data, people and infrastructure that simulates properties of the human mind.
  14. 14. Streams and Areas Example Areas Process (& Regulation) Data People Infrastructure Intelligence Digital Public Services XX Business Process Reengineering XX Dynamic Workflow Automation XX X Organisational Interoperability XX Semantic Interoperability X XX Technical Interoperability X XX Digital Identity (e-ID) X X XX Digital Security X X XX Service Portals XX Mobile applications X XX Metrics X XX Cloud Infrastructures X X XX e-Participation XX X e-Voting X XX X Open Governmental Data XX X X Linked Data XX X X X e-Collaboration X XX X Big Data Processing XX X X Visual Analytics X XX X Social Media X XX X Extract of the Areas Taxonomy STREAMS
  15. 15. Additional Domain Structure Elements Generations are identifiers of big movements in Digital Governance (e.g. Gov 1.0, Gov 2.0, Gov3.0), each including several Areas. Each area belongs to one or more Generations Collectives are arbitrary, well-coined and recognized, identifiers that act as sets of Digital Governance Areas (e.g. Smart Cities, which contains several Areas). Verticals are sets of Areas in the same sector of the economy or society (e.g. eHealth, eJustice, etc / each containing several Areas) Sectors are well-known economy or society sectors, where verticals are classified
  16. 16. The DG Domain Structure is a 6-Dimensional Space An Example ? Smart Cities / Service Automation Collectives Area Service Portals Stream Infrastructure Generation Gov 1.0 Vertical eHealth eJustice Health Security & Justice & several more Sectors
  17. 17. Digital Governance Domain Structure – Sneak Peek Streams Generations Collectives Verticals Areas Process (& Regulation) Data People Infrastructure Intelligence Gov 1.0 Gov 2.0 Gov 3.0 Smart Cities Data-driven Entrepreneurs hip Service Automation eHealth /Health Informatics eJustice /Legal Informatics eFinance Digital Public Services XX X X Business Process Reengineering XX X X Dynamic Workflow Automation XX X X X Organisational Interoperability XX X X Semantic Interoperability X XX X X Technical Interoperability X XX X X X Digital Identity (e-ID) X X XX X X X Digital Security X X XX X X Service Portals XX X X X X X Mobile applications X XX X X X X Metrics X XX X Cloud Infrastructures X X XX X X e-Participation XX X X e-Voting X XX X X Open Governmental Data XX X X X X X Linked Data XX X X X X X e-Collaboration X XX X X X Big Data Processing XX X X X X X X X Visual Analytics X XX X X Social Media X XX X X Artificial Intelligence X X X XX X X Blockchain X XX X X X Internet of Things X XX X X X X X Policy modelling & simulation X XX X Opinion Mining & Sentiment Analysis X XX XX X Service API-fication X XX X X X Text Mining X X XX X X X Evidence-based decision making XX X X XX X Sectors Law and Justice X Health X Education and Research Entrepreneurship & Development Labor & Social Security Economy & Finance X Internal Affairs Transportation Culture and Tourism Environment and Natural Resources External Affairs Public Safety
  18. 18. Next Steps Continue the analysis of the Domain Structure through: – Analysis of the Digital Governance Literature (DGRL - scientific papers) – Tracks of Digital Governance Conferences – Works of esteemed DG Authors – Several google/scopus/wsi queries Identification of the connections among the elements of the domain structure setting up their dependencies Community building to observe different point of views of the Domain Structure Development of various ontologies for Digital Governance terms Tools for manVisualisation
  19. 19. PART C DGSB NEIGHBORING DOMAINS (Workshop number #05 on the subject)
  20. 20. Neighboring Domains Digital Governance Computer Science, Information Systems Technology Management Science, Business Management and public administration Economics, Digital Economy Geography Psychology Social Science & Humanities, Sociology Philosophy/ ethics Political Science Development Theory Law Science These 10 neighboring domains are the results of many deliberations such as DG.O, ICEGOV, ICIS, EGOV- CeDEM-ePart, Samos Summit
  21. 21. Neighboring domains are adjacent to specific parts of the DG Domain Structure Digital Governance • Social Media Business Process Reengineering • Blockchain • Text Mining Social Science & Humanities, Sociology Management ScienceComputer Science, Information Systems Technology • Opinion Mining & Sentiment Analysis Economics, Digital Economy
  22. 22. Next Steps : The Domain / Neighboring Domains matrix A Cartesian Product (at least 10x100) analysing proximity of neighboring domains to DG areas Areas Social Media Digital Identity (e- ID) Policy modelling & simulation Opinion Mining & Sentiment Analysis Text Mining Open Governmental Data Business Process Reengin eering Blockchain … (70) Computer Science, Information Systems Technology Management Science Economics, Digital Economy Geography Psychology Social Science & Humanities, Sociology Philosophy/ ethics Political Science Development Theory Law Science Neighboring Domains
  23. 23. Next steps: Relating Neighboring Domains to DGSB Elements HOW Problem Space (problem classifications, multidimensional vector definitions) Solution Space (solution paths, cases, knowledge base of successes and failures) Assessment Tools (assessment frameworks, assessment tools, KPI’s) Solution Methods & Tools (frameworks, methodologies, toolsets, applications, algorithms) Case: Interoperability Neighboring Domains:  Social Science  Law Science  Economics  Management Science  Computer Science
  24. 24. PART D THE QUESTIONNAIRE (Workshop number #04 on the subject)

Editor's Notes

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