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Application of knowledge graphs for creating a library of reusable knowledge in the smart city domain

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Application of knowledge graphs for creating a library of reusable knowledge in the smart city domain

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Our presentation at the Conference on Digital Curation Technologies (Qurator 2022), Berlin, Germany, Sept. 19th-23rd, 2022.

Abstract
Knowledge reuse can increase the quality and efficiency of different activities, as well as reduce risks. The digital transformation of a city is a complex task that requires new approaches and management technologies. Knowledge reuse can reinforce city digital transformation initiatives, e.g. data integration and modeling activities can be improved via ontology reuse, design and development of digital solutions can be enhanced via reference architectures and reuse of existing methods and systems. Such reuse can speed up the work of city development managers, digital architects, and other ICT specialists, as well as decrease costs and risks. Although there are platforms for knowledge sharing and reuse within the smart city domain, they apply a traditional document-oriented approach to knowledge representation. This limits knowledge integration and the creation of intelligent services. So, knowledge graph technology was selected for collecting and curating digital city planning reusable content. The Open Research Knowledge Graph (ORKG) provided an opportunity for piloting this approach. The current paper will overview the digital city planning observatory within the ORKG, including main knowledge representation mechanisms and representative content examples, and provide the link between content and application scenarios.

For more details see the corresponding paper in the proceedings: http://ceur-ws.org/Vol-3234/paper3.pdf

Our presentation at the Conference on Digital Curation Technologies (Qurator 2022), Berlin, Germany, Sept. 19th-23rd, 2022.

Abstract
Knowledge reuse can increase the quality and efficiency of different activities, as well as reduce risks. The digital transformation of a city is a complex task that requires new approaches and management technologies. Knowledge reuse can reinforce city digital transformation initiatives, e.g. data integration and modeling activities can be improved via ontology reuse, design and development of digital solutions can be enhanced via reference architectures and reuse of existing methods and systems. Such reuse can speed up the work of city development managers, digital architects, and other ICT specialists, as well as decrease costs and risks. Although there are platforms for knowledge sharing and reuse within the smart city domain, they apply a traditional document-oriented approach to knowledge representation. This limits knowledge integration and the creation of intelligent services. So, knowledge graph technology was selected for collecting and curating digital city planning reusable content. The Open Research Knowledge Graph (ORKG) provided an opportunity for piloting this approach. The current paper will overview the digital city planning observatory within the ORKG, including main knowledge representation mechanisms and representative content examples, and provide the link between content and application scenarios.

For more details see the corresponding paper in the proceedings: http://ceur-ws.org/Vol-3234/paper3.pdf

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Application of knowledge graphs for creating a library of reusable knowledge in the smart city domain

  1. 1. Application of knowledge graphs for creating a library of reusable knowledge in the smart city domain Dmitry Kudryavtsev, PhD, Head of methodology and R&D Natalia Chichkova, Knowledge engineer Digital City Planner Oy
  2. 2. 2 Agenda 1. Introduction and motivation 2. Application of knowledge graphs for creating a library of reusable knowledge in the digital city planning domain 3. Overview of the pilot project and ORKG (Open Research Knowledge Graph) 4. Overview of the digital city planning observatory content 5. Application scenarios (current and future) 6. Conclusions
  3. 3. 1. Introduction and motivation 3
  4. 4. Smart city domain A smart city is a municipality that uses information and communication technologies (ICT) to increase operational efficiency, share information with the public and improve both the quality of government services and citizen welfare. Sharon Shea & Ed Burns, TechTarget https://internetofthingsagenda.techtarget.com/definition/smart-city 4
  5. 5. Key Issues for Smart City transformation Transforming a city is a complex task that requires new approaches and management technologies: • Number of tasks, stakeholders, problem-solving ways, and approaches is huge • Life speed is high and increasing: people need the newest innovative technologies and applications • New services for businesses, citizens and the government need to appear 5
  6. 6. City digital transformation actors and activities Actors: • City development managers • Digital transformation teams • Solution providers 6 Activities: • Data integration and modeling • Design and development of city digital solutions and systems • (Re-)Design of public services and processes • Smart city management and development
  7. 7. Knowledge reuse can improve many activities (areas) within a city’s digital transformation 1. Data integration and modeling activities can be improved via the reuse of data models and ontologies, 2. Design and development of city digital solutions and systems can be improved via reference architectures and reuse of existing solutions/systems/methods, 3. (Re-)Design of public services and processes can be improved via the reuse of patterns and reference process models, 4. Smart city management and development can be improved by reusing proven key performance indicators from existing reference models and standards or by reusing existing cutting-edge solutions for city analysis, monitoring, and control (including city digital twins). 7
  8. 8. 8 From problems and opportunities to a knowledge-based solution Problems: 1. Limited access to the world’s best practices and experience in the smart city area 2. The need to hire top/external consultants 3. Lack of a holistic and evidence-based smart city development system Opportunities: There is a lot of reference and reusable content in the smart city domain, such as: • reference models, • ontologies, • data models, • classifications/taxonomies (e.g. of processes or services), • patterns, • good practice cases, • reusable methods and systems. Collect, prepare and pack knowledge for reuse and worldwide replication
  9. 9. 9 Existing solutions and their limitations 1. Broad scope platforms with smart city solutions: • Bee smart city platform (https://www.beesmart.city/) • Bable (https://www.bable-smartcities.eu/) 2. Domain-specific platforms: • Eltis – The Urban Mobility Observatory (https://www.eltis.org/) etc. 3. Platforms for the specific type of content: • Smartcity.linkeddata.es etc. Although these platforms include well-structured libraries of materials, they use the "traditional" approach for knowledge representation: text documents with metadata. Such an approach has limitations in terms of knowledge access, reuse, and applicability for creating intelligent services.
  10. 10. 2. Application of knowledge graphs for creating a library of reusable knowledge in the digital city planning domain 10
  11. 11. 11 Application of knowledge graphs in the smart city domain • Smart city best practices and cases can be accumulated via knowledge graphs in order to make them more findable and reusable. • The city knowledge graph initiatives exist in the world, for example, Zaragoza’s Knowledge Graph. • But the existing city knowledge graph initiatives are mostly related to the collection and integration of smart city data, while we are interested in smart city knowledge reuse.
  12. 12. 12 The suggested solution Collect, prepare and pack knowledge for reuse and worldwide replication Knowledge graph technology Knowledge reuse City’s digital transformation
  13. 13. 3. Overview of the pilot project and ORKG (Open Research Knowledge Graph) 13
  14. 14. 14 A pilot project for creating a library of reusable knowledge for smart city domain “The Open Research Knowledge Graph utilizes the recent progress in information technologies to build the next generation digital libraries for semantic scientific knowledge. We aim to describe scientific knowledge in a structured, machine-interpretable way. This will help researchers find relevant contributions to their field and create state- of-the-art comparisons and reviews” https://www.orkg.org/orkg/about/1/Overview Collect, prepare and pack knowledge for reuse and worldwide replication Publicly available research papers Open Research Knowledge Graph (ORKG) platform provided by the TIB Leibniz Information Centre for Science and Technology Library of reusable knowledge for city digital transformation Curation of the Smart City Planning observatory within the ORKG
  15. 15. 15 Representation of smart city reusable knowledge in the ORKG, key components Research papers Contributions Comparisons Structured description using knowledge graph Reviews
  16. 16. 16 Representation of smart city reusable knowledge in the ORKG, some details
  17. 17. 4. Overview of the digital city planning observatory content 17
  18. 18. 18 Structured Descriptions of Research papers via Contributions (1/2) https://orkg.org/paper/R138642/R138645 A) provides a structured description of a paper, which suggests smart city ontology [14]
  19. 19. 19 Structured Descriptions of Research papers via Contributions (2/2) https://orkg.org/paper/R138187/R138189 B) provides a structured description of a paper, which suggests a recommender system for smart cities [15]
  20. 20. 20 Comparisons as an integration of contributions “Ontologies for smart city: levels and key classes” comparison, which compares the content of 6 smart city ontologies described in the corresponding research papers. It shows and compares classes of the ontologies along 18 levels (e.g. physical level, service level, safety, and risk management level) https://doi.org/10.48366/R215443
  21. 21. 21 Review as integration of contributions and comparisons Smart city's ontologies review Ontologies for smart city: levels and key classes Domain coverage in smart city ontologies Ontology reuse in smart city ontologies Review Comparison 1 Comparison 2 Comparison 3 Approx. 40 Contributions 18 papers
  22. 22. 22 Сity digital transformation information/ knowledge requirements (fragment) City digital transformation activities Questions Data integration and modeling What concepts (objects), domains, layers, dimensions, and relationships can be used for describing a city? Design and development of city digital solutions and systems What are the examples of digital solutions/systems for improving a specific domain or solving a particular problem? Are there any reusable ones? What are the results and outcomes of a solution/system application in smart cities? What methods and approaches are used within the particular solution? (Re-)Design of public services and processes What digital services can be offered to a specific category of citizens or businesses within a particular context (event)? How can services be delivered and implemented? How specific processes can be organized and/or transformed using available technologies? Smart city management and development What indicators can we use for measuring domain X? What city ranking systems exist, and what are the differences between them? What indicators can we use for measuring outcomes, outputs, processes, and inputs in domain X? How to integrate and present city-related data for decision-making? How city digital twins can be used for city management and development?
  23. 23. 23 Overview of the digital city planning observatory content (fragment) Totally the Digital City Planning (DCP) observatory within the Open Research Knowledge Graph (ORKG) includes 296 papers, 32 comparisons, 3 reviews (for 28.01.2022). City digital transformation activities Questions The DCP observatory content at the ORKG Data integration and modeling What concepts (objects), domains, layers, dimensions, and relationships can be used for describing a city? Review: Smart city's ontologies review [17] Comparisons: Ontologies for smart city: levels and key classes [14] Domain coverage in smart city ontologies [18] Design and development of city digital solutions and systems What are the examples of digital solutions/systems for improving a specific domain or solving a particular problem? Comparison: Recommender systems for smart cities, Smart governance dimension [19] Smart city management and development What indicators can we use for measuring domain X? What indicators can we use for measuring outcomes, outputs, process and inputs in domain X? How to integrate and present city-related data for decision making? How city digital twins can be used for city management and development? Review: Smart and sustainable city's indicators [20] Comparisons: Standardized indicators for Smart sustainable cities, by type of indicators [21] Analysis of natural environment indicators in Smart Cities' standards [22] Review: Towards a city digital twin [23] Comparisons: Thematic Identification of the City Digital Twin Potentials [24] Application areas of Digital Twin solutions in the smart city domain [25]
  24. 24. 5. Application scenarios (current and future) 24
  25. 25. 25 Current application scenarios: Faceted search Faceted search for relevant contributions (and corresponding papers) within the ORKG
  26. 26. 26 Current application scenarios: Visual analytics Visualization of the comparison content This example diagram may help to find the most relevant standard with the required types of indicators.
  27. 27. 27 Source data for visualization – the comparison Current application scenarios: Visual analytics
  28. 28. 28 Current application scenarios The specific indicators of a certain type can be taken for reuse from this comparison
  29. 29. 29 Future application scenarios (next steps) A platform for creating and reusing city digital transformation knowledge From cities to organizations in general (cities + commercial organizations) Knowledge producers Knowledge consumers
  30. 30. 30 Conclusions • City (and business) digital transformation can be enhanced via knowledge reuse. • Although there are several platforms for smart city knowledge sharing and reuse, they apply a traditional document-oriented approach to knowledge representation. • Knowledge graphs technology can provide a better way of collecting and curating digital city planning reusable content. • A pilot project of applying knowledge graphs was demonstrated: the curation of the digital city planning observatory within the ORKG. • Such an approach can be scaled into a platform for creating and curating reusable knowledge for digital transformation of cities and commercial organizations
  31. 31. Contacts Dmitry Kudryavtsev dmitry.kudryavtsev@digicityplanner.com Mobile phone/Whatsapp: +358 45 3444329 https://digicityplanner.com/ Lapinlahdenkatu 16, 00180 Helsinki (Maria 01) 31

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