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Smart cities no ai without ia


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How to build Smart Cities? no AI without IA

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Smart cities no ai without ia

  1. 1. How to build Smart Cities No AI without IA
  2. 2. A few housekeeping items • This webinar is in broadcast mode all participants are muted • Please put your questions in the GoToWebinar panel and we’ll answer as many as we can in the Q & A session • This broadcast is being recorded – replay information will be sent to all registrants following the broadcast
  3. 3. Who is speaking today? Martin Kaltenböck CFO Semantic Web Company Fredric Landqvist Principle Information Strategist & Researcher Findwise Sebastian Gabler Sales Engineer Semantic Web Company
  4. 4. Agenda • Introduction to theme • Semantic Information Platform • Case & Tools • Take away • Q&A
  5. 5. The Cognitive Revolution
  6. 6. Smart City
  7. 7. Content
  8. 8. CONFIDENTIAL Organising
  9. 9. Challenges
  10. 10. Landfill
  11. 11. Lingua Franca              
  12. 12. Standing on the shoulders of Giants No AI without IA Newton ShannonBayes TuringAl Kindi Ada Wolfram
  13. 13. The bright side of the road
  14. 14. CONFIDENTIAL We are the People! Trust Belonging
  15. 15. Tools for a smart platform
  16. 16. Martin Kaltenböck CFO & Managing Partner Semantic Web Company / PoolParty Semantic Suite PoolParty Semantic Suite Webinar 19.06. 2018 No AI without IA
  17. 17. Introduction The Evolution of the Internet…. well as of Data & Information Management 18
  18. 18. Core Principle The Semantic Layer completes the Four-layered Data & Content Architecture 19
  19. 19. Core Principle From Strings to Things... 20
  20. 20. PoolParty Semantic Suite Most complete Semantic Middleware on the Global Market 21 Bain Capital is a venture capital company based in Boston, MA. Since inception it has invested in hundreds of companies including AMC Entertainment, Brookstone, and Burger King. The company was co-founded by Mitt Romney. Taxonomy & Ontology Server Entity Extractor & Semantic Classifier Data Integration & Data Linking Unstructure d Data Semi- structured Data Structured Data Unified Views PoolParty GraphSearc h Identify new candidate concepts to be included in a controlled vocabulary Controlled vocabularies as a basis for highly precise knowledge extraction and text classification Entity Extractor informs all incoming data streams about its semantics and links them Schema mapping based on ontologies RDF Graph Database Factshee t
  21. 21. Knowledge Graphs as a Data Model for Machine Learning Download: Semantic AI White Paper These transformations can result in loss of information and introduce bias. To solve this problem, we require machine learning methods to consume knowledge in a data model more suited to represent this heterogeneous knowledge. We argue that knowledge graphs are that data model. Three examples for the benefits of using knowledge graphs: ▸ they allow for true end-to-end-learning, ▸ they simplify the integration of heterogeneous data sources and data harmonization, ▸ they provide a natural way to seamlessly integrate different forms of background knowledge. Wilcke X, Bloem P, De Boer V. The Knowledge Graph as the Default Data Model for Machine Learning. Data Science. 2017 Oct 17;1-19. Available from, DOI: 10.3233/DS-170007 22 Traditionally, when faced with heterogeneous knowledge in a machine learning context, data scientists preprocess the data and engineer feature vectors so they can be used as input for learning algorithms (e.g., for classification).
  22. 22. Our Solution Approach Why PoolParty? ▸ Future-proof investment & data portability Fully standards-compliant ▸ Middleware approach Easy integration based on comprehensive API ▸ Shorter learning curve Outstanding user-friendliness & E-learning ▸ Technological lead Machine Learning, NLP and Semantics ▸ Modular architecture & price model Adapt to growing demands 23 The Most Complete Semantic Middleware on the Global Market PoolParty enables enterprise- ready solutions based on cutting-edge technologies.
  23. 23. PoolParty Semantic Suite Re-use existing models & standards and link them... 24
  24. 24. How to start? The Semantic Web Starter Kit 25 kit/
  25. 25. PoolParty Semantic Suite TRY OUT NOW! 26 Get your PoolParty test account: Learn more:
  26. 26. Martin Kaltenböck CFO, Semantic Web Company ▸ ▸ ▸ ▸ 10-13 September 2018 Connect... 27 © Semantic Web Company - and
  27. 27. Fact sheet: Semantic Web Company 28 Semantic AI Semantic Web Company (SWC) ▸ Founded in 2004, based in Vienna ▸ Privately held ▸ 45+ FTE ▸ Consulting Experts in NLP, Semantics and Machine learning ▸ Developer & Vendor of PoolParty Semantic Suite ▸ 2.5 Mio Euro funding for R&D ▸ ~30% revenue growth/year ▸ SWC named to KMWorld’s ‘100 Companies That Matter in Knowledge Management’ in 2016, 2017 and 2018 ▸
  28. 28. Sebastian Gabler Consultant Semantic Web Company / PoolParty Semantic Suite No AI without IA Use case - trusted health information in Australia
  29. 29. The HealthDirect use case ▸ HealthDirect is a platform of the public health services for Australia ▸ Digital platform established on PoolParty 2013 ▸ Information Architecture for trusted health information ▸ W3C standards based information format ▸ Integration of public vocabularies, such as Drugbank, MeSH, IDC-10 and GIS information ▸ Services include Australian Health Thesaurus, Symptom Checker, and Semantic Search 30
  30. 30. Mission Statement: Ensuring all Australians have access to the right advice on the appropriate care for their health issue when they need it and where they need it.
  31. 31. Technical Platform
  32. 32. Used components: PoolParty Thesaurus Server (PPT) ● Vocabulary server to manage taxonomies and thesauri ● Use, manage and publish linked data and large enterprise knowledge graphs ● Based on standardized linked data technologies PoolParty Extractor (PPX) ● Scalable, high availability ● Powerful entity extractor and text mining service PoolParty API Enterprise Server
  33. 33. Development of the Australian Health Thesaurus • Department of Health Thesaurus • Local thesauri/taxonomies • Symptom Check • International thesauri/taxonomies • MeSH • DSM-V • ICD10 • Common search terms (Google Analytics) • Search terms with no results (Hitwise) • Across health information industry • Ongoing maintenance App. 10000 changes since Feb 2014
  34. 34. Conversion of taxonomies
  35. 35. Using the knowledge graph for semantic search … use the relationships … use the labels
  36. 36. Content publication process
  37. 37. Get in touch Sebastian Gabler Consultant, Semantic Web Company ▸ ▸ ▸ 38 © Semantic Web Company - and
  38. 38. Smart City - journey The city as a platform Models, challenges, effects and solutions
  39. 39. Digitalisation @ Göteborg 40HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN
  40. 40. 41HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN Sustainable Data Management
  41. 41. City Information Model 42HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN •Urban Environment •Movable Objects •Human Actor Networks •Virtual Urban Systems
  43. 43. Urban Environment 44HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN •Physical spaces, and things •Geo Data •BIM and beyond
  44. 44. Movable Objects 45HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN •Mobile Sensor Platforms •City Dynamic Data flows •FiWare and more… for interoperability
  45. 45. Human Actor Networks 46HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN •The City Public services as a platform •Interplay with citizens, business, visitors and more
  46. 46. Virtual Urban Systems 47HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN • Model data • Co-creation
  47. 47. Participation and city models 48HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN
  48. 48. 49 Standards, Domain, Exchange, interoperability Standard Domain Exchange
  49. 49. Gothenburg #smart data pilot ● Terms, terminologies, and reference data (SKOS ,W3C, Simple Knowledge Organising System) ○ Code System, Taxonomies, Glossaries, Thesauri, Ontologies ○ Integrated Public Service Vocab (ISPV), EUROVOC and more ● Workbench, manage object (with properties) and domain-models ( RDF-scheme, alt Web Ontologies, OWL) ○ ISA2 Core Vocabularies, W3C Organisation Ontology, Location, Inspire Spatial Data , FiWare and more models ● Quality data through use of open standards, and models reaching interoperability, and effective information management.
  50. 50. Interoperability for Public Administration (ISA2 ) 51HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN
  51. 51. Information flow 52HÅLLBAR STAD – ÖPPEN FÖR VÄRLDEN
  52. 52. Terminologies (SKOS) Reference data Glossaries, code systems Open standards, taxonomies. thesauri
  53. 53. Models and entities ● Master data entities from standards as ISA2 core vocabularies ● Person (individuals) ● Organisation (entities with vat.nb) ○ Enhet (OrgUnit) ● Place (address alt geo-code) ● Location, spatial area ● Service, (internal/external) [CPSV-AP]
  54. 54. Person ● A model to cover all type of person types. ● A individual have several facets (member of staff, citizen, pupil, politician etc) ● A member of staff might have multi employments, and roles.
  55. 55. Organisation ● Organisation is the super class that define any organisation, that the municipality interact with. ● Organisation is classificied with SNI-code (NACE) ● All organisations are linked to organisational unites. There are also inter-linking between organisations in networks.
  56. 56. Enhet (orgUnit) ● A municipality have a multitude of organising principles, as governance, political steering, city parts, departments, sectors, areas, and groups ● The organisation have many hierarchical levels, as well as links into a network (graph) ● Org Units provision many services ● A Unit can also be acting out of many places.
  57. 57. Place and area ● Place is either a address, or a geographical position where a Unit provision services. ● All places are part spatial areas, or geographical locations, as postal code, city part, area etc.. ● Locations is managed with the cities GIS-systems, with unique identifiers and spatial services.
  58. 58. Service ● Service either serve the public or internal workflows ● The data model used is Core Public Service Vocabulary – Application Protocol CPSV-AP ● A service might either be physical or virtual (e-service). ● A service isPartof Offer ● The provision of service is in-built in supporting information systems.
  59. 59. Utility of #smart data ● Information management with smart data platform: ○ Asynchronous (enterprise service bus) via informations contrakt v using the integration engine ○ Syncronous via RestfulAPI or SPARQL ○ Visualisation in a graph ● Independent if the actor is another system or an individual, the service opens up to many ways to interact, and re-use the information in interoperatible manner.
  60. 60. Graph visualisation
  61. 61. 63 • Founded in 2005 • 120+ employees • Vendor independent consultants • Sweden, Denmark, Norway, Finland, Poland & UK
  62. 62. 64 INFORMATION
  63. 63.
  64. 64. Take Away Guardrails for sustainable #smart cities development
  65. 65. Q & A Thank you for attending We’ll take questions now
  66. 66. AILife 3.0 and beyond…(governing principles) Introducing Semantic AI Semantic Web Starter Kit PoolParty Academy (online trainings) SEMANTiCS2018 conference (10-13.9.2018, Vienna)