From Research to Innovation: Linked Open Data and Gamification to Design Intelligent Learning Environments
- 1. NEES/IC and CAED/ICMC Federal University of Alagoas and University of São Paulo igbittencourt.com and isotani.caed-lab.com Ig Ibert Bittencourt and Seiji Isotani From Research to Innovation: Linked Open Data and Gamification to Design Intelligent Learning Environments
- 2. Brasil
- 3. Brasil
- 4. Maceió
- 8. NEES/IC e CAED/ICMC Federal University of Alagoas e University of São Paulo igbittencourt.com and isotani.caed-lab.com Ig Ibert Bittencourt e Seiji Isotani From Research to Innovation: Linked Open Data and Gamification to Design Intelligent Learning Environments
- 9. Linked Open Data Standardization effort and JOINT Gamification and MeuTutor
- 10. Linked Open Data Standardization effort and JOINT Gamification and MeuTutor
- 16. The Semantic Web Stack
- 17. The (new) Semantic Web Stack
- 18. The (new) Semantic Web Stack (with a Linked Data view)
- 33. “International alliance that provides a platform for domestic reformers committed to making their governments more open, accountable, and responsive to citizens”. OPEN GOVERNMENT PARTNERSHIP
- 35. Publish Consume
- 36. 1.06%
- 37. (Low Quality and Unlinked) Publish Consume
- 39. 188 tools
- 40. (Low Quality and Unlinked) Publish (Complex and Time-Consuming) Consume
- 41. Publish Consume How to better data on the Web?
- 42. Linked Open Data Standardization effort and JOINT Gamification and MeuTutor
- 44. Best Practices • URI Design • Use of vocabs to improve interoperability • Publishing and accessing versions of datasets • Reuse of vocabs and datasets Data Usage Vocab • To describe how to use a dataset • To know where and how data has been used by applications • To support discoverability of applications Quality and Granularity Vocab • To cover the quality of the data • To extend DCAT vocab • To foster trust amongst data consumers (e.g. developers) Data on the Web Best Practices Working Group Charter
- 45. Data on the Web Best Practices Working Group Charter Use Cases Challenges Requirements Best Practices Vocabulary
- 46. Data on the Web Best Practices Working Group Charter
- 47. Data on the Web Best Practices Working Group Charter
- 48. Data on the Web Best Practices Working Group Charter
- 49. Data on the Web Best Practices Working Group Charter
- 50. Data on the Web Best Practices Working Group Charter
- 51. Data on the Web Best Practices Working Group Charter Use Cases Challenges Requirements Best Practices Vocabulary
- 52. Best Practices • URI Design • Use of vocabs to improve interoperability • Publishing and accessing versions of datasets • Reuse of vocabs and datasets Data Usage Vocab • To describe how to use a dataset • To know where and how data has been used by applications • To support discoverability of applications Quality and Granularity Vocab • To cover the quality of the data • To extend DCAT vocab • To foster trust amongst data consumers (e.g. developers) Data on the Web Best Practices Working Group Charter
- 53. Linked Open Data Standardization effort and JOINT Gamification and MeuTutor
- 54. Publish Consume How to better data on the Web?
- 56. 188 tools
- 57. RDF Triples Paradigm OO Paradigm
- 58. JOINT
- 59. Ig Ibert Seiji Isotani Armando Barbosa Williams Alcantara Judson Bandeira Endhe Elias Holavo Olanda JOINT: Java Ontology Integrated Toolkit
- 60. + JOINT: Java Ontology Integrated Toolkit
- 61. • A toolkit that supports the development of ontology based applications; • It provides an integration of existing technologies and techniques to create a unified environment; • Main goal: Easy and efficient development of ontology-based application. 63 JOINT: Java Ontology Integrated Toolkit
- 62. JOINT: Java Ontology Integrated Toolkit
- 63. JOINT: Java Ontology Integrated Toolkit Interface OnlineAccount Class OnlineAccountImpl
- 64. JOINT: Java Ontology Integrated Toolkit
- 65. JOINT: Java Ontology Integrated Toolkit Artificial Intelligence Artificial Intelligence 2013 3ª Prentice Hall Russell Norvig a:author Prentice Hall Saddle River Stuart J. Russell 1962 Peter Norvig 1956 a:name Load at First level Lazy Load
- 66. JOINT: Java Ontology Integrated Toolkit Development Productivity Performance and use of memory Development of Real-World Apps
- 67. JOINT: Java Ontology Integrated Toolkit Group Machines Tool F5 Intel Core I5, 4GB de RAM JOINT F3 Intel Core I3, 4GB de RAM JOINT J5 Intel Core I5, 4GB de RAM Jastor and Jena J3 Intel Core I3, 4GB de RAM Jastor and Jena Group Development Time Codes Lines Running Time Memory Usage F5 7 hours 72 lines 2584 ms 15,4 MB F3 6 hours 81 lines 3757 ms 16,2 MB J5 15 hours 89 lines 4070 ms 61,5 MB J3 18 hours 84 lines 4144 ms 52,2 MB
- 68. JOINT: Java Ontology Integrated Toolkit
- 70. Education Health Security City Real Estates User Data
- 72. Linked Open Data Standardization effort and JOINT Gamification and MeuTutor