Talk at Japan Advanced Institute of Science and Technology - JAIST (2015).

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

5. Maceió
Maceió, AL

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)

29. Audience
Professor
Riichiro
JAIST’s
Professors
Professors’s
DBLP
DOI’s
Papers
CV’s
Authors
CV’s: Ig &
Seiji

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