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Boehringer Ingelheim Pharma GmbH & Co. KG
Scientific Information Center - Aleksandar Kapisoda
Semantics 2015 - Vienna, Aus...
Content
1. Intro
2. Goal
3. Overview Data & Technology
4. Workflow / Pipeline
5. Challenges
6. Data Curation
7. Conclusion...
Mundaneum
Mapping Knowledge
Semantics 2015
Vienna, Austria
3
http://www.mundaneum.org/en
http://archives.mundaneum.org/en/...
1895
We don't live in that kind of world
1895
Paul Otlet
Semantics 2015
Vienna, Austria
4http://www.mondotheque.be/wiki/in...
Paul Otlet
The Father of Information Science
He is one of several people who have been considered the
father of informatio...
1895 - Universal Decimal Classification system
http://www.mondotheque.be/wiki/index.php/Here
Paul Otlet created 1895 the
U...
1895 - Universal Decimal Classification system
2015 - Taxonomies, Dictionaries & Ontologies
https://blog.semantic-web.at/w...
1934 - Radiated Library
Semantics 2015
Vienna, Austria
8
Paul Otlets vision
The Book of the Books
A great network of
knowl...
1934 - Radiated Library
2015 – World Wide Web / Internet
Otlet's writings have sometimes been
called prescient of the curr...
1934 - Universal Information Structure
https://s-media-cache-ak0.pinimg.com/736x/7d/71/0f/7d710ffe8ad97234ebc4867546d68a28...
1934 - Universal Information Structure
2015 – Semantic Web
Paul Otlet
was imagining his
universal information structure
by...
Ubiquitous Web/Symbiotic Web
Semantics @ BI - Evolution of Information Management
12
Evolution of WebTechnology
Semantic W...
BI – Publication Tracker
Goal
Why BI needs
a Publication Tracking System?
Semantics 2015
Vienna, Austria
13
BI – Publication Tracker
Goals
Automatically Data import
ContentCuration
State of the Art Visualisation
Storage in a seman...
Goal – Data Analysis
Number of BI Research Publications in 2015 (Q1, Q2)
Semantics 2015
Vienna, Austria
15
Sample Data
TA:...
Goal – Data Analysis
Impact Factors 2015 (Q1 + Q2) & Published Article
Semantics 2015
Vienna, Austria
16
Sample Data
TA: T...
Goal - Analysing data
Based on Impact Factor Journal Ranking
Semantics 2015
Vienna, Austria
17
https://sciencetechblog.fil...
BI – Publication Tracker
Why BI is using
Semantic Technology
for
Publication Tracking?
Semantics 2015
Vienna, Austria
18
Scientific Publication
How it is looking like?
Semantics 2015
Vienna, Austria
19
http://www.ncbi.nlm.nih.gov/pubmed/262103...
BI – Publication Tracker
Overview Data & Technology
• Data & Data Storage
• xml. files from OVID http://www.ovid.com
• MS ...
BI – Publication Tracker
Workflow / Pipeline
auto-alerts from ovid (.xml file)
Alert Profile
(SearchTerms)
Scheduled Alert...
Data Curation & Analysis
Challenges
Cleaning noisy data
from ovid.xml
Authors
Institutions
Cleaning noisy data
from ovid.x...
Data Curration - Challenge
Data from .xml
Cleaning noisy data
from ovid.xml
Authors
Institutions
Cleaning noisy data
from ...
Data Curation
Ovid – Authors
Semantics 2015
Vienna, Austria
24
Curation Thesaurus Management
Institution – Mapped Concepts
Semantics 2015
Vienna, Austria
25
Data Curation
Ovid – Institution
Semantics 2015
Vienna, Austria
26
Curation Thesaurus Management
Unmapped – Mapped Concepts
Semantics 2015
Vienna, Austria
27
Curation Thesaurus Management
Institution – Mapped Concepts
Semantics 2015
Vienna, Austria
28
Curation Thesaurus Management
Authors – Mapped
Semantics 2015
Vienna, Austria
29
Curation Thesaurus Management
Unmapped – Mapped Concepts
Semantics 2015
Vienna, Austria
30
Curation Thesaurus Management System
Unmapped Concept - Company
Semantics 2015
Vienna, Austria
31
Curation Thesaurus Management System
Mapped Concept - Company
Semantics 2015
Vienna, Austria
32
Unmapped Concept
Data Curration - Challenge
BI internal Data
Cleaning noisy data
from ovid.xml
Authors
Institutions
Cleaning noisy data
fro...
BI Publication Tracker
Admin User Interface – Mock UP
34
Data Visualisation & Analysis
Challenges
Cleaning noisy data
from ovid.xml
Authors
Institutions
Cleaning noisy data
from o...
BI Publication Tracker
GUI/User Interface
36
Conclusions
Cleaning noisy data
from ovid.xml
Authors
Institutions
Cleaning noisy data
from ovid.xml
Authors
Institutions
...
Conclusions
• Linked Data:
Reuse of the Data (SPARQL Endpoint)
Domain Expert
• Data Network Solution
Semantics 2015
Vienn...
Outlook:
What We Want to achieve in the Next Steps
Technology
User Perspective
GUI
• Export of Search Results
Optimization...
Acknowledgement
• Boehringer Ingelheim:
Vision: Value through Innovation
• Research LeadershipTeam
• S.I.C. Colleagues
• S...
1895
We don't live in that kind of world
1895
Paul Otlet
Semantics 2015
Vienna, Austria
41http://ww.mondotheque.be/wiki/in...
2015
We do live in that kind of world
2015
Aleksandar Kapisoda
Semantics 2015
Vienna, Austria
42
Contact Information
Aleksandar Kapisoda
aleksandar.kapisoda@boehringer-ingelheim.com
Semantics 2015
Vienna, Austria
43
Questions?
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Aleksandar Kapisoda: The semantic approach for tracking scientific publications

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Aleksandar Kapisoda: The semantic approach for tracking scientific publications

  1. 1. Boehringer Ingelheim Pharma GmbH & Co. KG Scientific Information Center - Aleksandar Kapisoda Semantics 2015 - Vienna, Austria The semantic approach for tracking scientific publications
  2. 2. Content 1. Intro 2. Goal 3. Overview Data & Technology 4. Workflow / Pipeline 5. Challenges 6. Data Curation 7. Conclusions 8. Outlook 9. Acknowledgement Semantics 2015 Vienna, Austria 2
  3. 3. Mundaneum Mapping Knowledge Semantics 2015 Vienna, Austria 3 http://www.mundaneum.org/en http://archives.mundaneum.org/en/history
  4. 4. 1895 We don't live in that kind of world 1895 Paul Otlet Semantics 2015 Vienna, Austria 4http://www.mondotheque.be/wiki/index.php/Here
  5. 5. Paul Otlet The Father of Information Science He is one of several people who have been considered the father of information science, a field he called "documentation". As a young man, THE UTOPIAN started to think about a system that could represent the multiple networked relations between objects of various formats with various objectives. Paul Otlet designed explicitly mapped multiple relations between multi-media objects (so not just books) and allowed for constant transformation and modification. THE UTOPIAN was imagining his universal information structure by making 'symbolic links' from document to document. Semantics 2015 Vienna, Austria 5
  6. 6. 1895 - Universal Decimal Classification system http://www.mondotheque.be/wiki/index.php/Here Paul Otlet created 1895 the Universal Decimal Classification, (based on the Dewey Decimal Classification), one of the most prominent examples of faceted classification Semantics 2015 Vienna, Austria 6
  7. 7. 1895 - Universal Decimal Classification system 2015 - Taxonomies, Dictionaries & Ontologies https://blog.semantic-web.at/wp-content/uploads/2011/02/GICS_PP.jpg In 2015 we are creating, editing and using Taxonomies, Dictionaries & Ontologies. Semantics 2015 Vienna, Austria 7
  8. 8. 1934 - Radiated Library Semantics 2015 Vienna, Austria 8 Paul Otlets vision The Book of the Books A great network of knowledge which is centered on documents, included the notions, books, journals, radio, television… In 1934, Paul Otlet laid out this vision in what he called “Radiated Library” vision. http://www.mondotheque.be/wiki/index.php/Here
  9. 9. 1934 - Radiated Library 2015 – World Wide Web / Internet Otlet's writings have sometimes been called prescient of the current World Wide Web/ Internet His vision of a great network of knowledge was centered on documents and included the notions of hyperlinks, search engines, remote access, and social networks—although these notions were described by different names. In 1934, Otlet laid out this vision of the computer and internet in what he called “Radiated Library” vision. Semantics 2015 Vienna, Austria 9 http://www.mondotheque.be/wiki/index.php/Here
  10. 10. 1934 - Universal Information Structure https://s-media-cache-ak0.pinimg.com/736x/7d/71/0f/7d710ffe8ad97234ebc4867546d68a28.jpg Semantics 2015 Vienna, Austria 10 Paul Otlet was imagining his universal information structure by making 'symbolic links' from document to document,
  11. 11. 1934 - Universal Information Structure 2015 – Semantic Web Paul Otlet was imagining his universal information structure by making 'symbolic links' from document to document, a system that looks surprisingly similar to what we now might call a 'Semantic Web'. https://s-media-cache-ak0.pinimg.com/736x/7d/71/0f/7d710ffe8ad97234ebc4867546d68a28.jpg Semantics 2015 Vienna, Austria 11
  12. 12. Ubiquitous Web/Symbiotic Web Semantics @ BI - Evolution of Information Management 12 Evolution of WebTechnology Semantic Web Semantic Databases, Linked Data Semantic Search, RDF,Text Mining 2020 - 2030 1990 - 2000 2000 - 2010 2010 - 2020 Year Evolution of Information Management at BI Scientific Information Center „Expert Searches“ based onText MiningTechnologies Data Analysis based on SemanticTechnololgies Version Web 4.0 Web 1.0 Web 2.0 Web 3.0 Scientific Information Center Text Mining, BI-internal Wikis (MediaWiki) Social Web Blogs, Wikis Keyword Search World Wide Web Portals, Internet Databases, File Servers, SQL Scientific Library E-Journals LinkSolver Interaction between humans and machines in symbiosis Comparison WebTechnology vs. BI internal Information Management
  13. 13. BI – Publication Tracker Goal Why BI needs a Publication Tracking System? Semantics 2015 Vienna, Austria 13
  14. 14. BI – Publication Tracker Goals Automatically Data import ContentCuration State of the Art Visualisation Storage in a semantic database Data Analysis possible Semantics 2015 Vienna, Austria 14 Manually added database NoContent Curation Primite Visualisation Storage No Data Analysis possible Scientific Publication Database (State July 2015) BI Scientific PublicationTracking Going live September 2015
  15. 15. Goal – Data Analysis Number of BI Research Publications in 2015 (Q1, Q2) Semantics 2015 Vienna, Austria 15 Sample Data TA: Therapeutic Area
  16. 16. Goal – Data Analysis Impact Factors 2015 (Q1 + Q2) & Published Article Semantics 2015 Vienna, Austria 16 Sample Data TA: Therapeutic Area
  17. 17. Goal - Analysing data Based on Impact Factor Journal Ranking Semantics 2015 Vienna, Austria 17 https://sciencetechblog.files.wordpress.com/2011/05/journal-impact-factors-2008_1.jpg
  18. 18. BI – Publication Tracker Why BI is using Semantic Technology for Publication Tracking? Semantics 2015 Vienna, Austria 18
  19. 19. Scientific Publication How it is looking like? Semantics 2015 Vienna, Austria 19 http://www.ncbi.nlm.nih.gov/pubmed/26210363
  20. 20. BI – Publication Tracker Overview Data & Technology • Data & Data Storage • xml. files from OVID http://www.ovid.com • MS Excel (sheet) • Virtuoso Universal Server as a Triple Store http://virtuoso.openlinksw.com/ • Systems • PoolParty (Thesaurus Server) https://www.poolparty.biz/portfolio-item/poolparty-thesaurus-server • PoolParty Graph Search https://www.poolparty.biz/tag/graph-search • SPARQL http://www.w3.org/TR/sparql11-query/#docResultDesc • Spring https://de.wikipedia.org/wiki/Spring_(Framework) • Maven http://maven.apache.org Semantics 2015 Vienna, Austria 20
  21. 21. BI – Publication Tracker Workflow / Pipeline auto-alerts from ovid (.xml file) Alert Profile (SearchTerms) Scheduled Alerts Content Enrichment Admin User Interface SIC Crawler 21 Current awareness searches Data Curation Thesaurus Management System “reflects the average number of citations to recent articles published in a journal” Impact Factor List Virtuoso Database BI PublicationTracker User Interface
  22. 22. Data Curation & Analysis Challenges Cleaning noisy data from ovid.xml Authors Institutions Cleaning noisy data from ovid.xml Authors Institutions Adding BI internal data Division Theraupeutic Area Location Adding BI internal data Division Theraupeutic Area Location Adding external data Impact Factors Lightweight High scalable User Interface Adding external data Impact Factors Lightweight High scalable User Interface Challenges Semantics 2015 Vienna, Austria 22
  23. 23. Data Curration - Challenge Data from .xml Cleaning noisy data from ovid.xml Authors Institutions Cleaning noisy data from ovid.xml Authors Institutions Adding BI internal data Division Theraupeutic Area Location Adding BI internal data Division Theraupeutic Area Location Building Web Application Lightweight High scalable User Interface Building Web Application Lightweight High scalable User Interface Noisy Data PoolParty Thesaurus Server Admin GUI User GUI Semantics 2015 Vienna, Austria 23
  24. 24. Data Curation Ovid – Authors Semantics 2015 Vienna, Austria 24
  25. 25. Curation Thesaurus Management Institution – Mapped Concepts Semantics 2015 Vienna, Austria 25
  26. 26. Data Curation Ovid – Institution Semantics 2015 Vienna, Austria 26
  27. 27. Curation Thesaurus Management Unmapped – Mapped Concepts Semantics 2015 Vienna, Austria 27
  28. 28. Curation Thesaurus Management Institution – Mapped Concepts Semantics 2015 Vienna, Austria 28
  29. 29. Curation Thesaurus Management Authors – Mapped Semantics 2015 Vienna, Austria 29
  30. 30. Curation Thesaurus Management Unmapped – Mapped Concepts Semantics 2015 Vienna, Austria 30
  31. 31. Curation Thesaurus Management System Unmapped Concept - Company Semantics 2015 Vienna, Austria 31
  32. 32. Curation Thesaurus Management System Mapped Concept - Company Semantics 2015 Vienna, Austria 32 Unmapped Concept
  33. 33. Data Curration - Challenge BI internal Data Cleaning noisy data from ovid.xml Authors Institutions Cleaning noisy data from ovid.xml Authors Institutions Adding BI internal data Division Theraupeutic Area Location Adding BI internal data Division Theraupeutic Area Location Building Web Application Lightweight High scalable User Interface Building Web Application Lightweight High scalable User Interface Missing BI internal data PoolParty Thesaurus Server Admin GUI User GUI Semantics 2015 Vienna, Austria 33
  34. 34. BI Publication Tracker Admin User Interface – Mock UP 34
  35. 35. Data Visualisation & Analysis Challenges Cleaning noisy data from ovid.xml Authors Institutions Cleaning noisy data from ovid.xml Authors Institutions Adding BI internal data Division Theraupeutic Area Location Adding BI internal data Division Theraupeutic Area Location Adding external data Impact Factors Lightweight High scalable User Interface Adding external data Impact Factors Lightweight High scalable User Interface Visualization & Analysis PoolParty Thesaurus Server Admin GUI Visualisation & Analysis Semantics 2015 Vienna, Austria 35
  36. 36. BI Publication Tracker GUI/User Interface 36
  37. 37. Conclusions Cleaning noisy data from ovid.xml Authors Institutions Cleaning noisy data from ovid.xml Authors Institutions Adding & Linking BI internal data Division Theraupeutic Area Location Adding & Linking BI internal data Division Theraupeutic Area Location Adding & Linking external data Impact Factors Lightweight High scalable User Interface Adding & Linking external data Impact Factors Lightweight High scalable User Interface PoolParty Thesaurus Server Admin GUI Visualisation & Analysis Semantics 2015 Vienna, Austria 37
  38. 38. Conclusions • Linked Data: Reuse of the Data (SPARQL Endpoint) Domain Expert • Data Network Solution Semantics 2015 Vienna, Austria 38
  39. 39. Outlook: What We Want to achieve in the Next Steps Technology User Perspective GUI • Export of Search Results Optimization of data of data import • Using Ovid RSS-feeds for updates Semantics 2015 Vienna, Austria 39
  40. 40. Acknowledgement • Boehringer Ingelheim: Vision: Value through Innovation • Research LeadershipTeam • S.I.C. Colleagues • Semantic Web Company Semantics 2015 Vienna, Austria 40
  41. 41. 1895 We don't live in that kind of world 1895 Paul Otlet Semantics 2015 Vienna, Austria 41http://ww.mondotheque.be/wiki/index.php/Here
  42. 42. 2015 We do live in that kind of world 2015 Aleksandar Kapisoda Semantics 2015 Vienna, Austria 42
  43. 43. Contact Information Aleksandar Kapisoda aleksandar.kapisoda@boehringer-ingelheim.com Semantics 2015 Vienna, Austria 43
  44. 44. Questions?

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