http://aksw.org/Projects/ReDDObservatory

1. ReDD-Observatory
Using the Web Of Data to Evaluate Research-Disease
Disparity
Amrapali Zaveri, Ricardo Pietrobon, Sören Auer,
Jens Lehmann, Michael Martin and Timofey Ermilov
24 August, WI-2011 1 of 20

2. Outline
• Overview
• Steps
• Dataset Identification
• Dataset Conversion
• Datasets Interlinking
• Research Indices
• Results
• User Interface
• Limitations and Future Work
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 2 of 18

3. ReDD-Observatory
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 3 of 18

4. ReDD-Observatory
• A project to evaluate the disparity
between
• active areas of biomedical research and
• the global burden of disease
• Using Linked Data
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 3 of 18

5. Motivation
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6. Motivation
• Large amount of disparity all over the world
• Placing individuals in danger
• Hindrance to Research Policy makers
• Partially caused by restricted access to
information
• Due to difficulty in reliably obtaining and
integrating data
• Solution: Using Linked Data
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 4 of 18

7. Datasets Identification
The Life Science Linked Data Web
Linked
CT
PubMed
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 5 of 18

8. Datasets Identification
Dataset RDFized
LinkedCT
1 Linked
CT
Bio2RDF’s PubMed
2 PubMed
Global Health Observatory (GHO)
3 ?
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 6 of 18

9. Dataset Conversion
GHO
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 7 of 18

10. Dataset Conversion
GHO
Convert
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 7 of 18

11. Dataset Conversion
GHO
Convert
Using The RDF
Data Cube
Vocabulary
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 7 of 18

12. Dataset Conversion
GHO
Convert
Publish
Using The RDF
Data Cube
Vocabulary
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 7 of 18

13. Dataset Conversion
GHO
Convert
The Linked Data Web
Publish Sussex
Reading
St.
Andrews NDL
Using The RDF
Audio- Lists Resource subjects t4gm
MySpace scrobbler Lists
Moseley (DBTune) (DBTune) RAMEAU
Folk NTU SH lobid
GTAA Plymouth Resource
Lists
Organi-
Reading
Lists
sations
Music The Open ECS
Magna- Brainz Music
DB tune Library LCSH South-
(Data Brainz LIBRIS ampton
Tropes lobid Ulm
Incubator) (zitgist) Man- EPrints
Resources
Data Cube
chester
Surge Reading
biz. Music RISKS
Radio Lists The Open ECS
data. John Brainz
Discogs Library PSH Gem. UB South-
gov.uk Peel (DBTune)
FanHubz (Data In- (Talis) Norm- Mann- ampton
(DB cubator) Jamendo datei heim RESEX
Tune)
Popula- Poké- DEPLOY
Last.fm
tion (En- pédia
Artists Last.FM Linked RDF
AKTing) research EUTC (DBTune) (rdfize) LCCN VIAF Book Wiki
data.gov Produc- Pisa Eurécom
P20 Mashup semantic
NHS .uk tions classical web.org
Pokedex
Vocabulary
(EnAKTing) (DB
Mortality Tune) PBAC ECS
(En-
AKTing)
BBC MARC (RKB Budapest
Program Codes Explorer)
Energy education OpenEI BBC List Semantic Lotico Revyu OAI
(En- CO2 data.gov mes Music Crunch SW
AKTing) (En- .uk Chronic- Linked Dog
NSZL Base
AKTing) ling Event- MDB RDF Food IRIT
America Media Catalog
ohloh
BBC DBLP ACM IBM
Good- BibBase
Ord- Wildlife (RKB
Openly Recht- win
nance Finder Explorer)
Local spraak. Family DBLP
legislation Survey Tele- New VIVO UF
.gov.uk nl graphis York flickr (L3S) New-
VIVO castle
Times URI wrappr Open Indiana RAE2001
UK Post- Burner Calais DBLP
codes statistics (FU
VIVO CiteSeer Roma
data.gov LOIUS Taxon iServe Berlin) IEEE
.uk Cornell
Concept Geo
World data
ESD Fact- OS dcs
Names book dotAC
stan- reference Project
Linked Data NASA (FUB) Freebase
dards data.gov Guten-
.uk
for Intervals (Data GESIS Course-
transport DBpedia berg STW ePrints CORDIS
Incu- ware
data.gov bator) (FUB)
Fishes ERA UN/
.uk
of Texas Geo LOCODE
Uberblic
Euro- Species
The stat dbpedia TCM SIDER Pub KISTI
(FUB) lite Gene STITCH Chem JISC
London Geo KEGG
DIT LAAS
Gazette TWC LOGD Linked Daily OBO Drug
Eurostat Data UMBEL lingvoj Med
(es) Disea-
YAGO Medi some
Care ChEBI KEGG NSF
Linked KEGG KEGG
Linked Drug Cpd
GovTrack rdfabout Glycan
Sensor Data CT Bank Pathway
US SEC Open Reactome
(Kno.e.sis) riese Uni
Cyc Lexvo Path-
way PDB Media
Semantic totl.net Pfam
HGNC
XBRL
WordNet KEGG KEGG Geographic
Linked Taxo- CAS Reaction
Twarql (VUA) UniProt Enzyme
rdfabout EUNIS Open nomy
US Census Publications
Numbers PRO- ProDom
SITE Chem2
UniRef Bio2RDF User-generated content
Climbing WordNet SGD Homolo
Linked (W3C) Affy- Gene
GeoData
Cornetto
metrix Government
PubMed Gene
UniParc
Ontology
GeneID Cross-domain
Airports
Product
DB UniSTS MGI
Gen Life sciences
Bank OMIM InterPro
As of September 2010
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 7 of 18

14. Dataset RDFization
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 8 of 18

15. Dataset RDFization
• Available as spreadsheets
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 8 of 18

16. Dataset RDFization
• Available as spreadsheets
• Fully automated conversion not feasible
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 8 of 18

17. Dataset RDFization
• Available as spreadsheets
• Fully automated conversion not feasible
• Semi-automatic approach developed:
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 8 of 18

18. Dataset RDFization
• Available as spreadsheets
• Fully automated conversion not feasible
• Semi-automatic approach developed:
• As plug-in in OntoWiki* - semantic
collaboration platform developed by AKSW
research group.
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 8 of 18

19. Dataset RDFization
• Available as spreadsheets
• Fully automated conversion not feasible
• Semi-automatic approach developed:
• As plug-in in OntoWiki* - semantic
collaboration platform developed by AKSW
research group.
• CSV file converted to RDF using the RDF Data
Cube Vocabulary
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 8 of 18

20. Dataset RDFization
• Available as spreadsheets
• Fully automated conversion not feasible
• Semi-automatic approach developed:
• As plug-in in OntoWiki* - semantic
collaboration platform developed by AKSW
research group.
• CSV file converted to RDF using the RDF Data
Cube Vocabulary
* Sören Auer et.al.: OntoWiki: A Tool for Social Semantic Collaboration
In: Proceedings of the CKC 2007 at the 16th International WWW2007 Banff,
Canada, 2007
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 8 of 18

21. Dataset RDFization
OntoWiki’s CSV Import Plug-in
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22. Dataset RDFization
OntoWiki’s CSV Import Plug-in
Table 3. Estimated deaths per 100,000 female population by cause, and
Member State, 2004 (a)
Afghanistan Albania Algeria Andorra Angola
3010 4005 1010 4008 1020
Tuberculosis 41.4 1.4 1.3 0.9 16.2
STDs 5.4 0 1.5 0.1 5.3
excluding HIV
Syphilis 3.5 0 0.5 0 3.8
Chlamydia 0.9 - 0 - 0.1
Gonorrhoea 0.3 - 0 - 0.1
HIV/AIDS 0 - 0.7 1.4 66
Diarrhoeal 309.2 4.6 27.9 1.2 332.4
diseases
Childhood- 42 0 2.1 0 38.7
cluster
diseases
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 9 of 18

23. Dataset RDFization
OntoWiki’s CSV Import Plug-in
Dimensions Table 3. Estimated deaths per 100,000 female population by cause, and
Country Member State, 2004 (a)
rdfs:subPropertyOf
qb:concept
Afghanistan Albania Algeria Andorra Angola
Population 3010 4005 1010 4008 1020
rdfs:subPropertyOf
qb:concept Tuberculosis 41.4 1.4 1.3 0.9 16.2
Disease STDs 5.4 0 1.5 0.1 5.3
rdfs:subPropertyOf excluding HIV
qb:concept Syphilis 3.5 0 0.5 0 3.8
Chlamydia 0.9 - 0 - 0.1
Gonorrhoea 0.3 - 0 - 0.1
HIV/AIDS 0 - 0.7 1.4 66
Diarrhoeal 309.2 4.6 27.9 1.2 332.4
diseases
Childhood- 42 0 2.1 0 38.7
cluster
diseases
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 9 of 18

24. Dataset RDFization
OntoWiki’s CSV Import Plug-in
Dimensions Table 3. Estimated deaths per 100,000 female population by cause, and
Country Member State, 2004 (a)
rdfs:subPropertyOf
qb:concept
Afghanistan Albania Algeria Andorra Angola
Population 3010 4005 1010 4008 1020
rdfs:subPropertyOf
qb:concept Tuberculosis 41.4 1.4 1.3 0.9 16.2
Disease STDs 5.4 0 1.5 0.1 5.3
rdfs:subPropertyOf excluding HIV
qb:concept Syphilis 3.5 0 0.5 0 3.8
Attributes Chlamydia 0.9 - 0 - 0.1
Measure
Gonorrhoea 0.3 - 0 - 0.1
qb:attribute
Unit of Measure HIV/AIDS 0 - 0.7 1.4 66
Diarrhoeal 309.2 4.6 27.9 1.2 332.4
diseases
Childhood- 42 0 2.1 0 38.7
cluster
diseases
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 9 of 18

25. Dataset RDFization
OntoWiki’s CSV Import Plug-in
Dimensions Table 3. Estimated deaths per 100,000 female population by cause, and
Country Member State, 2004 (a)
rdfs:subPropertyOf
qb:concept
Afghanistan Albania Algeria Andorra Angola
Population 3010 4005 1010 4008 1020
rdfs:subPropertyOf
qb:concept Tuberculosis 41.4 1.4 1.3 0.9 16.2
Disease STDs 5.4 0 1.5 0.1 5.3
rdfs:subPropertyOf excluding HIV
qb:concept Syphilis 3.5 0 0.5 0 3.8
Attributes Chlamydia 0.9 - 0 - 0.1
Measure
Gonorrhoea 0.3 - 0 - 0.1
qb:attribute
Unit of Measure HIV/AIDS 0 - 0.7 1.4 66
Data Range Diarrhoeal 309.2 4.6 27.9 1.2 332.4
3,5 diseases
Childhood- 42 0 2.1 0 38.7
7,12
cluster
diseases
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 9 of 18

26. Dataset RDFization
* Available for download at: http://aksw.org/Projects/Stats2RDF
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 10 of 18

27. Dataset RDFization
Example of a single statistical item, the death
value of 41.4, from the GHO dataset*
represented using the Data Cube vocabulary:
eg:o1 a qb:Observation;
gho:Country Afghanistan;
gho:whoid 1605;
gho:pop 3010;
gho:disease Tuberculosis;
gho:gbdcode W0003;
gho:death 41.4.
* Available for download at: http://aksw.org/Projects/Stats2RDF
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 10 of 18

28. Dataset RDFization
Example of a single statistical item, the death
value of 41.4, from the GHO dataset*
represented using the Data Cube vocabulary:
eg:o1 a qb:Observation;
gho:Country Afghanistan;
gho:whoid 1605;
gho:pop 3010;
gho:disease Tuberculosis;
gho:gbdcode W0003;
gho:death 41.4.
* Available for download at: http://aksw.org/Projects/Stats2RDF
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 10 of 18

29. Dataset RDFization
Example of a single statistical item, the death
value of 41.4, from the GHO dataset*
represented using the Data Cube vocabulary:
eg:o1 a qb:Observation;
gho:Country Afghanistan;
gho:whoid 1605;
gho:pop 3010; 3 Million Triples*
gho:disease Tuberculosis;
gho:gbdcode W0003;
gho:death 41.4.
* Available for download at: http://aksw.org/Projects/Stats2RDF
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 10 of 18

30. Datasets Interlinking
Using SILK* and MeSH (UMLS)**
*J. Volz, C. Bizer, M. Gaedke, and G. Kobilarov, “Discovering and
maintaining links on the web of data,” in ISWC, 2009.
**S. J. Nelson, T. Powell, Humphreys, and B. L., The Unified Medical
Language System (UMLS) Project. New York: Marcel Dekker, Inc., 2002, pp.
369–378.
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 11 of 18

31. Datasets Interlinking
Using SILK* and MeSH (UMLS)**
Publications
*J. Volz, C. Bizer, M. Gaedke, and G. Kobilarov, “Discovering and
maintaining links on the web of data,” in ISWC, 2009.
**S. J. Nelson, T. Powell, Humphreys, and B. L., The Unified Medical
Language System (UMLS) Project. New York: Marcel Dekker, Inc., 2002, pp.
369–378.
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 11 of 18

32. Datasets Interlinking
Using SILK* and MeSH (UMLS)**
Publications Countries
*J. Volz, C. Bizer, M. Gaedke, and G. Kobilarov, “Discovering and
maintaining links on the web of data,” in ISWC, 2009.
**S. J. Nelson, T. Powell, Humphreys, and B. L., The Unified Medical
Language System (UMLS) Project. New York: Marcel Dekker, Inc., 2002, pp.
369–378.
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 11 of 18

33. Datasets Interlinking
Using SILK* and MeSH (UMLS)**
Publications Countries Diseases
*J. Volz, C. Bizer, M. Gaedke, and G. Kobilarov, “Discovering and
maintaining links on the web of data,” in ISWC, 2009.
**S. J. Nelson, T. Powell, Humphreys, and B. L., The Unified Medical
Language System (UMLS) Project. New York: Marcel Dekker, Inc., 2002, pp.
369–378.
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 11 of 18

34. Datasets Details
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 12 of 18

35. Datasets Details
Linked SPARQL
Dataset Triples Classes Properties RDF Links
Data Endpoint
data/linkedct.org/
LinkedCT LinkedCT.org snorql 7M 13 90 235,998
pubmed.bio2rdf.org
PubMed Bio2RDF. org /sparql 797M 120 362 30,000
db0.aksw.org:8895/
GHO redd.aksw.org sparql 3M 8 8 6,000
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 12 of 18

36. Research Indices
Death
DALY
DALY = Disability-adjusted life-year
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37. Research Indices
Death
Trials vs. Deaths = Trials (weighted)/Total Number of Trials
DALY
DALY = Disability-adjusted life-year
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 13 of 18

38. Research Indices
Death
Trials vs. Deaths = Trials (weighted)/Total Number of Trials
Deaths/Total Number of Deaths
DALY
DALY = Disability-adjusted life-year
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 13 of 18

39. Research Indices
Death
Trials vs. Deaths = Trials (weighted)/Total Number of Trials
Deaths/Total Number of Deaths
Pubs vs. Deaths = Pubs (weighted)/Total Number of Pubs
DALY
DALY = Disability-adjusted life-year
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 13 of 18

40. Research Indices
Death
Trials vs. Deaths = Trials (weighted)/Total Number of Trials
Deaths/Total Number of Deaths
Pubs vs. Deaths = Pubs (weighted)/Total Number of Pubs
Deaths/Total Number of Deaths
DALY
DALY = Disability-adjusted life-year
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 13 of 18

41. Research Indices
Death
Trials vs. Deaths = Trials (weighted)/Total Number of Trials
Deaths/Total Number of Deaths
Pubs vs. Deaths = Pubs (weighted)/Total Number of Pubs
Deaths/Total Number of Deaths
DALY
Trials vs. DALYs = Trials (weighted)/Total Number of Trials
DALY/Total Number of DALYs
DALY = Disability-adjusted life-year
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 13 of 18

42. Research Indices
Death
Trials vs. Deaths = Trials (weighted)/Total Number of Trials
Deaths/Total Number of Deaths
Pubs vs. Deaths = Pubs (weighted)/Total Number of Pubs
Deaths/Total Number of Deaths
DALY
Trials vs. DALYs = Trials (weighted)/Total Number of Trials
DALY/Total Number of DALYs
Pubs vs. DALYs = Pubs (weighted)/Total Number of Pubs
DALY/Total Number of DALYs
DALY = Disability-adjusted life-year
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 13 of 18

43. Result - ReDD-Observatory
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44. Result - ReDD-Observatory
Country Profile - Tuberculosis
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45. Result - ReDD-Observatory
Country Profile - Tuberculosis
Trials
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46. Result - ReDD-Observatory
Country Profile - Tuberculosis
Trials Publications
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47. User Interface
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48. User Interface
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49. User Interface
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50. User Interface
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51. User Interface
* Available at: http://redd.aksw.org
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52. Limitations and Future Work
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53. Limitations and Future Work
• Limitations
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54. Limitations and Future Work
• Limitations
• Information Quality
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 16 of 18

55. Limitations and Future Work
• Limitations
• Information Quality
• Coverage
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 16 of 18

56. Limitations and Future Work
• Limitations
• Information Quality
• Coverage
• Interlinking Quality
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57. Limitations and Future Work
• Limitations
• Information Quality
• Coverage
• Interlinking Quality
• Error Propagation
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58. Limitations and Future Work
• Limitations
• Information Quality
• Coverage
• Interlinking Quality
• Error Propagation
• Future Work
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59. Limitations and Future Work
• Limitations
• Information Quality
• Coverage
• Interlinking Quality
• Error Propagation
• Future Work
• Include more datasets
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60. Limitations and Future Work
• Limitations
• Information Quality
• Coverage
• Interlinking Quality
• Error Propagation
• Future Work
• Include more datasets
• Refine indices
Amrapali Zaveri, Universität Leipzig 24 August, WI-2011 16 of 18

61. Limitations and Future Work
• Limitations
• Information Quality
• Coverage
• Interlinking Quality
• Error Propagation
• Future Work
• Include more datasets
• Refine indices
• Improve user interface
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62. Acknowledgements
Team Members
Reviewers
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63. Questions?
Comments?
Suggestions?
Thank you !
http://aksw.org/AmrapaliZaveri
zaveri@informatik.uni-leipzig.de
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