Date: 19/10/2012
The Landscape of Ontology Reuse
in Linked Data
María Poveda, Mari Carmen Suárez-Figueroa,
Asunción Gómez-...
The Landscape of Ontology Reuse in Linked Data 2
Table of contents
• Introduction
• Experimental Method
• Results, Analysi...
Introduction (i)
3
The Linked Data (LD) initiative enables the easy exposure, sharing, and connecting of data on the Web.
...
Introduction (ii)
4The Landscape of Ontology Reuse in Linked Data
How should I
reuse elements
or vocabularies?
Should I im...
The Landscape of Ontology Reuse in Linked Data 5
Table of contents
• Introduction
• Experimental Method
• Results, Analysi...
Experimental Method (i)
6The Landscape of Ontology Reuse in Linked Data
Definitions
Elements
appearing in
a vocabulary.
Lo...
7The Landscape of Ontology Reuse in Linked Data
Automatically:
SPARQL, JEN
A API, Vapour
Manually:
Looking for
rdf, owl, e...
The Landscape of Ontology Reuse in Linked Data 8
Table of contents
• Introduction
• Experimental Method
• Results, Analysi...
9The Landscape of Ontology Reuse in Linked Data
Automatically:
SPARQL, JEN
A API, Vapour
Manually:
Looking for
rdf, owl, e...
10The Landscape of Ontology Reuse in Linked Data
Automatically:
SPARQL, JEN
A API, Vapour
Manually:
Looking for
rdf, owl, ...
Ratios Graphs
Reuse ratio
Detailed reuse ratios
Import graph
Reference graph
Calculating derived products (Phase 2)
11The ...
12The Landscape of Ontology Reuse in Linked Data
Automatically:
SPARQL, JEN
A API, Vapour
Manually:
Looking for
rdf, owl, ...
13The Landscape of Ontology Reuse in Linked Data
Automatically:
SPARQL, JEN
A API, Vapour
Manually:
Looking for rdf,
owl, ...
The Landscape of Ontology Reuse in Linked Data 14
Table of contents
• Introduction
• Experimental Method
• Results, Analys...
Future
work
15The Landscape of Ontology Reuse in Linked Data
Conclusions and Future Works
In this
paper we...
• to complet...
Questions
16
Thanks!
The Landscape of Ontology Reuse in Linked Data
Any questions?
Date: 19/10/2012
The Landscape of Ontology Reuse
in Linked Data
María Poveda, Mari Carmen Suárez-Figueroa,
Asunción Gómez-...
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The Landscape of Ontology Reuse in Linked Data - OEDW2012

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The Landscape of Ontology Reuse in Linked Data - OEDW2012

  1. 1. Date: 19/10/2012 The Landscape of Ontology Reuse in Linked Data María Poveda, Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez Ontology Engineering Group. Departamento de Inteligencia Artificial. Facultad de Informática, Universidad Politécnica de Madrid. Campus de Montegancedo s/n. 28660 Boadilla del Monte. Madrid. Spain {mpoveda, mcsuarez, asun}@fi.upm.es
  2. 2. The Landscape of Ontology Reuse in Linked Data 2 Table of contents • Introduction • Experimental Method • Results, Analysis, and Discussion • Conclusions and Future Works
  3. 3. Introduction (i) 3 The Linked Data (LD) initiative enables the easy exposure, sharing, and connecting of data on the Web. Linked Data principles (http://www.w3.org/DesignIssues/LinkedData.html): • Use URIs as names for things • Use HTTP URIs so that people can look up those names. • When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL) • Include links to other URIs, so that they can discover more things. The Landscape of Ontology Reuse in Linked Data
  4. 4. Introduction (ii) 4The Landscape of Ontology Reuse in Linked Data How should I reuse elements or vocabularies? Should I import another ontology? Should I reference other ontology element URIs? ... replicating manually the URI? ... modularizing and merging ontologies?
  5. 5. The Landscape of Ontology Reuse in Linked Data 5 Table of contents • Introduction • Experimental Method • Results, Analysis, and Discussion • Conclusions and Future Works
  6. 6. Experimental Method (i) 6The Landscape of Ontology Reuse in Linked Data Definitions Elements appearing in a vocabulary. Local elements: those defined in the vocabulary namespace. External elements: those not defined in the vocabulary namespace. Imported elements: those defined in any of the imported vocabularies namespaces. Referenced elements: those not defined in any of the imported vocabularies namespaces but referenced in the vocabulary being analized. Referenced by import elements: those not defined in any of the imported vocabularies namespaces but referenced in at least one of them. Should I import another ontology? Should I reference other ontology element URIs? ... replicating manually the URI? ... merging ontologies? Let’s see how others are reusing terms.
  7. 7. 7The Landscape of Ontology Reuse in Linked Data Automatically: SPARQL, JEN A API, Vapour Manually: Looking for rdf, owl, etc files Harvesting vocabularies Experimental Method (ii) Dataset (vocabularies to be analyzed) Static statistics Reuse metrics and reuse landscape Extracting static statistics (Phase 1) Per element: Per ontology: Type Name Observed in vocabulary Ontologies imported Ontologies referenced Type of appearance Ratios Graphs Reuse ratio Detailed reuse ratios Import graph Reference graph Calculating derived products (Phase 2)
  8. 8. The Landscape of Ontology Reuse in Linked Data 8 Table of contents • Introduction • Experimental Method • Results, Analysis, and Discussion • Conclusions and Future Works
  9. 9. 9The Landscape of Ontology Reuse in Linked Data Automatically: SPARQL, JEN A API, Vapour Manually: Looking for rdf, owl, etc files Harvesting vocabularies Ratios Graphs Reuse ratio Detailed reuse ratios Import graph Reference graph Calculating derived products (Phase 2) Results, Analysis, and Discussion (i) 265 vocabulary prefixes and namespaces retrieved from LOV 242 files downloaded 52 failed 190 successfully loaded into JENA 23 no file downloaded 56 files downloaded manually 6 successfully loaded into JENA Dataset of 196 vocabularies to be analyzed Ontologies difficult to find even manually looking for them Not reachable due to connection problems ease the task of finding and understanding the vocabularies for other developers by providing user friendly web sites where both the ontology and its documentation are easily accessible ease the tasks of accessing and processing vocabularies programmatically by implementing recommended methods for publishing vocabularies http://www.w3.org/TR/swbp-vocab-pub/ Extracting static statistics (Phase 1) Per element: Per ontology: Type Name Observed in vocabulary Ontologies imported Ontologies referenced Type of appearance
  10. 10. 10The Landscape of Ontology Reuse in Linked Data Automatically: SPARQL, JEN A API, Vapour Manually: Looking for rdf, owl, etc files Harvesting vocabularies Ratios Graphs Reuse ratio Detailed reuse ratios Import graph Reference graph Calculating derived products (Phase 2) Extracting static statistics (Phase 1) Per element: Per ontology: Type Name Observed in vocabulary Ontologies imported Ontologies referenced Type of appearance Results, Analysis, and Discussion (ii) Classes Object Properties Datatype Properties Total Locally Defined 5384 3956 1714 11054 Imported 1671 2297 1084 5052 Referenced 783 314 266 1363 ReferencedByImport 488 484 148 1120 Total 8326 7051 3212 18589 59.47% (11054 out of 18589) original definitions 40.53% (7535 out of 18589) reused elements 67.05% (5052 out of 7535) imported elements 18.09% (1363 out of 7535) referenced elements 14.86% (1120 out of 7535) referenced by import elements It could be due to the owl:imports statements mechanism and its transitivity
  11. 11. Ratios Graphs Reuse ratio Detailed reuse ratios Import graph Reference graph Calculating derived products (Phase 2) 11The Landscape of Ontology Reuse in Linked Data Automatically: SPARQL, JEN A API, Vapour Manually: Looking for rdf, owl, etc files Harvesting vocabularies Extracting static statistics (Phase 1) Per element: Per ontology: Type Name Observed in vocabulary Ontologies imported Ontologies referenced Type of appearance Results, Analysis, and Discussion (iii) Reused ontology Prefix #being referenced http://xmlns.com/foaf/0.1/ foaf 43 http://purl.org/dc/terms/ dc 26 http://www.w3.org/2003/01/geo/wgs84_pos geo 25 http://purl.org/dc/elements/1.1/ dce 14 http://www.w3.org/2004/02/skos/core skos 14 http://www.w3.org/2000/10/swap/pim/contact con 11 http://schema.org/ schema 8 http://purl.org/NET/c4dm/event.owl# event 7 http://dbpedia.org/ontology/ DBpedia* 5 http://purl.org/ontology/bibo/ bibo 5 http://purl.org/vocab/frbr/core# frbr 5 Prefixes marked with an * in this table refer to ontologies that are not included in LOV. Imported ontology Prefix #being imported http://purl.org/dc/elements/1.1/ dce 15 http://www.w3.org/2003/06/sw-vocab-status/ns vs 10 http://purl.org/dc/terms/ dc 9 http://xmlns.com/foaf/0.1/ foaf 9 http://purl.org/NET/c4dm/event.owl event 8 http://purl.org/goodrelations/v1 gr 5 http://www.w3.org/2006/time time 5 http://purl.org/vocab/vann/ vann 4 http://purl.org/NET/scovo scovo 3 http://purl.org/ontology/ao/core ao 3 http://purl.org/ontology/similarity/ sim 3 http://www.linkedmodel.org/schema/vaem vaem 3 34.69% (68 out of 196) of the vocabularies use the owl:imports statement 165 owl:imports statements 53.06% (104 out of 196) of the vocabularies reference to other vocabularies Even though ontology editors support owl:imports through few simple user interactions while reusing part of an ontology involves more complex activities (e.g: module extraction, partitioning, pruning, merging, etc.).
  12. 12. 12The Landscape of Ontology Reuse in Linked Data Automatically: SPARQL, JEN A API, Vapour Manually: Looking for rdf, owl, etc files Harvesting vocabularies Ratios Graphs Reuse ratio Detailed reuse ratios Import graph Reference graph Calculating derived products (Phase 2) Results, Analysis, and Discussion (iv) 0 20 40 60 80 100 120 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 ReuseRatio ImportRatio ReferenceRatio ReferenceByImportRatio 101 ontologies present a reuse percentage between 0.0 and 0.1 most of the ontologies do little or no reuse The trend is to adopt a type of reuse for each ontology, either based on owl:imports statements or based on referencing element URIs. It is scarce to find ontologies combining both types of reuse at the same level. For those cases with a reuse ratio higher than 60% the tendency is to achieve this level by importing ontologies. It could be due to the owl:imports statements mechanism that include and its transitivity. Extracting static statistics (Phase 1) Per element: Per ontology: Type Name Observed in vocabulary Ontologies imported Ontologies referenced Type of appearance
  13. 13. 13The Landscape of Ontology Reuse in Linked Data Automatically: SPARQL, JEN A API, Vapour Manually: Looking for rdf, owl, etc files Harvesting vocabularies Ratios Graphs Reuse ratio Detailed reuse ratios Import graph Reference graph Calculating derived products (Phase 2) Results, Analysis, and Discussion (v) ImportGraph ReferenceGraph • Unconnected graphs • Few of them have in and out links • ReferenceGraph is denser than the ImportGraph Extracting static statistics (Phase 1) Per element: Per ontology: Type Name Observed in vocabulary Ontologies imported Ontologies referenced Type of appearance
  14. 14. The Landscape of Ontology Reuse in Linked Data 14 Table of contents • Introduction • Experimental Method • Results, Analysis, and Discussion • Conclusions and Future Works
  15. 15. Future work 15The Landscape of Ontology Reuse in Linked Data Conclusions and Future Works In this paper we... • to complete the set of vocabularies analyzed so that all vocabularies appearing in the nodes are included. • to analyze the outliers obtained from our study as some results might be due to o mismatches between URIs (e.g., mismatch between a URI used in an owl:imports statement and the one use as preferred in the ontology being imported) o mismatches between ontology versions (e.g., the ontology retrieved when importing a given namespace and the one found following an ontology documentation website). • have drawn the current reuse status in a subset of the LD vocabularies. It could be useful for: o Linked Data working teams aiming to reuse ontology terms o LOV developers to include new aspects and metrics of the vocabularies in their ecosystem • have observed the type of appearances of elements in the analyzed vocabularies: locally defined (59.47%), imported (27.18%), referenced (7.33%) and referenced by import (6.02%). • have sketched a first version of the linked vocabularies cloud overview
  16. 16. Questions 16 Thanks! The Landscape of Ontology Reuse in Linked Data Any questions?
  17. 17. Date: 19/10/2012 The Landscape of Ontology Reuse in Linked Data María Poveda, Mari Carmen Suárez-Figueroa, Asunción Gómez-Pérez Ontology Engineering Group. Departamento de Inteligencia Artificial. Facultad de Informática, Universidad Politécnica de Madrid. Campus de Montegancedo s/n. 28660 Boadilla del Monte. Madrid. Spain {mpoveda, mcsuarez, asun}@fi.upm.es

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