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KIT Graduiertenkolloquium 11.05.2016

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The formulation of constraints and the validation of RDF data against these constraints is a common requirement and a much sought-after feature, particularly as this is taken for granted in the XML world. Recently, RDF validation as a research field gained speed due to shared needs of data practitioners from a variety of domains. For constraint formulation and RDF data validation, several languages exist or are currently developed. Yet, none of the languages is able to meet all requirements raised by data professionals.
We have published a set of constraint types that are required by diverse stakeholders for data applications. We use these constraint types to gain a better understanding of the expressiveness of solutions, investigate the role that reasoning plays in practical data validation, and give directions for the further development of constraint languages.
We introduce a validation framework that enables to consistently execute RDF-based constraint languages on RDF data and to formulate constraints of any type in a way that mappings from high-level constraint languages to an intermediate generic representation can be created straight-forwardly. The framework reduces the representation of constraints to the absolute minimum, is based on formal logics, and consists of a very simple conceptual model with a small lightweight vocabulary. We demonstrate that using another layer on top of SPARQL ensures consistency regarding validation results and enables constraint transformations for each constraint type across RDF-based constraint languages.

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KIT Graduiertenkolloquium 11.05.2016

  1. 1. KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft www.kit.edu Validation Framework for RDF-based Constraint Languages M.Sc. (TUM) Thomas Hartmann Graduiertenkolloquium, 11.05.2016
  2. 2. 2 enthusiasm for SW technologies problem statement
  3. 3. 3 common need for RDF Validation problem statement
  4. 4. 4 common needs of data practitioners W3C RDF Validation Workshop 2 international working groups on RDF validation constraint languages SPARQL Query Language for RDF SPARQL Inferencing Notation (SPIN) Web Ontology Language (OWL) Shape Expressions (ShEx) Resource Shapes (ReSh) Description Set Profiles (DSP) no clear favorite RDF validation as research field problem statement
  5. 5. 5 Which types of research data and related metadata are not yet representable in RDF and how to adequately model them to be able to validate RDF data against constraints extractable from these vocabularies? research question 1 RQ1 LDOW (WWW 2013) SemStats (ISWC 2013) DC 2012 IASSIST Quarterly, 38(4) & 39(1), 7-16 IASSIST Quarterly, 38(4) & 39(1), 17-24 IASSIST Quarterly, 38(4) & 39(1), 25-37 IASSIST Quarterly, 38(4) & 39(1), 38-46 ESWC 2011 (Poster)
  6. 6. 6 development of 3 RDF vocabularies: 1. DDI-RDF Discovery Vocabulary (DDI-RDF) to support the discovery of metadata on unit-record data 2. Physical Data Description (PHDD) to describe data in tabular format and its physical properties 3. The SKOS Extension for Statistics (XKOS) to describe the structure and textual properties of formal statistical classifications to describe relations between classifications and concepts and among concepts contribution 1 RQ1
  7. 7. www.kit.edu 7 research question 2
  8. 8. 8 XML, XML Schema (XSD) RDF, Web Ontology Language (OWL) XML Schemas > OWL ontologies time-consuming work designing domain ontologies from scratch by hand reuse information contained in XML Schemas designing OWL domain ontologies RQ2
  9. 9. 9 How to directly validate XML data on semantically rich OWL axioms using common RDF validation tools when XML Schemas, adequately representing particular domains, have already been designed? research question 2 RQ2
  10. 10. 10 sub-class relationships OWL hasValue restrictions on data properties OWL universal restrictions on object properties semantically rich OWL axioms <library> <book year="February 1890"> <author> <name>Arthur Conan Doyle</name> </author> <title>The Sign of the Four</title> </book> </library> Title ⊑  value.string Year ⊑  value.integer RQ2
  11. 11. 11 on formal logics based transformations OWL axioms extracted out of XML Schemas Explicitly Implicitly formally underpin transformations to formally define and model semantics in a semantically correct way complete extraction of XML Schemas' structural information XML can directly be validated against semantically rich OWL axioms any XML Schema is convertible to OWL minimized effort designing OWL domain ontologies contributions IJMSO, 8(3) RQ2
  12. 12. 12 DC (ISWC 2012) ICITST 2011 OCAS (ISWC 2011) RQ2
  13. 13. 13 1. step of approach executed generic test cases created out of the XML Schema meta-model transformed XML Schemas of 6 XML standards 2. step of approach specified SWRL rules for 3 OWL domain ontologies verified hypothesis determined effort for traditional manual approach estimated effort for semi-automatic approach DDI-RDF serves as OWL domain ontology The effort and the time needed to deliver high quality domain ontologies from scratch by reusing information of already existing XML Schemas is much less than creating domain ontologies completely manually and from the ground up. evaluation IJMSO, 8(3) RQ2
  14. 14. www.kit.edu 14 research question 3
  15. 15. 15 development of constraint languages http://purl.org/net/rdf-validation DC 2014RQ3
  16. 16. 16 Which types of constraints must be expressible by constraint languages to meet all collaboratively and comprehensively identified requirements to formulate constraints and validate RDF data? research question 3 RQ3
  17. 17. 17 published 81 constraint types constraints are instantiated from constraint types each constraint type corresponds to a specific requirement types of constraints on RDF data RQ3
  18. 18. 18 expressivity of constraint languages low-level implementation languages vs. high-level constraint languages OWL 2 is the most expressive high-level constraint language RQ3
  19. 19. 19 high-level constraint languages either lack an implementation or are based on different implementations How to consistently validate RDF data against constraints of any constraint type expressed in any RDF-based constraint language? research question 4-1 RQ4
  20. 20. 20 SPIN as basic validation framework validation environment for RDF-based constraint languages constraint languages are translated into SPARQL represented in RDF in form of a SPIN mapping a SPIN mapping contains one SPIN construct template for each supported constraint type consistent validation across RDF-based constraint languages DC 2014 RQ4
  21. 21. 21 validation process RQ4
  22. 22. 22 validation results CONSTRUCT { _:constraintViolation a spin:ConstraintViolation ; spin:violationRoot ?subject ; rdfs:label ?violationMessage ; spin:violationSource ?violationSource ; :severityLevel ?severityLevel ; spin:violationPath ?violationPath ; spin:fix ?violationFix } RQ4
  23. 23. 23 full implementations for all OWL 2 and DSP language constructs all constraint types expressible in OWL 2 and DSP major constraint types representable by ShEx and ReSh validation environment http://purl.org/net/rdfval-demo RQ4
  24. 24. 24 constraints and constraint language constructs must be representable in RDF constraint languages and supported constraint types must be expressible in SPARQL limitations RQ4
  25. 25. 25 How to represent constraints of any constraint type and how to reduce the representation of constraints of any constraint type to the absolute minimum? research question 4-2 RQ4
  26. 26. 26 abstraction layer enables to express each constraint type straight-forward mappings from high-level constraint languages based on formal logics validation framework for RDF-based constraint languages RQ4
  27. 27. 27 conceptual model DC 2015 RQ4 75%
  28. 28. 28 minimum qualified cardinality restrictions (R-75) OWL: SHACL: :Publication rdfs:subClassOf [ a owl:Restriction ; owl:minQualifiedCardinality 1 ; owl:onProperty :author ; owl:onClass :Person ] . :PublicationShape a sh:Shape ; sh:scopeClass :Publication ; sh:property [ sh:predicate :author ; sh:valueShape :PersonShape ; sh:minCount 1 ; ] . :PersonShape a sh:Shape ; sh:scopeClass :Person . RQ4
  29. 29. 29 ShEx: ReSh: DSP: :Publication { :author @:Person{1, } } :Publication a rs:ResourceShape ; rs:property [ rs:propertyDefinition :author ; rs:valueShape :Person ; rs:occurs rs:One-or-many ; ] . [ dsp:resourceClass :Publication ; dsp:statementTemplate [ dsp:minOccur 1 ; dsp:property :author ; dsp:nonLiteralConstraint [ dsp:valueClass :Person ] ] ] . RQ4 minimum qualified cardinality restrictions (R-75)
  30. 30. 30 SPARQL and SPIN: CONSTRUCT { [ a spin:ConstraintViolation ... . ] } WHERE { ?subject a ?C1 ; ?predicate ?object . BIND ( qualifiedCardinality( ?subject, ?predicate, ?C2 ) AS ?c ) . BIND( STRDT ( STR ( ?c ), xsd:nonNegativeInteger ) AS ?cardinality ) . FILTER ( ?cardinality < ?minimumCardinality ) . FILTER ( ?minimumCardinality = 1 ) . FILTER ( ?C1 = :Publication ) . FILTER ( ?C2 = :Person ) . FILTER ( ?predicate = :author ) . } SELECT ( COUNT ( ?arg1 ) AS ?c ) WHERE { ?arg1 ?arg2 ?object . ?object a ?arg3 . } RQ4 minimum qualified cardinality restrictions (R-75)
  31. 31. 31 minimum qualified cardinality restrictions (R-75): simple constraints RQ4 [ a rdfcv:SimpleConstraint ; rdfcv:contextClass :Publication ; rdfcv:leftProperties ( :author ) ; rdfcv:classes ( :Person ) ; rdfcv:constrainingElement "minimum cardinality" ; rdfcv:constrainingValue "1" ] .
  32. 32. 32 framework is solely based on the abstract definitions of constraint types just 1 SPIN mapping for each constraint type How to ensure for any constraint type that RDF data is consistently validated against semantically equivalent constraints of the same constraint type across RDF-based constraint languages? research question 4-3 RQ4
  33. 33. 33 mappings from constraint languages to the abstraction layer and back enable… How to ensure for any constraint type that semantically equivalent constraints of the same constraint type can be transformed from one RDF-based constraint language to another? RQ4 research question 4-4
  34. 34. 34 What is the role reasoning plays in practical data validation? research question 5-1 RQ5 SEMANTiCS 2015
  35. 35. 35 reasoning solves redundency Publication ⊑ ∃ publicationDate . xsd:date Book ⊑ Publication Conference-Proceeding ⊑ Publication Journal-Article ⊑ Publication RQ5
  36. 36. 36 For which constraint types reasoning may be performed prior to validation to enhance data quality? research question 5-2 RQ5
  37. 37. 37 > 2/5 of constraint types property domains (R-25): constraint types with reasoning ∃ author.⊤ ⊑ Publication author(Alices-Adventures-In-Wonderland, Lewis-Carroll) → rdf:type(Alices-Adventures-In-Wonderland, Publication) RQ5
  38. 38. 38 For which constraint types validation results differ (1) if the CWA or the OWA and (2) if the UNA or the nUNA is assumed? CWA dependent: 56.8% UNA dependent: 66.6% research question 5-3 RQ5
  39. 39. 39 expressivity of constraint languages RQ5
  40. 40. 40 collected 115 constraints from vocabularies or domain experts on 3 common vocabularies well-established (QB, SKOS) under development (DDI-RDF) classified constraints implemented constraints evaluation evaluation ICSC 2016 33 SPARQL endpoints
  41. 41. 41 classification of constraint types RDFS/OWL based constraint language based SPARQL based classification of constraints informational warning error evaluation classification
  42. 42. 42 C (constraints), CV (constraint violations) values in % evaluation main finding C CV SPARQL 63.2 78.2 CL 34.7 21.8 RDFS/OWL 35.6 21.8
  43. 43. 43 evaluation based on 3 vocabularies evaluation limitation
  44. 44. 44 RQ1: future work publication of RDF vocabularies DDI Alliance specifications W3C recommendation for DDI-RDF DDI-Lifecycle MD (Model-Driven) new requirements based on experiences with DDI-RDF international working group: DDI Moving Forward Project individual contributions formalize conceptual model (using UML 2) conceptualize and implement diverse model serializations (e.g., RDFS/OWL) future work
  45. 45. 45 aligning PHDD and CSV on the WEB overlap in the description of tabular data in CSV format broader scope of PHDD description of tabular data with fixed record length description of tabular data with multiple records per case evaluation for use in DDI-Lifecycle MD RQ1: future work future work
  46. 46. 46 RQ2: future work bidirectional transformations from models of any meta-model to OWL generalize from XSD meta-model based unidirectional transformations from XSD models into OWL models enable to validate any data against constraints extractable from models of any meta-model using common RDF validation tools future work
  47. 47. 47 RQ3: future work maintain and extend RDF validation database collect case studies and use cases extract requirements publish constraint types future work
  48. 48. 48 RQ4: future work SPIN mappings for constraint languages not expressible in SPARQL keep framework and constraining elements in sync combine the framework with SHACL derive SHACL extensions with SPARQL bodies define mappings from SHACL to the abstraction layer and back synchronize consistent implementations of constraint types future work
  49. 49. 49 acknowledgements, publications, research data 29 publications 5 journal articles, 9 conference articles, 3 workshop articles, 2 specifications, 10 technical reports 1. author of all (except 1) journal articles, conference articles, workshop articles research data KIT research data repository: http://dx.doi.org/10.5445/BWDD/11 GitHub repository: https://github.com/github-thomas-hartmann/phd-thesis international working groups DCMI RDF Application Profiles Task Group part of the editorial board RDF Vocabularies Working Group editor for DDI-RDF and PHDD W3C RDF Data Shapes Working Group DDI Moving Forward Project
  50. 50. 50 outlook and summary of main contributions provide a basis for continued research incorporate findings of this thesis into the working groups RDF vocabularies RDFication of XML set of constraint types validation framework for RDF-based constraint languages role of reasoning for data validation THANK YOU!
  51. 51. www.kit.edu 51 appendix
  52. 52. 52 publications: journal articles 1. Bosch, Thomas & Mathiak, B. (2015). Use Cases Related to an Ontology of the Data Documentation Initiative. IASSIST Quarterly, 38(4) & 39(1), 25–37. http://iassistdata.org/iq/issue/38/4 2. Bosch, Thomas, Olsson, O., Gregory, A., & Wackerow, J. (2015c). DDI-RDF Discovery - A Discovery Model for Microdata. IASSIST Quarterly, 38(4) & 39(1), 17–24. http://iassistdata.org/iq/issue/38/4 3. Bosch, Thomas & Zapilko, B. (2015). Semantic Web Applications for the Social Sciences. IASSIST Quarterly, 38(4) & 39(1), 7–16. http://iassistdata.org/iq/issue/38/4 4. Schaible, J., Zapilko, B., Bosch, Thomas, & Zenk-Möltgen, W. (2015). Linking Study Descriptions to the Linked Open Data Cloud. IASSIST Quarterly, 38(4) & 39(1), 38–46. http://iassistdata.org/iq/issue/38/4 5. Bosch, Thomas & Mathiak, B. (2013b). How to Accelerate the Process of Designing Domain Ontologies based on XML Schemas. International Journal of Metadata, Semantics and Ontologies - Special Issue on Metadata, Semantics and Ontologies for Web Intelligence, 8(3), 254 – 266. http://www.inderscience.com/info/inarticle.php?artid=57760 Please note that in 2015, my last name changed from Bosch to Hartmann.
  53. 53. 53 publications: articles in conference proceedings 1. Hartmann, Thomas, Zapilko, B., Wackerow, J., & Eckert, K. (2016). Validating RDF Data Quality using Constraints to Direct the Development of Constraint Languages. In Proceedings of the 10th International Conference on Semantic Computing (ICSC 2016) Laguna Hills, California, USA: IEEE. http://www.ieee-icsc.com/ 2. Bosch, Thomas & Eckert, K. (2015). Guidance, Please! Towards a Framework for RDF-based Constraint Languages. In Proceedings of the 15th DCMI International Conference on Dublin Core and Metadata Applications (DC 2015) São Paulo, Brazil. http://dcevents.dublincore.org/IntConf/dc-2015/paper/view/386/368 3. Bosch, Thomas, Acar, E., Nolle, A., & Eckert, K. (2015a). The Role of Reasoning for RDF Validation. In Proceedings of the 11th International Conference on Semantic Systems (SEMANTiCS 2015) (pp. 33–40). Vienna, Austria: ACM. http://doi.acm.org/10.1145/2814864.2814867 4. Bosch, Thomas & Eckert, K. (2014a). Requirements on RDF Constraint Formulation and Validation. In Proceedings of the 14th DCMI International Conference on Dublin Core and Metadata Applications (DC 2014) Austin, Texas, USA. http://dcevents.dublincore.org/IntConf/dc-2014/paper/view/257 5. Bosch, Thomas & Eckert, K. (2014b). Towards Description Set Profiles for RDF using SPARQL as Intermediate Language. In Proceedings of the 14th DCMI International Conference on Dublin Core and Metadata Applications (DC 2014) Austin, Texas, USA. http://dcevents.dublincore.org/IntConf/dc- 2014/paper/view/270 Please note that in 2015, my last name changed from Bosch to Hartmann.
  54. 54. 54 publications: articles in conference proceedings 6. Bosch, Thomas, Cyganiak, R., Wackerow, J., & Zapilko, B. (2012). Leveraging the DDI Model for Linked Statistical Data in the Social, Behavioural, and Economic Sciences. In Proceedings of the 12th DCMI International Conference on Dublin Core and Metadata Applications (DC 2012) Kuching, Sarawak, Malaysia. http://dcpapers.dublincore.org/pubs/article/view/3654 7. Bosch, Thomas (2012). Reusing XML Schemas’ Information as a Foundation for Designing Domain Ontologies. In P. Cudré-Mauroux, J. Heflin, E. Sirin, T. Tudorache, J. Euzenat, M. Hauswirth, J. Parreira, J. Hendler, G. Schreiber, A. Bernstein, & E. Blomqvist (Eds.), The Semantic Web - ISWC 2012, volume 7650 of Lecture Notes in Computer Science (pp. 437–440). Springer Berlin Heidelberg. http://dx.doi.org/10.1007/978-3-642-35173-0_34 8. Bosch, Thomas & Mathiak, B. (2012). XSLT Transformation Generating OWL Ontologies Automatically Based on XML Schemas. In Proceedings of the 6th International Conference for Internet Technology and Secured Transactions (ICITST 2011), IEEE Xplore Digital Library (pp. 660–667). Abu Dhabi, United Arab Emirates. http://edas.info/web/icitst2011/program.html 9. Bosch, Thomas, Wira-Alam, A., & Mathiak, B. (2011). Designing an Ontology for the Data Documentation Initiative. In Proceedings of the 8th Extended Semantic Web Conference (ESWC 2011), Poster-Session Heraklion, Greece. http://www.eswc2011.org/content/accepted-posters.html Please note that in 2015, my last name changed from Bosch to Hartmann.
  55. 55. 55 publications: articles in workshop proceedings Please note that in 2015, my last name changed from Bosch to Hartmann. 1. Bosch, Thomas, Cyganiak, R., Gregory, A., & Wackerow, J. (2013a). DDI-RDF Discovery Vocabulary: A Metadata Vocabulary for Documenting Research and Survey Data. In Proceedings of the 6th Workshop on Linked Data on the Web (LDOW 2013), 22nd International World Wide Web Conference (WWW 2013), volume 996 Rio de Janeiro, Brazil. http://ceur-ws.org/Vol-996/ 2. Bosch, Thomas, Zapilko, B., Wackerow, J., & Gregory, A. (2013b). Towards the Discovery of Person-Level Data - Reuse of Vocabularies and Related Use Cases. In Proceedings of the 1st International Workshop on Semantic Statistics (SemStats 2013), 12th International Semantic Web Conference (ISWC 2013), Sydney, Australia. http://semstats.github.io/2013/proceedings 3. Bosch, Thomas & Mathiak, B. (2011). Generic Multilevel Approach Designing Domain Ontologies Based on XML Schemas. In Proceedings of the 1st Workshop Ontologies Come of Age in the Semantic Web (OCAS 2011), 10th International Semantic Web Conference (ISWC 2011) (pp. 1–12). Bonn, Germany. http://ceur-ws.org/Vol-809/
  56. 56. 56 publications: specifications Please note that in 2015, my last name changed from Bosch to Hartmann. 1. Bosch, Thomas, Cyganiak, R., Wackerow, J., & Zapilko, B. (2016). DDI-RDF Discovery Vocabulary: A Vocabulary for Publishing Metadata about Data Sets (Research and Survey Data) into the Web of Linked Data. DDI Alliance Specification, DDI Alliance. http://rdf-vocabulary.ddialliance.org/discovery 2. Wackerow, J., Hoyle, L., & Bosch, Thomas (2016). Physical Data Description. DDI Alliance Specification, DDI Alliance. http://rdf-vocabulary.ddialliance.org/phdd.html
  57. 57. 57 publications: technical reports Please note that in 2015, my last name changed from Bosch to Hartmann. 1. Hartmann, Thomas (2016a). Validation Framework for RDF-based Constraint Languages - PhD Thesis Appendix. Karlsruhe Institute of Technology (KIT), Karlsruhe. http://dx.doi.org/10.5445/IR/1000054062 2. Vompras, J., Gregory, A., Bosch, Thomas, & Wackerow, J. (2015). Scenarios for the DDI-RDF Discovery Vocabulary. DDI Working Paper Series. http://dx.doi.org/10.3886/DDISemanticWeb02 3. Alonen, M., Bosch, Thomas, Charles, V., Clayphan, R., Coyle, K., Dröge, E., Isaac, A., Matienzo, M., Pohl, A., Rühle, S., & Svensson, L. (2015b). Report on Validation Requirements. DCMI Draft, Dublin Core Metadata Initiative (DCMI). http://wiki.dublincore.org/index.php/RDF_Application_Profiles/Requirements 4. Alonen, M., Bosch, Thomas, Charles, V., Clayphan, R., Coyle, K., Dröge, E., Isaac, A., Matienzo, M., Pohl, A., Rühle, S., & Svensson, L. (2015a). Report on the Current State: Use Cases and Validation Requirements. DCMI Draft, Dublin Core Metadata Initiative (DCMI). http://wiki.dublincore.org/index.php/RDF_Application_Profiles/UCR_Deliverable 5. Bosch, Thomas, Nolle, A., Acar, E., & Eckert, K. (2015b). RDF Validation Requirements - Evaluation and Logical Underpinning. Computing Research Repository (CoRR), abs/1501.03933. http://arxiv.org/abs/1501.03933
  58. 58. 58 publications: technical reports Please note that in 2015, my last name changed from Bosch to Hartmann. 6. Hartmann, Thomas, Zapilko, B., Wackerow, J., & Eckert, K. (2015a). Constraints to Validate RDF Data Quality on Common Vocabularies in the Social, Behavioral, and Economic Sciences. Computing Research Repository (CoRR), abs/1504.04479. http://arxiv.org/abs/1504.04479 7. Hartmann, Thomas, Zapilko, B., Wackerow, J., & Eckert, K. (2015b). Evaluating the Quality of RDF Data Sets on Common Vocabularies in the Social, Behavioral, and Economic Sciences. Computing Research Repository (CoRR), abs/1504.04478. http://arxiv.org/abs/1504.04478 8. Bosch, Thomas, Wira-Alam, A., & Mathiak, B. (2014). Designing an Ontology for the Data Documentation Initiative. Computing Research Repository (CoRR), abs/1402.3470. http://arxiv.org/abs/1402.3470 9. Bosch, Thomas & Mathiak, B. (2013a). Evaluation of a Generic Approach for Designing Domain Ontologies Based on XML Schemas. Gesis Technical Report 08, Gesis - Leibniz Institute for the Social Sciences, Mannheim, Germany. http://www.gesis.org/publikationen/archiv/gesis-technical-reports/ 10. Block, W., Bosch, Thomas, Fitzpatrick, B., Gillman, D., Greenfield, J., Gregory, A., Hebing, M., Hoyle, L., Humphrey, C., Johnson, J., Linnerud, J., Mathiak, B., McEachern, S., Radler, B., Risnes, Ø., Smith, D., Thomas, W., Wackerow, J., Wegener, D., & Zenk-Möltgen, W. (2012). Developing a Model-Driven DDI Specification. DDI Working Paper Series
  59. 59. 59 research questions 1. Which types of research data and related metadata are not yet representable in RDF and how to adequately model them to be able to validate RDF data against constraints extractable from these vocabularies? 2. How to directly validate XML data on semantically rich OWL axioms using common RDF validation tools when XML Schemas, adequately representing particular domains, have already been designed? 3. Which types of constraints must be expressible by constraint languages to meet all collaboratively and comprehensively identified requirements to formulate constraints and validate RDF data? 4. How to ensure for any constraint type that (1) RDF data is consistently validated against semantically equivalent constraints of the same constraint type across RDF-based constraint languages and (2) semantically equivalent constraints of the same constraint type can be transformed from one RDF-based constraint language to another? 5. What is the role reasoning plays in practical data validation and for which constraint types reasoning may be performed prior to validation to enhance data quality? appendix
  60. 60. 60 summary of contributions 1. Development of three RDF vocabularies (1) to represent all types of research data and related metadata in RDF and (2) to validate RDF data against constraints extractable from these vocabularies 2. Direct validation of XML data using common RDF validation tools against semantically rich OWL axioms extracted from XML Schemas properly describing certain domains 3. Publication of 81 types of constraints that must be expressible by constraint languages to meet all jointly and extensively identified requirements to formulate constraints and validate RDF data against constraints 4.1 Consistent validation across RDF-based constraint languages 4.2 Minimal representation of constraints of any type 4.3 For any constraint type, RDF data is consistently validated against semantically equivalent constraints of the same constraint type across RDF-based constraint languages 4.4 For any constraint type, semantically equivalent constraints of the same constraint type can be transformed from one RDF-based constraint language to another 5. We delineate the role reasoning plays in practical data validation and investigated for each constraint type (1) if reasoning may be performed prior to validation to enhance data quality, (2) how efficient in terms of runtime validation is performed with and without reasoning, and (3) if validation results depend on different underlying semantics 6. Evaluation of the Usability of Constraint Types for Assessing RDF Data Quality appendix
  61. 61. 61 summary of limitations 1. XML Schemas must adequately represent particular domains in a syntactically and semantically correct way 2. Constraints of supported constraint types must be representable in RDF 3. Constraint languages and supported constraint types must be expressible in SPARQL 4. The generality of the findings of the large-scale evaluation has to be proved for all vocabularies appendix

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