Ontology-based multi-domain metadata for research data management using triple stores
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A presentation given on the IDEAS 2014 Conference about database modelling using triple stores for research data management. IDEAS '14, July 07 - 09 2014, Porto, Portugal. Paper Abstract: Most current research data management solutions rely on a fixed set of descriptors (e.g. Dublin Core Terms) for the description of the resources that they manage. While these are easy to understand and use, their semantics are limited to general concepts, leaving out domain-specific metadata and representing values as sets of text values. While this enables retrieval through free-text search, faceted search and dataset interlinking becomes limited. From the point of view of the relational database schema modeler, designing a more flexible metadata model represents a non-trivial challenge because of the open nature of the model. This work demonstrates the current approaches followed by current open-source platforms and propose a graph-based model for achieving modular, ontology-based metadata for interlinked data assets in the Semantic Web. This proposed model was implemented in a collaborative research data management platform currently under development at the University of Porto.
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Ontology-based multi-domain metadata for research data management using triple stores
- 1. Ontology-based multi-domain metadata for research data management using triple stores João Rocha da Silva joaorosilva@gmail.com Faculdade de Engenharia da Universidade do Porto / INESC TEC Cristina Ribeiro mcr@fe.up.pt DEI—Faculdade de Engenharia da Universidade do Porto / INESC TEC João Correia Lopes jlopes@fe.up.pt IDEAS '14, July 07 - 09 2014, Porto, Portugal
- 2. Contents • Diverse metadata: relational modeling challenges • Current approaches built on relational databases • Dendro: graph-based research data management • Live demo • Conclusions 2
- 3. Problem: diverse metadata Relational modeling challenges 3
- 4. Analytical Chemistry Dataset Mechanical Engineering Dataset … Generic Author Description Creation date … Author Description Creation date … … Domain Specific Sample Count Analysed Substance … Initial Crack Length Specimen Type … 4
- 5. Common challenges in RDB schema modeling • Entities with unknown attributes at time of modeling • Time-variant attribute values • Inheritance / sub-class mapping • Resource hierarchies (parents of parents…) • Schemas rely on external documentation 5
- 6. Data management and description platforms Study of relational models 6
- 7. DSpace • Academic publications management platform • Not targeted specifically at data • More than 1000 active installations • Mature open-source codebase 7
- 8. DSpace • Designed for self-deposit by common users • Good deposit workflow (validation, licensing…) 8
- 9. U.Porto Open Repository Homepage (http://repositorio-aberto.up.pt) Powered by DSpace 9
- 10. Powered by DSpace A thesis record in the repository (http://repositorio-aberto.up.pt/handle/10216/58508) 10
- 12. DSpace 12
- 13. •Metadata profiles for objects other than Items •Descriptor hierarchy for specialization •Collaborative schema derivation •Validation of metadata completeness against different schemas •Restricting possible metadata for each type of resource New requirements 13
- 14. 14
- 15. CKAN • Open-source data publishing platform • Deposit requires minimal metadata at first • Flexible metadata model • Open-Source 15
- 16. 1 2 16
- 17. 1 17
- 18. ! source CKAN 18
- 19. ! source CKAN 18
- 21. Entity with variable, time-dependent attributes Fixed attrs. ! source CKAN 18
- 22. Attribute name Entity with variable, time-dependent attributes Fixed attrs. ! source CKAN 18
- 23. Attribute name Value (always varchar) Entity with variable, time-dependent attributes Fixed attrs. ! source CKAN 18
- 24. Attribute name Timestamps Value (always varchar) Entity with variable, time-dependent attributes Fixed attrs. ! source CKAN 18
- 25. Invenio • Software behing Zenodo, a data publishing portal • Static metadata model • Very complex relational schema generated by business logic code • Tight coupling between DB and code • Open-Source 19
- 26. 1 2 20
- 28. !22
- 29. !22
- 30. Ontologies Semantic annotation for richer metadata 23
- 31. 24
- 35. ! ! ! ! http://dendro.fe.up.pt/ project/datanotes/data nie:isLogicalPartOf “Base data of the DCB experiments” dc:title rdf:type nie:File ! ! ! ! ! ! http://dendro.fe.up.pt/project/ datanotes/data/base %20data.xls 24
- 36. ! ! ! ! http://dendro.fe.up.pt/ project/datanotes/data nie:isLogicalPartOf “Base data of the DCB experiments” dc:title base data.xls nie:title rdf:type nie:File ! ! ! ! ! ! http://dendro.fe.up.pt/project/ datanotes/data/base %20data.xls 24
- 37. ! ! ! ! http://dendro.fe.up.pt/ project/datanotes/data nie:isLogicalPartOf “Base data of the DCB experiments” dc:title base data.xls nie:title rdf:type nie:File base data.xls dcb:initialCrackLength ! ! ! ! ! ! http://dendro.fe.up.pt/project/ datanotes/data/base %20data.xls 24
- 38. Semantic MediaWiki • Semantic extension of MediaWiki, the code behind Wikipedia • Semantic Links between pages • Uses ontologies • Strong emphasis on page versioning • DB schema built around the time dimension 25
- 41. Semantic Forms From DataNotes + UPBox http://purl.pt/24107/1/iPres2013_PDF/UPBox%20and%20DataNotes%20a%20collaborative%20data%20management%20environment%20for%20the%20long%20tail%20of%20research%20data.pdf 28
- 42. Semantic Forms From DataNotes + UPBox http://purl.pt/24107/1/iPres2013_PDF/UPBox%20and%20DataNotes%20a%20collaborative%20data%20management%20environment%20for%20the%20long%20tail%20of%20research%20data.pdf 29
- 43. Semantic Forms From DataNotes + UPBox http://purl.pt/24107/1/iPres2013_PDF/UPBox%20and%20DataNotes%20a%20collaborative%20data%20management%20environment%20for%20the%20long%20tail%20of%20research%20data.pdf 30
- 45. “Old Versions” aka “copy everything and add a timestamp” 31 ! source MediaWiki
- 46. ! source MediaWiki now imagine we want images of different kinds, with different attributes… 32
- 49. Issues review • Entities with unknown attributes at time of modeling • Time-variant attribute values • Inheritance / sub-classing • Hierarchies (parents of parents of parents…) • Need for external documentation 35
- 50. Dendro a graph-based data management platform 36
- 51. Graph databases • Represent entities (Users, Products, Places…) as vertexes (entity types are called classes) • Connections between them are directed graph edges (edge types are called properties) ! • The meaning of these connections is expressed in ontologies that can be shared and reused 37
- 52. Getting all my Projects • Will fetch all the projects created by the user • Will also return their attributes (“database columns”) • Different projects may have different attributes 38
- 53. Inference • Transitive Properties • Subclasses • Multiple Inheritance •Resource can be a Folder and a Dataset at the same time) 39
- 54. Loading an ontology • Load ontology straight from the web • No platform-specific syntax (like in SMW) 40
- 55. Nothing comes for free • Aggregation operators slow • No ACID properties • Transactions are not supported in standard SPARQL • (“SPARQL 1.1 Query/Update Services should be atomic but that they are not required to be atomic.”) • Graph DBMS Solutions are in early stages (many bugs, many “beta”s, many mailing lists…) 41
- 56. Dendro • Dropbox and File/Folder description platform • Variable descriptions • Time-dependent values • Directory structures (hierarchy) • Need for simple querying… 42
- 57. nie:isLogicalPartOf Pn Dn 280mm “DCB Base Data” 120 Dn-1 dcb:initialCrackLength dc:title dcb:specimenWidth dc:isReferencedBy Fn 120 dc:title dcb:specimenWidth dc:isVersionOf Added property instance 01/01/2014 ^^xsd:date dc:created 01/01/2014 ^^xsd:date dc:modified Changed modification timestamp Revision creation timestamp Un dc:creator Current dataset version Past Revisions ddr:pertainsTo Change recording C ddr:initial CrackLen gth ddr:changedDescriptor “add” ddr:operation “DCB Base Data” 43
- 58. nie:isLogicalPartOf Pn Dn 280mm “DCB Base Data” 120 Dn-1 dcb:initialCrackLength dc:title dcb:specimenWidth dc:isReferencedBy Fn 120 dc:title dcb:specimenWidth dc:isVersionOf Added property instance 01/01/2014 ^^xsd:date dc:created 01/01/2014 ^^xsd:date dc:modified Changed modification timestamp Revision creation timestamp Un dc:creator Current dataset version Past Revisions ddr:pertainsTo Change recording C ddr:initial CrackLen gth ddr:changedDescriptor “add” ddr:operation “DCB Base Data” 43
- 59. nie:isLogicalPartOf Pn Dn 280mm “DCB Base Data” 120 Dn-1 dcb:initialCrackLength dc:title dcb:specimenWidth dc:isReferencedBy Fn 120 dc:title dcb:specimenWidth dc:isVersionOf Added property instance 01/01/2014 ^^xsd:date dc:created 01/01/2014 ^^xsd:date dc:modified Changed modification timestamp Revision creation timestamp Un dc:creator Current dataset version Past Revisions ddr:pertainsTo Change recording C ddr:initial CrackLen gth ddr:changedDescriptor “add” ddr:operation “DCB Base Data” 43
- 60. nie:isLogicalPartOf Pn Dn 280mm “DCB Base Data” 120 Dn-1 dcb:initialCrackLength dc:title dcb:specimenWidth dc:isReferencedBy Fn 120 dc:title dcb:specimenWidth dc:isVersionOf Added property instance 01/01/2014 ^^xsd:date dc:created 01/01/2014 ^^xsd:date dc:modified Changed modification timestamp Revision creation timestamp Un dc:creator Current dataset version Past Revisions ddr:pertainsTo Change recording C ddr:initial CrackLen gth ddr:changedDescriptor “add” ddr:operation “DCB Base Data” 43
- 61. nie:isLogicalPartOf Pn Dn 280mm “DCB Base Data” 120 Dn-1 dcb:initialCrackLength dc:title dcb:specimenWidth dc:isReferencedBy Fn 120 dc:title dcb:specimenWidth dc:isVersionOf Added property instance 01/01/2014 ^^xsd:date dc:created 01/01/2014 ^^xsd:date dc:modified Changed modification timestamp Revision creation timestamp Un dc:creator Current dataset version Past Revisions ddr:pertainsTo Change recording C ddr:initial CrackLen gth ddr:changedDescriptor “add” ddr:operation “DCB Base Data” 43
- 62. nie:isLogicalPartOf Pn Dn 280mm “DCB Base Data” 120 Dn-1 dcb:initialCrackLength dc:title dcb:specimenWidth dc:isReferencedBy Fn 120 dc:title dcb:specimenWidth dc:isVersionOf Added property instance 01/01/2014 ^^xsd:date dc:created 01/01/2014 ^^xsd:date dc:modified Changed modification timestamp Revision creation timestamp Un dc:creator Current dataset version Past Revisions ddr:pertainsTo Change recording C ddr:initial CrackLen gth ddr:changedDescriptor “add” ddr:operation “DCB Base Data” 43
- 63. Demo Dendroβ 44
- 64. Conclusions • Recording rich metadata requires data model flexibility • Unknown attributes, time-variant information or hierarchies can be hard to model in a relational database • Several current solutions make compromises due to their relational database layer 45
- 65. Conclusions (cont’d) • Graph-based models are more flexible and easily expansible through ontology loading • Ontologies are shareable on the web, and document the database “schema” • Queries become simpler due to the graph model’s ability to easily model challenging scenarios for RDBs • Dendro is a collaborative data management platform fully built on a graph model 46
- 66. João Rocha da Silva is an Informatics Engineering PhD student at the Faculty of Engineering of the University of Porto. He specializes on research data management, applying the latest Semantic Web Technologies to the adequate preservation and discovery of research data assets.! ! He is also an experienced freelancer iOS Developer with several Apps published on the App Store, and a self- taught DIY mechanic with a special interest in classic cars, particularly his 1987 Toyota Corolla GT Twin Cam, also known as Hachi-Roku or AE86.! Research Data Management and Semantic Web Researcher, Web & iPhone Developer João Rocha da Silva! João Correia Lopes is an Assistant Professor in Informatics Engineering at Universidade do Porto and a researcher at INESC TEC. He has graduated in Electrical Engineering in the University of Porto in 1984 and holds a PhD in Computing Science by Glasgow University in1997. His teaching includes undergraduate and graduate courses in databases and web applications, software engineering and object-oriented programming, markup languages and semantic web. He has been involved in research projects in the area of long-term preservation, service-oriented architectures and e-Science. Currently his main research interests are e-Science and the management of research data. Cristina Ribeiro is an Assistant Professor in Informatics Engineering at Universidade do Porto and a researcher at INESC TEC. She has graduated in Electrical Engineering, holds a Master in Electrical and Computer Engineering and a Ph.D. in Informatics. Her teaching includes undergraduate and graduate courses in information retrieval, digital libraries, knowledge representation and markup languages. She has been involved in research projects in the areas of cultural heritage, multimedia databases and information retrieval. Currently her main research interests are information retrieval, digital preservation and the management of research data. Assistant Professor in Informatics Engineering at Universidade do Porto, Researcher at INESC TECCristina Ribeiro! Assistant Professor in Informatics Engineering at Universidade do Porto, Researcher at INESC TEC João Correia Lopes!