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Semantic Mapping in CLARIN Component Metadata.

  1. Semantic Mapping in CLARIN Component Metadata Matej Durco Institute for Corpus Linguistics and Text Technology Menzo Windhouwer The Language Archive - DANS MTSR 2013 Thessaloniki, Greece
  2. Outline      CLARIN an european infrastructure for language resources Component Metadata Infrastructure (CMDI) Semantic Mapping in CMDI Semantic mapping in the CLARIN joint metadata domain Conclusions and future work
  3. CLARIN  CLARIN = Common Language Resources and Technology Infrastructure = an european ESFRI infrastructure project  Aims at providing easy and sustainable access for scholars in the humanities and social sciences to digital language data (in written, spoken, video or multimodal form) and advanced tools to discover, explore, exploit, annotate, analyze or combine them, independent of where they are located.  Building a networked federation of European data repositories, service centers and centers of expertise.  One pillar of this infrastructure is a joint metadata domain
  4. Component Metadata Infrastructure Rationale for CMDI  Limitations of existing metadata schemas (OLAC/DCMI, IMDI, TEI header)     Inflexible: too many (IMDI) or too few (OLAC) metadata elements Limited interoperability (both semantic and syntactic) Problematic (unfamiliar) terminology for some sub-communities. Limited support for LT tool & services descriptions  CMDI addresses this by:  Explicit defined schema & semantics  User/project/community defined components
  5. CMDI - example Lets describe a speech recording Sample frequency Format Size Technical Metadata …
  6. CMDI - example Lets describe a speech recording Name Language Id … Technical Metadata
  7. CMDI - example Lets describe a speech recording Name Actor Age Sex Language Language … Technical Metadata
  8. CMDI - example Continent Location Country Address … Actor Language Technical Metadata Lets describe a speech recording
  9. CMDI - example Name Project Contact … Location Actor Language Technical Metadata Lets describe a speech recording
  10. CMDI - example Project Lets describe a speech recording Location Actor Metadata schema (W3C XML Schema) Language Technical Metadata Metadata Profile Metadata description (XML document)
  11. CMDI - workflow metadata catalogue component registry & editor ISOcat metadata modeler metadata user search & semantic mapping metadata curator Relation Registry metadata editor Joint metadata repository Local metadata repository OAI-PMH Service provider OAI-PMH Data provider DATA metadata creator metadata curator
  12. Semantic Mapping in CMDI  A CMD component, element or value should be linked to a ‘concept’, i.e., an URI that points to a semantic description  ‘concepts’ can be shared indicating shared semantics  Current components use mainly:  Dublin Core elements or terms  ISOcat Data Categories  ISOcat ( is an ISO 12620:2009 compliant Data Category Registry  allows ellaborate specifications, e.g., a definition, (alternative) names, examples, explanations, value domains (all in various languages)  can be freely used by anyone, including the creation of new data categories  the Athens Core group has created many metadata data categories inspired by OLAC, TEI Header and IMDI
  13. Semantic Mapping in CMDI Name Language Id … Semantic Registry Language Name : A human understandable name of the language that ... Language ID : Identifier of the language as defined by ISO 639 that … Language Dictionary Author …
  14. Semantic Mapping in CMDI  Due to the use of multiple ‘concept’ registries and the open nature of some of them (almost) same-as relationships have to be specified  RELcat (under development) is a Relation Registry which allows to store these in, possibly user or community specific, sets language ID isocat:DC-2482 dc:language language name isocat:DC-2484 time coverage isocat:DC-1502 relcat:subClassOf dc:coverage
  15. CMDI in CLARIN 2011-01 Profiles 2012-06 2013-01 2013-06 40 53 87 124 Components 164 298 542 828 Elements 511 893 1505 2399 Distinct Data Categories (DCs) 203 266 436 499 Metadata DCs 277 712 774 791 24.7% 17.6% 21.5% 26.5% % Elements w/o DCs   CMD profiles for existing metadata schemas like OLAC/DCMI, TEI Header and META-SHARE have been created Profiles differ a lot in structure:  Small and flat profiles with 5 – 10 elements  Large and complex profiles of up to 10 component levels with hundreds of elements  Around half a million CMD records are harvested from around 70 providers
  16. CMD Semantic Mapping in CLARIN  791 metadata Data Categories  222 from Athens Core (recommended)  2 showcases (of very common concepts):  Language  Name  SMC (Semantic Mapping Component) Browser   Allows the metadata modeller to explore the semantic overlap between profiles, components and elements in an interactive graph
  17. CMD Semantic Mapping in CLARIN  Language  LanguageID (  languageName (  Linked in the RelationRegistry with the Dublin Core term language  (graph)  Together these ‘concepts’ are linked with 80 profiles  Other related language Data Categories could be considered  sourceLanguage, languageMother  The Relation Registry allows to include them to maximize the recall for a specific language
  18. CMD Semantic Mapping in CLARIN
  19. CMD Semantic Mapping in CLARIN  Name  Is a more ambiguous term used by 72 CMD elements  12 different Data Categories are used by these elements       resourceName ( resourceTitle ( author ( contact full name ( dcterms:Contributor ...  A naive search on ‘name’ would yield semantically very heterogenous results, instead use  The ‘concept’ links  Context, i.e., the enclosing components of an element
  20. Conclusion & future work  The CMD Infrastructure is very flexible with regard to metadata structures, but also provides an integrated semantic layer to achieve semantic interoperability  All the proper registries are in place and prove to be useful, e.g., by the central CLARIN catalogue  Users can search and navigate the metadata based on semantics and are not directly confronted with the structural diversity  Furture work: sometimes more context is needed for disambiguation  However, for metadata modellers the percieved proliferation of reusable profiles and component can be a burden  The SMC browser gives already insight in (semantic) overlap and differences  Future work: statistics based on the instance data will also help to select among profiles and components