The MetaDater Model and the formation of a GRID for the support of social research John Kallas Greek Social Data Bank National Center for Social Research.

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Presentation transcript:

The MetaDater Model and the formation of a GRID for the support of social research John Kallas Greek Social Data Bank National Center for Social Research

The formation of a GRID  What is a GRID ? A data grid is a distributed data processing system that integrates resources from multiple institutions, each with their own policies and mechanisms; use open general purpose protocols to negotiate and manage sharing and addresses multiple quality and service dimensions, including security, reliability and performance  The Social Sciences Data Archives form a grid with the following characteristics:  Data Archives are the main nodes of the GRID  All the Archives share a documentation standard  The GRID establishes sharing relationships, between data producers, data providers and data analysts and supports standard services  Organizations like CESSDA, IFDO and IASSIST, play an important role in the formation of the GRID

The services that the metadata model supports  The usual services supported by the Data Archives  Dataset archiving  Dataset dissemination  Topic classification of the datasets  New services  Support secondary data production  Support supplementary research documentation  Support enhanced data discovery  Support building a subject matter ontology for specific research fields  Support new study design

Support secondary data production  Secondary Analysis  Get data from different studies  Transform them  Analyze them  Document the results  Dataset Integration and harmonization  Get data from different studies  Harmonize them  Integrate them  Document the new study

Complex study documentation

Supplementary research documentation  Add documentation produced during the different uses of a dataset  Analysis results  References (publications etc)  Citations  Collections

Linking documentation objects

Building a subject matter ontology for specific research fields  Define the elements of a subject matter ontology  Objects of observation  Attributes  Concepts  Value domains  Built a subject matter knowledge base  Create collections for a subject matter field  Create a terminology for a subject matter field

Linking variables to concepts

Data discovery  Retrieve data in different ways  By title  By topic  By any related documentation object  By term  By object of observation  By variable  By question  By value domain  Navigate through different surveys and datasets

Support new study design  A subject matter knowledge base can be used for new study design  Select concepts  Select objects of observation  Select variables  Select value domains

Conclusions  The development of metadata management systems based on a common conceptual metadata model will enhance the functionality of the GRID  The integration of metadata based on a common conceptual metadata model will improve conceptualization in the different research fields of social sciences