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Data Standardization in Digital Libraries An ETD Case in Turkey

Data Standardization in Digital Libraries An ETD Case in Turkey. Özlem Şenyurt Topçu , Tolga Çakmak , Güleda Doğan Hacettepe University , Department of Information Management { ozlemsenyurt , tcakmak , gduzyol } @ hacettepe.edu.tr. Content. Data Standardization Data Cleaning

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Data Standardization in Digital Libraries An ETD Case in Turkey

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  1. Data Standardization in Digital Libraries An ETD Case in Turkey ÖzlemŞenyurtTopçu, Tolga Çakmak, GüledaDoğan HacettepeUniversity, Department of Information Management {ozlemsenyurt, tcakmak, gduzyol} @ hacettepe.edu.tr

  2. Content • Data Standardization • Data Cleaning • Data StandardizationandMetadata • LIS ETDs Archive in Turkey • Content&DataStructure • Standardizationwork-flow • Data StandardizationProcess Conclusion 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  3. Data Standardization • Quality data should have some criteria: • accuracy • integrity • completeness • validity • consistency • uniformity • density 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  4. Data Standardization Data standardization: • consistency, • between the content and format of data types represented in a system, • for data mapping and dataoutputs. • processestoimprove information retrieval, • loss of data, • unduplicated data. 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  5. Data Standardization Essentialprocessesfor; • userinteraction • meetinginformationneeds Advantages; • increasesthe clarity level of data, • providesinternal consistency of data, • presentsa high quality and consistent platform for users, 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  6. Data Cleaning Detecting and removing errors and inconsistencies from data(Rahm and Do, 2000). Data cleaning is to weed out unsuitable or incorrectly entered data in the data set (Tekerek, 2011). Data cleaning is also stated as a process that increases data quality and solves data quality problems. 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  7. Data Standardization and Metadata • Usage of digital collections effectively is dependent on the metadata quality. • management of digital resources usefully at a wider level requires some degree ofstandardization of data and metadata (Gartner, 2008, p. 4). 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  8. Data Standardization and Metadata • Standardized data utilize: • efficient discovery, • access, • transfer and use of common terms, • common definitions, etc. (Gartner, 2008, p. 5; Why, 2013). 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  9. Data Standardization and Metadata Standardizedmetadata • enables users effectiveandefficient access todata by using a set of terminology (GeoNetwork, 2008, p. 32). • allowsusers’ accesstotheinformationtheyneed(Xie and Shibasaki, 2013). 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  10. LIS ETD Archive in Turkeyhttp://bbytezarsivi.hacettepe.edu.tr 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  11. LIS ETD Archive in Turkey Objectivesof the project are: • Creating a union catalog • Developing a digital archive that presents full texts and bibliographic descriptions • Identification of ETDs via interoperable and standardized structures. • Increasing access and visibility • ProvidingOAI-PMH standards and protocols, and an interoperable environment for search engines. 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  12. Content & datastructure • 436 post-graduate (masters and doctorate) • by the end of 2012. 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  13. Data standardizationprocesses and data standardization work-flow • First stage; • Data set was determined and created via various supplementary resources, • Second stage; • Rules and norms that will be used for the standardization processes were determined, • Final stage; • Data integrity were provided, and false and flawed data were corrected. 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  14. Standardizationwork-flow 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  15. Data standardizationprocess • Authorities: Virtual Authority File (VIAF) • Title: AACR2 • Date: Publication mm-dd-yy • Keywords and subject headings • Summaries • Usage restrictions 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  16. Conclusion • interoperability with other systems, • mostly supporting open access and scholarly communication, • effective information retrieval and support critical thinking processes of users, 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  17. References Gartner, R. (2008). Metadatafordigitallibraries: state of the art andfuturedirections. JISC Technology & Standarts Watch. RetrievedJune 17, 2013, from http://www.jisc.ac.uk/media/documents/techwatch/tsw_0801pdf.pdf GeoNetworkOpensource  (2008). Thecompletemanual. RetrievedJune 23, 2013, from http://apps.who.int/geonetwork/docs/Manual.pdf Xie, R. andShibasaki, R. (2013).Standardizationframeworkfor CEOP metadatadevelopmentandapplication. CEOP/IGWCO Joint Meeting. University of Tokyo, Japan. RetrievedJune 20, 2013, from http://jaxa.ceos.org/wtf_ceop/documents/CEOP_Metadata_Report_20th.pdf Rahm, E. and Do. H. H. (2000). Data Cleaning: problemsandcurrentapproaches. RetrievedJune 10, 2013, from http://dc-pubs.dbs.uni-leipzig.de/files/Rahm2000DataCleaningProblemsand.pdf. Tekerek, A. (2011). Veri madenciliği süreçleri ve açık kaynak kodlu veri madenciliği araçları. paperpresented at Akademik Bilişim 2011 Konferansı. Malatya: İnönü Üniversitesi. Why standardize metadata? (2013). RetrievedJune 21, 2013, from http://gep.frec.vt.edu/pdfFiles/Metadata_PDF's/3.0MD_Presentation-Section3.pdf 3rd International Conference on Integrated Information (IC-ININFO) – September 5-9, 2013 – Prague

  18. If you can’t explain it simply, you don’t understand it well enough Albert Einstein Thankyou… 

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