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Big Data Analytics and Artificial Intelligence Applications in Records and Archive Administration Processes

Year 2019, Volume: 2 Issue: 1, 44 - 58, 28.06.2019
https://doi.org/10.33721/by.570634

Abstract

Artificial
intelligence and big data, which are frequently heard in recent years, have
reached the level that affect almost every aspects of ​​human being. Recently,
records and archive management has been one of the application fields of Artificial
Intelligence (AI) technologies used in many fields from consumer behavior to
personality analysis, from traffic problems to space studies. The studies and
projects show that archives, libraries and information centers from a


huge amount of
content bars now want to use automated software that processes more accuracy
and almost zero errors instead of man-made processes. Processes which are
relatively long is now being abandoned and automated processes based on
artificial intelligence reduced processing times to minutes or even seconds. As
a natural consequence, while providing rapid access to information, the
effectiveness of information in making strategic decisions has increased. In
this study, the concepts of AI and big data are examined; international studies
on the applicability of these technologies to records and archive management
processes and the issues that the experts should take against these
technologies are discussed. As a result of the information obtained from the
literature review in the other scientific fields, (Data Science, Management
Information Systems, Computer Science and Engineering) related with the
discipline of Information and Records Management, case studies and thoughts
were examined. Recently, automatic file code classification and referral
processes, automatic archiving and design of disposal processes are being
carried out. Regarding the applicability of AI and big data analytics number of
studies records management in Turkey is quite limited.
While this study aims
to contribute to remedy the deficiencies in the field,
it is also
tried to explain that
the process of preserving corporate records and the selection of
archival material which has an archival value using in Turkey in the basis of
AI. At the same time, the implementation of open government data to the public
and interest groups through big data analytics will be introduced. In order to
capture the requirements of the age, it is understood that the experts working
in this field and coordinator institutions surely should benefit from this
technology in Turkey.

References

  • Aktan, E. (2018). Büyük veri: Uygulama alanları, analitiği ve güvenlik boyutu. Bilgi Yönetimi Dergisi, 1(1), 1-22.
  • Arlitsch, K. ve Newell, B. (2017). Thriving in the age of accelerations: A brief look at the societal effects of artificial ıntelligence and the opportunities for libraries. Journal of Library Administration, 57(7), 789-798.
  • Boyd, D. ve Crawford, K. (2012). Critical questions for big data. Information, Communication & Society, 15(5), 662-679.
  • Cox, M. ve Ellsworth, D. (1997). Application-Controlled Demand Paging for Out-of-core Visualization. Erişim Adresi: https://www.nas.nasa.gov/assets/pdf/techreports/1997/nas-97-010.pdf
  • Cox, R., Shah, S., Frederick, W., Nelson, T., Thomas, W., Jansen, G., Dibert, N., Kurtz, M. ve Marciano, R. (2018). A case study in creating transparency in using cultural big data: The legacy of slavery project. IEEE Big Data 2018: 3rd CAS Workshop. Seattle: Washington. Erşim Adresi: https://dcicblog.umd.edu/cas/wp-content/uploads/sites/13/2018/12/12.Cox_-2.pdf
  • Currall, J. ve Moss, M. (2008). We are archivists, but are we OK?. Records Management Journal, 18(1), 69-91.
  • Çiçek, N. (2009). Modern Belgelerin Diplomatiği. İstanbul: Derlem Yayınları.
  • Dale, K. L. (2015). RIM’s role in harnessing the power of big data. Information Management, 2015, 29-32
  • Dollar, C. M. (1993). Archivists and Record Managers in the Information Age. Archivaria, 36, 37-52.
  • Emery, P. (2003). Document and records management: Understanding the differences and embracing integration. ZyLAB Technologies White Paper, September 2003, 1-8.
  • Frey, C. B. ve Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?” Technological Forecasting and Social Change, 114, 254­280.
  • Government Office for Science. (2014). The Internet of Things: Making the Most of the Second Digital Revolution. Erişim Adresi: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/409774/14-1230 internet-of-things-review.pdf
  • Gramatica, R. ve Pickering, R. (2017). Start-up story yewno: an aı-driven path to a knowledge-based future. Insights the UKSG Journal, 30(2), 107­111.
  • Grewal, S. (2014). A critical conceptual analysis of definitions of artificial ıntelligence as applicable to computer engineering. IOSR Journal of Computer Engineering, 6(2), 9-13.
  • Gutierrez, D. (2017). Above the Trend Line-Your Industry Rumor Central for 4/10/2017. Erişim Adresi: https://insidebigdata.com/2017/04/10/trend-line-industry-rumor-central-4102017/
  • Harari, Y. N. (2017). The Rise of the Useless Class. Erişim Adresi: http:// ideas.ted.com/the-rise-of-the-useless-class/
  • IBM. (2010). The Smart Archive Strategy From IBM. IBM Software Industry Solutions.
  • Janssen, M. ve Hoven, J. (2015). Big and open linked data (bold) in government: A challenge to transparency and privacy. Government Information Quarterly, 32, 363-368.
  • Jie, S., Linqian, D., S. Jing, S. ve Huan, H. (2016). Management of University Endowment Fund Archives Under the Background of Big Data. Erişim Adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7976552
  • Kandur, H. (2006). Elektronik Belge Yönetimi Sistem Kriterleri Referans Modeli v.2.0. Ankara: Devlet Arşivleri Genel Müdürlüğü, Cilt No: 29.
  • Lee, M., Zhang, Y., Chen, S., Spencer , E., Cruz , J. D., Hong, H. ve Marciano, R. (2017). Heuristics for Assessing Computational Archival Science (CAS) Research - The Case of the Human Face of Big Data Project. Erişim Adresi: https://ieeexplore.ieee.org/document/8258179
  • Levi, A. S. (2013). Humanities big data. 2013 IEEE International Conference on Big Data. Erişim Adresi: https://pdfs.semanticscholar.org/b302/6e202008a321fa2e15b7668331be9f3cc8cf.pdf
  • Mahon, D. (2015). Focus on the active. Business Intelligence Journal, 19(4), 40-47.
  • Marciano, R., Lemieux, V., Hedges, M., Esteva, M., Underwood, W., Kurtz, M. ve Conrad, M. (2018). Archival records and training in the age of big data. Advances in Librarianship, 44(B), 179-199.
  • McDonald, J. ve Léveillé, J. V. (2014). Whither the retention schedule in the era of big data and open data?. Records Management Journal, 24(2), 99-121.
  • Moses, R. P. (2005). A Glossary of Archival and Records Terminology. Chicago: The Society of American Archivists.
  • Newell, B. C. (2014). Technopolicing, surveillance, and citizen oversight: a neorepublican theory of liberty and ınformation control. Government Information Quarterly, 31(3), 421-431.
  • Prescott, A. (2013). Bibliographic Records as Humanities Big Data. 55-58. Erişim Adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6691670
  • Rolan, G., Humphries, G., Jeffrey, L., Samaras, E., Antsoupova, T. ve Stuart, K. (2018). More human than human? artificial ıntelligence in the archive, Archives and Manuscripts, 47(2), 179-203.
  • Sakyi, K. T. (2016). Big Data: Understanding Big Data. Erişim Adresi: https://arxiv.org/abs/1601.04602
  • Shallcross, M. (2016). Appraising Digital Archives with Archivematica. 3272-3276. Erişim Adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7840985
  • Shepherd, E. J. ve Yeo, G. (2003). Managing Records: A Handbook of Principles and Practice. London: Facet Publishing.
  • Thompson, N., Ravindran, R., ve Nicosia, S. (2015). Government data does not mean data governance: lessons learned from a public sector application audit. Government Information Quarterly, 32(3), 316-322. Uribe, L. M. (2018). Digital Archives as Big Data. Mathematical Population Studies, 26(2), 69-79.
  • Ünal, M. A. ve Özdemirci, F. (2017). EBYS (e-BEYAS) ve e-arşiv sistemlerinde/uygulamalarında yapay zeka yaklaşımı. F. Özdemirci ve Z. Akdoğan (Ed.) Bilgi Sistemleri ve Bilişim Yönetimi Bildiriler Kitabı içinde (ss.57-63). Ankara: BİL-BEM.
  • Yong, M., Liming, L. ve Yongsheng, Q. (2015). Improvement of Big Data Retrieval Algorithm in the Intelligent Archives Management. Erişim Adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7494245 adresinden 28.01.2019 tarihinde erişildi.

Belge ve Arşiv Yönetimi Süreçlerinde Büyük Veri Analitiği ve Yapay Zeka Uygulamaları

Year 2019, Volume: 2 Issue: 1, 44 - 58, 28.06.2019
https://doi.org/10.33721/by.570634

Abstract

Son yıllarda sıkça duyulan kavramlardan
olan yapay zeka ve büyük veri, insan hayatının neredeyse her alanına etki
edecek düzeye gelmiştir. Tüketici davranışlarından kişilik analizlerine, trafik
problemlerinin çözümünden uzay çalışmalarına kadar birçok alanda kullanılan
yapay zeka teknolojilerinin uygulama alanlarından biri de son dönemde belge ve
arşiv yönetimi olmuştur. Yapılan çalışmalar ve yürütülen projeler, çok büyük
miktarda içerik barından arşivler, kütüphaneler ve bilgi merkezlerinin, insan
eliyle gerçekleştirilen süreçler yerine artık daha fazla doğruluk ve neredeyse
sıfır hata ile işleyen otomatikleştirilmiş yazılımlar kullanmak istediklerini
göstermektedir. Uygulama süresinin görece uzun olduğu işler artık terkedilmeye
başlanmış ve yapay zeka temelli otomatikleştirilmiş süreçler, işlem sürelerini dakikalara
hatta saniyelere indirgemiştir. Bunun doğal bir sonucu olarak da bilgiye hızlı
erişim sağlanırken, stratejik kararların alınmasında bilginin etkinliği de artmıştır.
Bu çalışmada, yapay zeka ve büyük veri kavramları incelenmiş; bu teknolojilerin
belge ve arşiv yönetimi süreçlerine uygulanabilirliği konusunda yapılan uluslararası
çalışmalara değinilmiş ve alan uzmanlarının bu teknolojiler karşısında nasıl
bir pozisyon alması gerektiği konuları ele alınmıştır. Bilgi ve Belge Yönetimi
disiplini ile bu disiplinin ilişkide olduğu diğer bilimsel alanlardaki (Veri
Bilimi, Yönetim Bilişim Sistemleri, Bilgisayar Bilimi ve Mühendisliği)
 literatür taramasından elde edilen veriler
neticesinde örnek olaylar ve düşünceler incelenmiştir. Son zamanlarda otomatik
dosya kodu sınıflandırma ve sevk işlemleri, otomatik arşivleme ve tasfiye
süreçlerinin tasarımı ile ilgili çalışmalar yapılmaktadır. Belge yönetiminde
yapay zeka ve büyük veri analitiğinin uygulanabilirliğine dair Türkiye’de
yapılan çalışmaların sayısı oldukça sınırlıdır. Yapılan bu çalışma ile alandaki
eksikliğin giderilmesine katkı sağlanması amaçlanırken, kurumsal belgelerin saklama
süreçlerinde ve arşiv değeri olan malzeme seçiminde yapay zekanın Türkiye’de
kullanım koşulları açıklanmaya çalışılacaktır. Aynı zamanda açık devlet verilerinin
büyük veri analitiği aracılığıyla halkın ve ilgi gruplarının hizmetine sunulmasıyla
ilgili uygulamalar ortaya konulacaktır. Çağın gereklerini yakalamak adına, Türkiye’de
de bu alanda çalışan konu uzmanlarının ve koordinatör kurumların mutlaka bu
teknolojilerden faydalanması gerektiği anlaşılmaktadır.

References

  • Aktan, E. (2018). Büyük veri: Uygulama alanları, analitiği ve güvenlik boyutu. Bilgi Yönetimi Dergisi, 1(1), 1-22.
  • Arlitsch, K. ve Newell, B. (2017). Thriving in the age of accelerations: A brief look at the societal effects of artificial ıntelligence and the opportunities for libraries. Journal of Library Administration, 57(7), 789-798.
  • Boyd, D. ve Crawford, K. (2012). Critical questions for big data. Information, Communication & Society, 15(5), 662-679.
  • Cox, M. ve Ellsworth, D. (1997). Application-Controlled Demand Paging for Out-of-core Visualization. Erişim Adresi: https://www.nas.nasa.gov/assets/pdf/techreports/1997/nas-97-010.pdf
  • Cox, R., Shah, S., Frederick, W., Nelson, T., Thomas, W., Jansen, G., Dibert, N., Kurtz, M. ve Marciano, R. (2018). A case study in creating transparency in using cultural big data: The legacy of slavery project. IEEE Big Data 2018: 3rd CAS Workshop. Seattle: Washington. Erşim Adresi: https://dcicblog.umd.edu/cas/wp-content/uploads/sites/13/2018/12/12.Cox_-2.pdf
  • Currall, J. ve Moss, M. (2008). We are archivists, but are we OK?. Records Management Journal, 18(1), 69-91.
  • Çiçek, N. (2009). Modern Belgelerin Diplomatiği. İstanbul: Derlem Yayınları.
  • Dale, K. L. (2015). RIM’s role in harnessing the power of big data. Information Management, 2015, 29-32
  • Dollar, C. M. (1993). Archivists and Record Managers in the Information Age. Archivaria, 36, 37-52.
  • Emery, P. (2003). Document and records management: Understanding the differences and embracing integration. ZyLAB Technologies White Paper, September 2003, 1-8.
  • Frey, C. B. ve Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?” Technological Forecasting and Social Change, 114, 254­280.
  • Government Office for Science. (2014). The Internet of Things: Making the Most of the Second Digital Revolution. Erişim Adresi: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/409774/14-1230 internet-of-things-review.pdf
  • Gramatica, R. ve Pickering, R. (2017). Start-up story yewno: an aı-driven path to a knowledge-based future. Insights the UKSG Journal, 30(2), 107­111.
  • Grewal, S. (2014). A critical conceptual analysis of definitions of artificial ıntelligence as applicable to computer engineering. IOSR Journal of Computer Engineering, 6(2), 9-13.
  • Gutierrez, D. (2017). Above the Trend Line-Your Industry Rumor Central for 4/10/2017. Erişim Adresi: https://insidebigdata.com/2017/04/10/trend-line-industry-rumor-central-4102017/
  • Harari, Y. N. (2017). The Rise of the Useless Class. Erişim Adresi: http:// ideas.ted.com/the-rise-of-the-useless-class/
  • IBM. (2010). The Smart Archive Strategy From IBM. IBM Software Industry Solutions.
  • Janssen, M. ve Hoven, J. (2015). Big and open linked data (bold) in government: A challenge to transparency and privacy. Government Information Quarterly, 32, 363-368.
  • Jie, S., Linqian, D., S. Jing, S. ve Huan, H. (2016). Management of University Endowment Fund Archives Under the Background of Big Data. Erişim Adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7976552
  • Kandur, H. (2006). Elektronik Belge Yönetimi Sistem Kriterleri Referans Modeli v.2.0. Ankara: Devlet Arşivleri Genel Müdürlüğü, Cilt No: 29.
  • Lee, M., Zhang, Y., Chen, S., Spencer , E., Cruz , J. D., Hong, H. ve Marciano, R. (2017). Heuristics for Assessing Computational Archival Science (CAS) Research - The Case of the Human Face of Big Data Project. Erişim Adresi: https://ieeexplore.ieee.org/document/8258179
  • Levi, A. S. (2013). Humanities big data. 2013 IEEE International Conference on Big Data. Erişim Adresi: https://pdfs.semanticscholar.org/b302/6e202008a321fa2e15b7668331be9f3cc8cf.pdf
  • Mahon, D. (2015). Focus on the active. Business Intelligence Journal, 19(4), 40-47.
  • Marciano, R., Lemieux, V., Hedges, M., Esteva, M., Underwood, W., Kurtz, M. ve Conrad, M. (2018). Archival records and training in the age of big data. Advances in Librarianship, 44(B), 179-199.
  • McDonald, J. ve Léveillé, J. V. (2014). Whither the retention schedule in the era of big data and open data?. Records Management Journal, 24(2), 99-121.
  • Moses, R. P. (2005). A Glossary of Archival and Records Terminology. Chicago: The Society of American Archivists.
  • Newell, B. C. (2014). Technopolicing, surveillance, and citizen oversight: a neorepublican theory of liberty and ınformation control. Government Information Quarterly, 31(3), 421-431.
  • Prescott, A. (2013). Bibliographic Records as Humanities Big Data. 55-58. Erişim Adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6691670
  • Rolan, G., Humphries, G., Jeffrey, L., Samaras, E., Antsoupova, T. ve Stuart, K. (2018). More human than human? artificial ıntelligence in the archive, Archives and Manuscripts, 47(2), 179-203.
  • Sakyi, K. T. (2016). Big Data: Understanding Big Data. Erişim Adresi: https://arxiv.org/abs/1601.04602
  • Shallcross, M. (2016). Appraising Digital Archives with Archivematica. 3272-3276. Erişim Adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7840985
  • Shepherd, E. J. ve Yeo, G. (2003). Managing Records: A Handbook of Principles and Practice. London: Facet Publishing.
  • Thompson, N., Ravindran, R., ve Nicosia, S. (2015). Government data does not mean data governance: lessons learned from a public sector application audit. Government Information Quarterly, 32(3), 316-322. Uribe, L. M. (2018). Digital Archives as Big Data. Mathematical Population Studies, 26(2), 69-79.
  • Ünal, M. A. ve Özdemirci, F. (2017). EBYS (e-BEYAS) ve e-arşiv sistemlerinde/uygulamalarında yapay zeka yaklaşımı. F. Özdemirci ve Z. Akdoğan (Ed.) Bilgi Sistemleri ve Bilişim Yönetimi Bildiriler Kitabı içinde (ss.57-63). Ankara: BİL-BEM.
  • Yong, M., Liming, L. ve Yongsheng, Q. (2015). Improvement of Big Data Retrieval Algorithm in the Intelligent Archives Management. Erişim Adresi: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7494245 adresinden 28.01.2019 tarihinde erişildi.

Details

Primary Language Turkish
Subjects Library and Information Studies
Journal Section Peer- Reviewed Articles
Authors

Mehmet Oytun CİBAROĞLU 0000-0002-5763-0770

Bahattin YALÇINKAYA This is me 0000-0003-2393-5207

Publication Date June 28, 2019
Submission Date May 27, 2019
Published in Issue Year 2019 Volume: 2 Issue: 1

Cite

APA CİBAROĞLU, M. O., & YALÇINKAYA, B. (2019). Belge ve Arşiv Yönetimi Süreçlerinde Büyük Veri Analitiği ve Yapay Zeka Uygulamaları. Bilgi Yönetimi, 2(1), 44-58. https://doi.org/10.33721/by.570634

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