References

• Abbott, D. (2008). What is digital curation. Erişim adresi: www.dcc.ac.uk/resources/briefing-papers/ introduc-tion-curation/what-digital-curation. google scholar
• AGIMO. (2013). AGIMO Big Data Strategy - Issues Paper. Erişim adresi: www.finance.gov.au/files/ 2013/03/ Big-Data-Strategy-Issues-Paper1.pdf. google scholar
• Ajis, A.F., Baharin, S.H. (2019). Dark Data Management as frontier of Information. Erişim adresi: https://iee-explore.ieee.org/document/8743915 google scholar
• Ayankoya, K..,Calitz, A.P., Greyling, J. (2014). Intrinsic relations between data science, big data, business analytics and datafication. ACM International Conference Proceeding Series 28 (2014), 192-198. google scholar
• Bates, M. (2015). The information professions: knowledge, memory, heritage. Information Research, 7 (1). Erişim adresi: www.informationr.net/ir/20-1/paper655.html#.WRx98jfTVLM (accessed 9 February 2018). google scholar
• Boulton, G. (2014, December). Open data and the future of science. Septentrio conference series (no. 1). Erişim adresi: https://septentrio.uit.no/index.php/SCS/article/view/3231. google scholar
• Business Intelligence Improved by Data Mining Algorithms and Big Data Systems: An Overview of Different Tools Asslied in Industrial Research. Computer Science and Information Technology 7 (1): 1-21, 2019. google scholar
• CA. (2016). Canada Capitalizing on Big Data. Erişim adresi: http://www.sshrc-crsh.gc.ca/news_room-salle_de_ presse/latest_ news-nouvell es_recentes/big_data_consultation-donnees_massives_consultation-eng.aspx. google scholar
• Carole, L. P. (2008). Research practices and research libraries: Working toward high impact information services. Erişim adresi: https://www.ideals.illinois.edu/ bitstream/handle/2142/9742/researchpracticieslibraries.sst. pdf?sequence=3. google scholar
• Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165-1188. google scholar
• Clark, T, D, Jones, M, C ve Armstrong, C, P. (2007). The dynamic structure of management sussort systems: theory development, research focus, and direction. MIS Quarterly, 31 (3) (2007), ss. 579-615 google scholar
• Chung, W. (2014). BizPro: Extracting and categorizing business intelligence fac- tors from textual news articles. International Journal of Information Management 34: 272-284. google scholar
• CNSF. (2015). National Science Foundation China. Retrieved from http://www.nsfc.gov.cn/. European Commission. 2014. Commission urges governments to embrace potential of big data. Erişim adresi: europa.eu/rapid/press-release_IP-14-769_en.htm. google scholar
• Cunningham, A. (2016). Describing archives in context: Peter J Scott and the Australian “series” system. In V. Lemieux (Ed.), Building trust in information: Perspectives on the frontiers of provenance (ss. 49-58). Berlin: Springer-Verlag, Research Triangle Park, NC. google scholar
• Çakın, İ. (2012). Bilgi profesyonellerinin eğitiminde 40 yıl: Hacettepe Üniver sitesinin lisans programındaki değişiklikler. Türk Kütüphaneciliği, 26(2), 262-290. google scholar
• Delen, D. Moscato,G., Toma, I.L. (2018). The impact of real-time business intelligence and advanced analytics on the behaviour of business decision makers. 2018 International Conference on Information Management and Processing (ICIMP). IEEE Xplore: 29 March 2018, DOI: 10.1109/ICIMP1.2018.8325840. google scholar
• Delen, D. (2014). Real-World Data Mining: Asslied Business Analytics and Decision Making. New Jersey:Pe-arson Education, Inc. google scholar
• Digital Curation Centre (2005). Digital curation and preservation: defining the research agenda for the next decad. Erişim adresi: www.dcc.ac.uk/sites/default/files/documents/data-forum/documents/events/Warwi-ck_Introduction.pdf . google scholar
• Diebold, F. X. (2012). A personal perspective on the origin(s) and develop- ment of “big data”: The phenomenon, the term, and the discipline (Scholarly Paper No. ID 2202843). Social Science Research Network. Erişim adresi: http://papers.ssrn.com/sol3/papers.cfm?abstract id=2202843. google scholar
• Dingwall, G., Marciano, R., Moore, R., & McLellan, E. (2007). From data to records: Preserving the geographic information system of the city of Vancouver. Archivaria, 64, 181-198. google scholar
• Duranti, L., & Michetti, G. (2015). The archival method: Rediscovering a research tradition. In A. Gilliland, A. Lau, & A. McKemmish (Eds.), Research in the archival multiverse. Clayton, Victoria, Australia: Monash University Publishing. google scholar
• Eckerson, W. (2010). Performance Dashboards: Measuring Monitoring and Managing Your Business. John Wiley & Sons, Inc. google scholar
• Elragal. A. (2014). ERP and big data: the inept couple, Procedia Technology, Vol. 16, 242-249. google scholar
• Eroshkin, S.Yu., Kameneva, N.A., Kovkov, D.V., Sukhoruko A.I. (2017). Conceptual system in the modern information management Procedia Computer Science 103 (2017) 609 - 612. II. International Symposium Intelligent Systems, INTELS 16, 5-7 October 2016, Moscow. google scholar
• European Commission. (2014). Commission urges governments to embrace potential of big data. Erişim adresi: europa.eu/rapid/press-release_IP-14-769_en.htm. google scholar
• Fairfielda, J. and Shteina, H. (2014). Big data, big problems: Emerging issues in the ethics of data science and journalism. Journal of Mass Media Ethics 29, 1 (2014), 38-51. google scholar
• Fan, J., Han, F., & Liu, H. (2014). Challenges of big data analysis. National Science Review, 1(2), 293-314. google scholar
• Feldman, R. (2013). Techniques and asslications for sentiment analysis. Communi- cations of the ACM, 56(4), 82-89. google scholar
• Ferran, N., Mor, E., & Minguillon, J. (2005). Towards personalization in digital libraries through ontologies. Library Management, 26(4/5), 206-217. google scholar
• Foley, E. ve Guillemette, M, G. (2010). What is Business Intelligence. International Journal of Business In-telligence Research, vol. 1, no. 4. google scholar
• Fresa, A., Justrell, B., Prandoni, C. (2015). Digital curation and quality standards for memory institutions: PREFORMA research Project. Archival Science (2015) 15: 191-216. google scholar
• Gandomi, A. Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35 (2): 137-144. google scholar
• Gopalakrishnan, S., Kessler, E., & Scillitoe, J. (2010). Navigating the innovation landscape: past research, present practice, and future trends. Organ. Manag. J., 7: 262-277. google scholar
• Hahn, U., & Mani, I. (2000). The challenges of automatic summarization. Computer, 33(11), 29-36. google scholar
• Heard, J., & Marciano, R. (2011). A system for scalable visualization of geographic archival records. In Proce-edings of the 1st IEEE Symposium on Large-Scale Data Analysis and Visualization (ss. 121-122). Erişim adresi: http://www.slideshare.net/richardjmarciano/a-system-for-scalablevisualization-of-geographic-arc-hival-records/ google scholar
• Hey, T. , Tansley, S. and Tolle, K. (2009). The Fourth Paradigm: Data-Intensive Scientific Discovery. Erişim adresi: http://research.microsoft.com/en-us/collaboration/fourthparadigm/: 2032-2033. google scholar
• Higgins, S. (2017). Time to become our own profession?. Digital Preservation Coalition Blog. Erişim adresi: www.dpconline.org/blog/time-to-become-our-own-profession google scholar
• Higgins, S. (2018). Digital curation: the development of a discipline within information science. Journal of Documentation, 74 (6): 1318-1338. google scholar
• Hirtle, P.B. (2008). The history and current state of digital preservation in the United States, in Westbrooks, E. and Jenkins, K. (Eds), Metadata and Digital Collections: A Festschrift in google scholar
• Huang, R. H., & Li, B. Y. (2016). Data literacy education: Expansion of information lit-eracy instruction in the big data era. Document, Information & Knowledge, 1, 21-27. google scholar
• Jiang, J. (2012). Information extraction from text. In C. C. Aggarwal, & C. Zhai (Eds.), Mining text data (ss. 11-41). United States: Springer. google scholar
• Janssen, H. van der Voort, A. Wahyudi. (2012). Factors influencing big data decision-making quality”, Journal of Business Research, vol. 70, ss. 338-345. google scholar
• Johnson, A. P. (2002). A Short guide to action research. Boston: Allyn & Bacon. google scholar
• Katerina B., Dimovski, V. (2019). Business intelligence and analytics for value creation: The role of absorptive capacity. International Journal of Information Management (46):93-103 google scholar
• Kelly, K. (2012). The quantified century. In Quantified Self Conference. Retrieved from http://quantifiedself. com/conference/Palo-Alto-2012. google scholar
• Khan, R. A.and S. M. K. Quadri. (2012). Business intelligence: an integrated assroach, Business Intelligence Journal, Vol.5, No.1, 64-70. google scholar
• Kooiman, J. (2015E). Fish for life, interactive governance for fisheries. Amsterdam: Amsterdam University Press. google scholar
• Kourentzes, N., Petropoulos, F. and Trapero, J.R. (2014), “Improving forecasting by estimating time series structural components across multiple frequencies”, International Journal of Forecasting, Vol. 30 No. 2, ss. 291-302. google scholar
• Kwon, O., Lee, N., & Shin, B. (2014). Data quality management, data usage expe- rience and acquisition inten-tion of big data analytics. International Journal of Information Management, 34(3), 387-394. google scholar
• Külcü, Ö. (2018). Bilgi Kuramı ve Bilgi Yönetimi. İstanbul. Hiper Yayın. google scholar
• Labrinidis, A., & Jagadish, H. V. (2012). Challenges and ossortunities with big data. Proceedings of the VLDB Endowment, 5(12), 2032-2033. google scholar
• Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. 6(70). META Group Research Note. google scholar
• Lemieux, V. (2012). Using information visualization and visual analytics to achieve a more sustainable future for archives: A survey and critical analysis of some developments. Comma, 2012(2), 5570. google scholar
• Lemieux, V. (2014). Towards a ‘third order’ archival interface: Research notes on some theoretical and practical implications of visual explorations in the Canadian context of financial electronic records. Archivaria, 78, 53-93. google scholar
• Li, S., Jiao, F. Zhang, Y., Xu, X. (2019). Problems and Changes in Digital Libraries in the Age of Big Data From the Perspective of User Services. The Journal of Academic Librarianship. 45 (1): 22-30. google scholar
• Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies, 5(1), 1-167. google scholar
• Longbing, C. (2017). Data Science: A Comprehensive Overview. ACM Computing Surveys. 50 (3): 43.1-43.42 google scholar
• Loukides, M. (2011). The Evolution of Data Products. O’Reilly, Cambridge. google scholar
• Marciano, R., Lemieux, V., Hedges, M., Esteva, M., Underwood, W., Kurtz, M. & Conrad, google scholar
• Muntean, M., Sabau, G., Bologa, A., Surcel, T. and Florea, A. (2013), “Performance dashboards for universities”, 2nd International Conference on Manufacturing Engineering, Quality and Production Systems, ss. 206-211. google scholar
• Massaro, A., Vitti, V., Galiano, A., Morelli, A. (2019). Business Intelligence Improved by Data Mining Algo-rithms and Big Data Systems: An Overview of Different Tools Asslied in Industrial Research. Computer Science and Information Technology 7(1): 1-21 google scholar
• Massaro, A., Vitti, V. Lisco, P., Galiano, A., Savino, N. (2019). A business intelligence platform implemented in a big data system embedding data mining: a case of study. International Journal of Data Mining & Knowledge Management Process (IJDKP) 9 (1): 1-20. google scholar
• Mills, G. E. (2003). Action research: A guide for the teacher researcher. NJ: Merrill/Prentice Hall. google scholar
• Ong, I., Siew, P. and Wong, S. (2011), “A five-layered business intelligence architecture”, Communications of the IBIMA, ss. 1-11. google scholar
• Salo, D. (2010). Retooling libraries for the data challenge. Ariadne, 64. google scholar
• Scholtz, B., Calitz, A and Haupt, H. (2016). A business intelligence framework for sustainability information management in higher education. International Journal of Sustainability in Higher Education19 (2): 266-290 google scholar
• Shera, J. H. (1968). An epistemological foundation for library science. FRONTIERS OF LIBRARIANSHIP- 193 SYRACUSE UNIVERSITY (8), 7-&. Shepherd, S., Bunn, J., Flinn, A and Lomas, E. (2019). Open govern-ment data: critical information management perspectives. Records Management Journal 291(1/2): 152-167. google scholar
• Skeina, S. S. (2017). The Data Science Design Manual. New York: Springer. google scholar
• Sixin, X., Yayuan Y.,Jiang, Y. (2017). A New Governance Architecture for Government Information Resources based on Big Data Ecological Environment in China. 2017 IEEE International Symposium on Multimedi. DOI 10.1109/ISM.2017.103: 524-530 google scholar
• UK. (2016). UK Big Data. Erişim adresi: http://www.rcuk.ac.uk/research/infrastructure/big-data/. google scholar
• USD2D. (2016). US National Consortium for Data Science. Erişim adresi: data2discovery.org. google scholar
• UN. (2010). United Nation Global Pulse Projects. Erişim adresi: http://www.unglobalpulse.org/. google scholar
• USNSF. 2012. US Big Data Research Initiative. Erişim adresi: http://www.nsf.gov/cise/news/bigdata.jsp. google scholar
• Uthayasankar, S. Kamal, M., Irani, Z., Weerakkody, V. (2017). Critical analysis of Big Data challenges and analytical methods. Journal of Business Research (70), January 2017: 263-286 google scholar
• Uzuner, Y. (2005). Özel eğitimden örneklerle eylem araştırmaları. Ankara Üniversitesi Eğitim Fakültesi Özel Eğitim Dergisi, 6(2), 1 - 12. google scholar
• TechAmerica Foundation’s Federal Big Data Commission. (2012). Demystifying big data: A practical guide to transforming the business of Government. Erişim adresi: http://www.techamerica.org/Docs/fileManager. cfm?f=techamerica- bigdatareport-final.pdf google scholar
• Tonta, Y. (2012). Kütüphanecilik ve bilgi bilim eğitiminde gelişmeler ve program değişiklikleri. Türk Kütüp-haneicliği 26 (2): 227-261) google scholar
• Uslu, M. (2016). Veri Biliminde Veri Analitiği Tipleri. Erişim adresi:https://kod5.org/veri-biliminde-veri-ana-litigi-tipleri/. google scholar
• Xu, S., Du, W., Wang, C., & Liu, D. (2017). The library big data research: Status and libraries in China. Library Work and Study, 7, 46-50. google scholar
• Wang, X. Y. (2015). Analysis of and reflection on the asslication of big data in university libraries. Journal of Academic Library and Information Science, 33(1), 55-60. google scholar
• Winling, L., Connolly, N., Nelson, R., & Marciano R. (2017). Integrating the Depression-era history of race and redlining. In I. Gregory & D. Lafreniere (Eds.), Routledge handbook of spatial history, (ss. 502-524). New York, NY: Routledge. google scholar
• Wu, K., Su, X. N., & Deng, S. H. (2013). Big data, cloud computing and user behavior analysis. Digital Library Forum. 6. Digital Library Forum (ss. 19-23). google scholar
• Wu, X. et al. (2008). Top 10 algorithms in data mining, Knowl. Inf. Syst., v.14, 1-37. google scholar
• Wyk, J., Walt, I. (2018). A Research Data Management Readiness Training Toolkit. International Data Week 2018, SciDataCon 2018 Conference, 5-9 November 2018, Gaborone, Botswana. google scholar
• Yigitbasioglu, O.M. and Velcu, O. (2012), “A review of dashboards in performance management: implications for design and research”, International Journal of Accounting Information Systems, Vol. 13 No. 1, ss. 41-59. google scholar
• Yiu, C. (2012). The Big Data Ossortunity. Erişim adresi: http://www.policyexchange.org.uk/images/publications/ thessortunity.pdf. google scholar