{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:26:03Z","timestamp":1781105163903,"version":"3.54.1"},"reference-count":47,"publisher":"IGI Global Scientific Publishing","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,1,1]]},"abstract":"<p>This article analyzes the properties of unknown faults in knowledge management and Big Data systems processing Big Data in real-time. These faults introduce risks and threaten the knowledge pyramid and decisions based on knowledge gleaned from volumes of complex data. The authors hypothesize that not yet encountered faults may require fault handling, an analytic model, and an architectural framework to assess and manage the faults and mitigate the risks of correlating or integrating otherwise uncorrelated Big Data, and to ensure the source pedigree, quality, set integrity, freshness, and validity of the data. New architectures, methods, and tools for handling and analyzing Big Data systems functioning in real-time will contribute to organizational knowledge and performance. System designs must mitigate faults resulting from real-time streaming processes while ensuring that variables such as synchronization, redundancy, and latency are addressed. This article concludes that with improved designs, real-time Big Data systems may continuously deliver the value of streaming Big Data.<\/p>","DOI":"10.4018\/ijkm.2018010103","type":"journal-article","created":{"date-parts":[[2018,2,28]],"date-time":"2018-02-28T10:19:25Z","timestamp":1519813165000},"page":"30-50","source":"Crossref","is-referenced-by-count":5,"title":["Our Knowledge Management Hubble May Need Glasses"],"prefix":"10.4018","volume":"14","author":[{"given":"William H.","family":"Money","sequence":"first","affiliation":[{"name":"The Citadel, Charleston, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen J.","family":"Cohen","sequence":"additional","affiliation":[{"name":"Microsoft Corporation, Oakton, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJKM.2018010103-0","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465272"},{"key":"IJKM.2018010103-1","doi-asserted-by":"crossref","unstructured":"Borgatti, S. P., Mehra, A., Brass, D. J., & Labianca, G. (2009). Network analysis in the social sciences. science, 323(5916), 892-895.","DOI":"10.1126\/science.1165821"},{"issue":"4","key":"IJKM.2018010103-2","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.2307\/41703503","article-title":"Business intelligence and analytics: From big data to big impact.","volume":"36","author":"H.Chen","year":"2012","journal-title":"Management Information Systems Quarterly"},{"key":"IJKM.2018010103-3","doi-asserted-by":"publisher","DOI":"10.1007\/s11704-013-3903-7"},{"key":"IJKM.2018010103-4","doi-asserted-by":"publisher","DOI":"10.24251\/HICSS.2017.121"},{"key":"IJKM.2018010103-5","unstructured":"Cooney, M. (2015). FAA: 2 million lines of code process new air traffic system. Retrieved 5-31-2016 from http:\/\/www.networkworld.com\/article\/2917198\/software\/faa2-million-lines-of-code-process-new-air-traffic-system.html"},{"issue":"7","key":"IJKM.2018010103-6","first-page":"2818","article-title":"Hadoop Architecture and Fault Tolerance Based Hadoop Clusters in Geographically Distributed Data Center","volume":"10","author":"T.Cowsalya","year":"2015","journal-title":"Journal of Engineering and Applied Sciences (Asian Research Publishing Network)"},{"key":"IJKM.2018010103-7","author":"G. J.Da Silva","year":"2010","journal-title":"Partial fault tolerance in stream processing applications-Methods and evaluation techniques"},{"key":"IJKM.2018010103-8","unstructured":"Dalal, N. (2012). \u201cWisdom Computing: Toward a Framework for Wisdom Research in Information Systems\u201d AMCIS 2012 Proceedings. Paper 14. Retrieved from http:\/\/aisel.aisnet.org\/amcis2012\/proceedings\/PerspectivesIS\/14"},{"key":"IJKM.2018010103-9","unstructured":"Das, S., & Qiao, J. (2014, November 25). Gobblin\u2019 Big Data With Ease. LinkedIn.com. Retrieved 6-7-2016 from https:\/\/engineering.linkedin.com\/data-ingestion\/gobblin-bigdata-ease"},{"key":"IJKM.2018010103-10","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2009.2021005"},{"key":"IJKM.2018010103-11","unstructured":"Dictionary.com. (2016). \u201cresiliency,\u201d in Collins English Dictionary - Complete & Unabridged 10th Edition. HarperCollins Publishers. Retrieved 6-12-2016 from http:\/\/www.dictionary.com\/browse\/resiliency"},{"key":"IJKM.2018010103-12","unstructured":"FAA.gov. (2016, February 29). Data, Visualization, Analysis, and Reporting System (DVARS) Draft Section C, Statement of Work (SOW). Retrieved 5-31-2016 from https:\/\/faaco.faa.gov\/index.cfm\/announcement\/view\/23741"},{"key":"IJKM.2018010103-13","doi-asserted-by":"publisher","DOI":"10.1093\/nsr\/nwt032"},{"key":"IJKM.2018010103-14","unstructured":"\u201cFault Tolerance and Processing Semantics in Apache Apex.\u201d (March 24, 2016). http:\/\/www.slideshare.net\/ApacheApexOrganizer\/webinarfault-toleranceandprocessingsemantics"},{"key":"IJKM.2018010103-15","unstructured":"Finnegan, M. (2013, March 6). Boeing 787s to create half a terabyte of data per flight, says Virgin Atlantic. Computerworld UK, 6. Retrieved 6-7-2016 from http:\/\/www.computerworlduk.com\/news\/data\/boeing-787screate-half-terabyte-of-data-per-flight-says-virgin-atlantic3433595\/"},{"key":"IJKM.2018010103-16","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2014.10.007"},{"key":"IJKM.2018010103-17","doi-asserted-by":"publisher","DOI":"10.5465\/amj.2014.4002"},{"key":"IJKM.2018010103-18","doi-asserted-by":"publisher","DOI":"10.1145\/3158421.3158427"},{"key":"IJKM.2018010103-19","doi-asserted-by":"publisher","DOI":"10.4018\/ijkm.2013070102"},{"key":"IJKM.2018010103-20","unstructured":"Juvva, K. (Spring, 1998). Real-Time Systems. Carnegie Mellon University, Pittsburg. Retrieved 4-23-2016 from https:\/\/users.ece.cmu.edu\/~koopman\/des_s99\/real_time\/"},{"key":"IJKM.2018010103-21","doi-asserted-by":"crossref","unstructured":"Kaisler, S. Armour, F., Espinosa, J. A., & Money, W. (2013, January). Big data: issues and challenges moving forward. In Proceedings of the201346th Hawaii International Conference on System Sciences (pp. 995-1004). IEEE.","DOI":"10.1109\/HICSS.2013.645"},{"key":"IJKM.2018010103-22","doi-asserted-by":"publisher","DOI":"10.1057\/ejis.2013.10"},{"key":"IJKM.2018010103-23","doi-asserted-by":"crossref","unstructured":"Ma, K. L., & Muelder, C. W. (2013). Large-scale graph visualization and analytics. Computer, 46(7), 39-46. Retrieved 6-14-2016 from https:\/\/www.computer.org\/csdl\/mags\/co\/2013\/07\/mco201307 0039-abs.html","DOI":"10.1109\/MC.2013.242"},{"key":"IJKM.2018010103-24","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2012.50"},{"key":"IJKM.2018010103-25","doi-asserted-by":"publisher","DOI":"10.1145\/2618243.2618288"},{"key":"IJKM.2018010103-26","unstructured":"Mall, R. (2009). Real-time systems: theory and practice. Pearson Education India. Retrieved from https:\/\/books.google.com\/books?id=coPT7vaEjFsC"},{"issue":"10","key":"IJKM.2018010103-27","first-page":"61","article-title":"Big data. The management revolution.","volume":"90","author":"A.McAfee","year":"2012","journal-title":"Harvard Business Review"},{"key":"IJKM.2018010103-28","unstructured":"Microsoft Customer Stories. (2015). Predicting student dropout risks, increasing graduation rates with cloud analytics. Retrieved 6-7-2016 from http:\/\/enterprise.microsoft.com\/enus\/industries\/citynext\/tacoma-public-schools\/"},{"issue":"4","key":"IJKM.2018010103-29","first-page":"39","article-title":"Designing resilient engineered systems.","volume":"102","author":"S. M.Mitchell","year":"2006","journal-title":"Chemical Engineering Progress"},{"key":"IJKM.2018010103-30","unstructured":"Parashar, M. (2014). Big Data Analytics for Power Grid Operations. In Proceedings of the IEEE-Northwest Energy Systems Symposium (NWESS). Alston Grid, Inc."},{"key":"IJKM.2018010103-31","unstructured":"Pepelniak, I. (2013, August 13). Management. Control, and Data Planes in Network Devices and Software. inSpace. Retrieved 6-2-2016 from http:\/\/blog.ipspace.net\/2013\/08\/management-control-anddata-planes-in.html"},{"key":"IJKM.2018010103-32","author":"R. S.Pressman","year":"2005","journal-title":"Software engineering: a practitioner\u2019s approach"},{"key":"IJKM.2018010103-33","article-title":"Real time machine learning to find fast transient radio anomalies: A semi-supervised approach combining detection and RFI excision.","author":"C.Reed","year":"2011","journal-title":"Proc. Int\u2019l Astronomical Union Symp. Time Domain Astronomy."},{"key":"IJKM.2018010103-34","unstructured":"Rennels, D. A. (1998). Fault Tolerant Computing. Retrieved from http:\/\/web.cs.ucla.edu\/~rennels\/article98.pdf Last accessed 614-2016"},{"key":"IJKM.2018010103-35","doi-asserted-by":"publisher","DOI":"10.2307\/41165944"},{"key":"IJKM.2018010103-36","unstructured":"Smith, C. (2016, June 2). By the Numbers: 125+ Amazing LinkedIn Statistics. Expandedramblings. Retrieved 6-7-2016 from http:\/\/expandedramblings.com\/index.php\/by-the-numbers-afew-important-linkedin-stats\/"},{"key":"IJKM.2018010103-37","unstructured":"PAKT Use. (2015). A Practical Guide to Building a Stream Data Platform (Part 1). confluent.io. Retrieved 5-1-2016 from http:\/\/www.confluent.io\/blog\/stream-dataplatform-1\/ Last accessed ."},{"key":"IJKM.2018010103-38","unstructured":"Vachon, B. (2012, May 18). CCNA security portable command guide. Pearson Education.in CCNA Security (640554) Portable Command Guide. Cisco Press."},{"key":"IJKM.2018010103-39","unstructured":"W\u00e4hner, K. (2014). Real-time stream processing as game changer in a big data world with Hadoop and data warehouse. InfoQ (September 10, 2014)."},{"key":"IJKM.2018010103-40","doi-asserted-by":"publisher","DOI":"10.1111\/jbl.12010"},{"key":"IJKM.2018010103-41","unstructured":"Weinberger, D. (2012). Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room. Basic Books."},{"key":"IJKM.2018010103-42","volume":"Vol. 31","author":"E. O.Wilson","year":"1999","journal-title":"Consilience: The unity of knowledge"},{"key":"IJKM.2018010103-43","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.197"},{"key":"IJKM.2018010103-44","doi-asserted-by":"crossref","unstructured":"Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE transactions on knowledge and data engineering, 26(1), 97-107.","DOI":"10.1109\/TKDE.2013.109"},{"key":"IJKM.2018010103-45","author":"S. J.Young","year":"1982","journal-title":"Real time languages"},{"key":"IJKM.2018010103-46","unstructured":"Zhu, Q., Chen, L., & Agrawal, G. (april, 2008). Supporting fault-tolerance in streaming grid applications. In Proceedings of the IEEE International Symposium on Parallel and Distributed Processing IPDPS \u201908. IEEE."}],"container-title":["International Journal of Knowledge Management"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=201525","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T17:49:07Z","timestamp":1651859347000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJKM.2018010103"}},"subtitle":["Designing for Unknown Real-Time Big Data System Faults"],"short-title":[],"issued":{"date-parts":[[2018,1,1]]},"references-count":47,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,1]]}},"URL":"https:\/\/doi.org\/10.4018\/ijkm.2018010103","relation":{},"ISSN":["1548-0666","1548-0658"],"issn-type":[{"value":"1548-0666","type":"print"},{"value":"1548-0658","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,1,1]]}}}