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Mark E S Bernard ‘Knowledge Cube’ based on DIKW Hierarchy, Blooms Taxonomy, Knowledge Management Methodology
 

Mark E S Bernard ‘Knowledge Cube’ based on DIKW Hierarchy, Blooms Taxonomy, Knowledge Management Methodology

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Mark E S Bernard ‘Knowledge Cube’ based on DIKW Hierarchy, Blooms Taxonomy, Knowledge Management Methodology

Mark E S Bernard ‘Knowledge Cube’ based on DIKW Hierarchy, Blooms Taxonomy, Knowledge Management Methodology

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  • Within the power-point slide deck I am attempting to explain the subtle differences between data-information-knowledge and wisdom. This is import to understand for Knowledge Management purposes, Risk Management purposes and Information Security Management Systems to function appropriately. We need to identify what the class of asset is to effectively evaluate the threats and vulnerabilities are to it, arriving at an accurate risk assessment. Once completed properly this will lead to the application of more cost effective security measures and better protection of Corporate Knowledge a tangible, valued asset.
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    Mark E S Bernard ‘Knowledge Cube’ based on DIKW Hierarchy, Blooms Taxonomy, Knowledge Management Methodology Mark E S Bernard ‘Knowledge Cube’ based on DIKW Hierarchy, Blooms Taxonomy, Knowledge Management Methodology Presentation Transcript

    • Compiled by; Mark E.S. Bernard, ISO 27001 Lead Auditor,CISSP, CISM, SABSA-F2, CISA, CRISC, CGEIT *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • The Knowledge Cube was created to help visually describe the relationship between the DIKWHierarchy, Bloom’s Taxonomy and Knowledge Domains Tacit, Implicit and Explicit.The bases for this explanation is that while data, information, knowledge and wisdom are created andmaintained we as humans continuously improve it. Each iteration after iteration results in the constantimprovement of data, information, knowledge and wisdom. This iterative cycle consists ofunderstanding or comprehending the input data, information, knowledge or wisdom followed by theapplication, analysis, synthesis and finally the evaluation before the next iteration begins.Another important fact is that while we acknowledge the DIKW Hierarchy we must also understand thatduring the process of comprehension, application, analysis, synthesis and evaluation we usually branchout and back into to the process utilizing newly developed - current data, information and knowledge.This allows humans to automatically – on the fly improve each interactive cycle, sometimes reducingthe interactive cycle , to initiate a new cycle before the initial cycle has complete. In other words newknowledge of data and information or knowledge gathered could impose new improved steps withinthe current cycle even before it ends.In addition, our tacit, implicit and explicit knowledge holdings are constantly affected by improvementsas we move along the DIKW Hierarchy and apply Bloom’s Taxonomy cycle. This includes the applicationof new or improved data, information, knowledge or wisdom, and the synthesis of that new orimproved data, information, knowledge or wisdom as we evaluate /validate results and improvements. *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • Mark is an independent contractor who formerly worked in BC Government as a Director overseeing the Government’s payments systems and public accounts processing in excess of $42 billion annually in payments and as a Compliance manager in the BC Government Security Branch… Mark also spent time over seeing the Privacy and Security programs for EDS Advanced Solutions and Central 1 Credit Union.Mark was recognized by the Premier of New Brunswick for his volunteer work in the KnowledgeIndustry establishing the Atlantic Chapter of the High Technology Crime Investigation Association.Mark is also a regular volunteered with local professional associations for HTCIA, ISACA, ISSA, IIAand FMI. Mark has been published in trade magazines and on the Internet in addition to beingsought after as an expert by local radio, newspapers and television.While working in Toronto Mark volunteer on the annual Toronto Children’s Sick Kids Telethon androad a stationary bike on a marathon Juvenile Diabetes campaign. Mark has also volunteered withlocal Minor Hockey Minor Fastball, Local Elementary School and Middle School, Boys Scots andassisted with raising money for the Mustard Seed Foods bank in conjunction with the annual NHLOld-Timers Challenge In Victoria BC. Mark is continuing to contribute his knowledge throughISACA with the development of Cloud Computing whitepaper and the Canadian StandardsInstitute’s workgroup updating ISO/IEC 27001:2012 – Information Security Management Systemsframework. *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • Define Data-Information-Knowledge-WisdomData can be defined as conscious and unconscious observations associate with sensory input into ourbrains from smell, taste, touch, visual, auditory. These observations may be the result of naturallyoccurring or man made events object or the output of a process.Additional defining of Man made data using computers.Data amounts to the bits and bytes organized in 16, 32, 64, 128 blocks. When database developers andsoftware engineers design systems we build in layers of controls and self checking to minimize the riskassociated with data contamination and integrity issues. In some systems temporary work files arecreated to calculate summary totals. These temporary files need to be overwritten or deleted andrecreated. These functions and callouts associated with modular program design need to be thoroughlytested so not to leave data behind or unprotected during production environment usage. It is alsopossible for database architecture to be used to help anonymize sensitive data by isolating certain datasets from each other. The level acceptance checking is often completed by software and systemsengineers. The data used to conduct testing should be constructed and not pulled from the customerdatabase. An example of a risk would be corrupted data caused by a software bug or virus. *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • Define Data-Information-Knowledge-WisdomInformation can be defined as the processing of data by our brains or man made devices applying somerationale and/or logical analytical process to achieve a desired outcome which could be as basic asunderstanding the relationship of input data with our observation of an object.Additional defining of Man made Information using computers.Information amounts to the output of data processing, parsing data segments together, businessintelligence data mining program. Information requires a higher level of integrity checking because nowinstead of checking the quality of bits and bytes we are validating content and applicability at the recordkeeping level. This level of validation checking is completed by business managers and customers. Theinformation used to facilitate user acceptance testing with the customer is based on real production orscrambled version of production information to recreate an environment as close as possible to realityfurther reducing risk of errors. An example of a risk would be inaccurate information because of thewrong files being used to pull data for processing or the human entering the information entered thewrong data. *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • Define Data-Information-Knowledge-WisdomKnowledge can be defined as the additional processing of information during the process of application,analysis, syntheses and evaluation of information resulting in a reducing of information initially requiredresulting in a more concise explanation of the object or relationships between multiple objects, eventsencountered during the process and lessons learned to improve the accuracy and effectiveness of theknowledge.Wisdom can be defined as the experience derived from iterative applications of knowledge to achieve ahigher order of understanding of nature and potential events /situations for future decision making andrationalization that can be projected forward or applied to real time situations. *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • In order to define what knowledge is it’s necessary to distinguish between data –information – knowledge and wisdom. There is constant uptake of each and intersectionsbetween each as they evolve to the next level of refinement and usefulness. I created the‘Knowledge Cube’ as a graphical representation of each element and I leveraged a fewpopular methodologies and standards to try and explain these interactions. *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • As D-I-K-W developsfollowing the CAASEKSystem the data is rolledup and parsed intoinformational records.Information records areleveraged to developknowledge concerningvarious related and non-related topics andsubjects again followingthe CAASEK System.As knowledge gets tested and refined Wisdom appears requiring reduced effort with a significantdrop in errors associated with the application of knowledge. During the entire process thisknowledge is recorded, stored in long term and short term memory within the human brain as tacitand explicit knowledge. Eventually some of this knowledge will be recorded and shared as explicitknowledge. *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • As D-I-K-W develops the volume is reduced requiring few characters orsymbols to achieve the goal for access and usage or application. *** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***
    • For more information contact http://www.linkedin.com/in/markesbernard*** THIS DOCUMENT IS CLASSIFIED FOR PUBLIC ACCESS ***