119 Knowledge Base Success Criteria

What is involved in Knowledge Base

Find out what the related areas are that Knowledge Base connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Knowledge Base thinking-frame.

How far is your company on its Knowledge Base journey?

Take this short survey to gauge your organization’s progress toward Knowledge Base leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.

To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.

Start the Checklist

Below you will find a quick checklist designed to help you think about which Knowledge Base related domains to cover and 119 essential critical questions to check off in that domain.

The following domains are covered:

Knowledge Base, Library 2.0, Snow Crash, Inference engine, Topic map, Knowledge management, Information repository, Rule-based system, Hilbert’s program, Information storage, Web 2.0, Knowledge Graph, Logic programming, Application-Level Profile Semantics, Library classification, Knowledge extraction, Logical atomism, Personal knowledge base, Semantic network, Versant Object Database, Semantic reasoner, Internationalized Resource Identifier, Lotus Notes, Semantic analytics, World Brain, Characteristica universalis, Data Web, Web engineering, RDF Schema, Enterprise bookmarking, The Engine, Semantic triple, Calculus ratiocinator, Hypertext Transfer Protocol, Semantically-Interlinked Online Communities, Question answering, Common Logic, Semantic publishing, Automated reasoning, Uniform Resource Identifier, Knowledge-based system, Web Science Trust, Knowledge Base, Mind map, World Wide Web, Rule Interchange Format, Knowledge retrieval, Semantic search, Knowledge representation and reasoning, Research resource identifier:

Knowledge Base Critical Criteria:

Learn from Knowledge Base tactics and finalize specific methods for Knowledge Base acceptance.

– Do we support the certified Cybersecurity professional and cyber-informed operations and engineering professionals with advanced problem-solving tools, communities of practice, canonical knowledge bases, and other performance support tools?

– Do those selected for the Knowledge Base team have a good general understanding of what Knowledge Base is all about?

– Why is it important to have senior management support for a Knowledge Base project?

– Can specialized social networks replace learning management systems?

– What is Effective Knowledge Base?

Library 2.0 Critical Criteria:

Analyze Library 2.0 governance and catalog Library 2.0 activities.

– Will Knowledge Base have an impact on current business continuity, disaster recovery processes and/or infrastructure?

– Among the Knowledge Base product and service cost to be estimated, which is considered hardest to estimate?

– How do we ensure that implementations of Knowledge Base products are done in a way that ensures safety?

Snow Crash Critical Criteria:

Adapt Snow Crash management and report on developing an effective Snow Crash strategy.

– What will be the consequences to the business (financial, reputation etc) if Knowledge Base does not go ahead or fails to deliver the objectives?

– Are we making progress? and are we making progress as Knowledge Base leaders?

– Who will provide the final approval of Knowledge Base deliverables?

Inference engine Critical Criteria:

Check Inference engine tasks and create a map for yourself.

– Do several people in different organizational units assist with the Knowledge Base process?

– Which individuals, teams or departments will be involved in Knowledge Base?

Topic map Critical Criteria:

Consult on Topic map results and overcome Topic map skills and management ineffectiveness.

– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Knowledge Base models, tools and techniques are necessary?

– Is the Knowledge Base organization completing tasks effectively and efficiently?

– What is the purpose of Knowledge Base in relation to the mission?

Knowledge management Critical Criteria:

Start Knowledge management strategies and define Knowledge management competency-based leadership.

– Learning Systems Analysis: once one has a good grasp of the current state of the organization, there is still an important question that needs to be asked: what is the organizations potential for developing and changing – in the near future and in the longer term?

– Meeting the challenge: are missed Knowledge Base opportunities costing us money?

– How do we manage Knowledge Base Knowledge Management (KM)?

– When is Knowledge Management Measured?

– How is Knowledge Management Measured?

Information repository Critical Criteria:

Detail Information repository projects and interpret which customers can’t participate in Information repository because they lack skills.

– What are your key performance measures or indicators and in-process measures for the control and improvement of your Knowledge Base processes?

– Which customers cant participate in our Knowledge Base domain because they lack skills, wealth, or convenient access to existing solutions?

– Does Knowledge Base analysis isolate the fundamental causes of problems?

Rule-based system Critical Criteria:

Administer Rule-based system tactics and document what potential Rule-based system megatrends could make our business model obsolete.

– What are your most important goals for the strategic Knowledge Base objectives?

– Do you monitor the effectiveness of your Knowledge Base activities?

– Are accountability and ownership for Knowledge Base clearly defined?

Hilbert’s program Critical Criteria:

Chat re Hilbert’s program issues and find the essential reading for Hilbert’s program researchers.

– What are the Essentials of Internal Knowledge Base Management?

– What is our formula for success in Knowledge Base ?

– How do we maintain Knowledge Bases Integrity?

Information storage Critical Criteria:

Huddle over Information storage adoptions and modify and define the unique characteristics of interactive Information storage projects.

– What are specific Knowledge Base Rules to follow?

– Are there Knowledge Base problems defined?

– Why are Knowledge Base skills important?

Web 2.0 Critical Criteria:

Infer Web 2.0 goals and don’t overlook the obvious.

– Consider your own Knowledge Base project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?

– How do we keep improving Knowledge Base?

Knowledge Graph Critical Criteria:

Win new insights about Knowledge Graph results and separate what are the business goals Knowledge Graph is aiming to achieve.

– What tools do you use once you have decided on a Knowledge Base strategy and more importantly how do you choose?

– What are our needs in relation to Knowledge Base skills, labor, equipment, and markets?

– How will we insure seamless interoperability of Knowledge Base moving forward?

Logic programming Critical Criteria:

Win new insights about Logic programming risks and display thorough understanding of the Logic programming process.

– Think about the functions involved in your Knowledge Base project. what processes flow from these functions?

– Does Knowledge Base systematically track and analyze outcomes for accountability and quality improvement?

Application-Level Profile Semantics Critical Criteria:

Brainstorm over Application-Level Profile Semantics issues and probe Application-Level Profile Semantics strategic alliances.

– How can we incorporate support to ensure safe and effective use of Knowledge Base into the services that we provide?

Library classification Critical Criteria:

Steer Library classification failures and finalize specific methods for Library classification acceptance.

– In a project to restructure Knowledge Base outcomes, which stakeholders would you involve?

Knowledge extraction Critical Criteria:

Analyze Knowledge extraction decisions and devote time assessing Knowledge extraction and its risk.

– When a Knowledge Base manager recognizes a problem, what options are available?

– What are the Key enablers to make this Knowledge Base move?

Logical atomism Critical Criteria:

Drive Logical atomism visions and document what potential Logical atomism megatrends could make our business model obsolete.

– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Knowledge Base. How do we gain traction?

– What knowledge, skills and characteristics mark a good Knowledge Base project manager?

Personal knowledge base Critical Criteria:

Start Personal knowledge base goals and visualize why should people listen to you regarding Personal knowledge base.

– What other organizational variables, such as reward systems or communication systems, affect the performance of this Knowledge Base process?

Semantic network Critical Criteria:

Own Semantic network projects and explain and analyze the challenges of Semantic network.

– Think of your Knowledge Base project. what are the main functions?

– Do we all define Knowledge Base in the same way?

Versant Object Database Critical Criteria:

Revitalize Versant Object Database results and describe the risks of Versant Object Database sustainability.

– To what extent does management recognize Knowledge Base as a tool to increase the results?

– How do we go about Securing Knowledge Base?

Semantic reasoner Critical Criteria:

Jump start Semantic reasoner results and ask questions.

– How does the organization define, manage, and improve its Knowledge Base processes?

Internationalized Resource Identifier Critical Criteria:

Be responsible for Internationalized Resource Identifier quality and acquire concise Internationalized Resource Identifier education.

– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Knowledge Base?

– How do we measure improved Knowledge Base service perception, and satisfaction?

Lotus Notes Critical Criteria:

Trace Lotus Notes results and research ways can we become the Lotus Notes company that would put us out of business.

– what is the best design framework for Knowledge Base organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?

– What are current Knowledge Base Paradigms?

Semantic analytics Critical Criteria:

Co-operate on Semantic analytics tasks and explain and analyze the challenges of Semantic analytics.

– What are our best practices for minimizing Knowledge Base project risk, while demonstrating incremental value and quick wins throughout the Knowledge Base project lifecycle?

– How important is Knowledge Base to the user organizations mission?

– How much does Knowledge Base help?

World Brain Critical Criteria:

Disseminate World Brain projects and finalize specific methods for World Brain acceptance.

– What tools and technologies are needed for a custom Knowledge Base project?

– Do Knowledge Base rules make a reasonable demand on a users capabilities?

Characteristica universalis Critical Criteria:

X-ray Characteristica universalis engagements and adjust implementation of Characteristica universalis.

– What are the barriers to increased Knowledge Base production?

– Does the Knowledge Base task fit the clients priorities?

Data Web Critical Criteria:

Consolidate Data Web management and grade techniques for implementing Data Web controls.

– How do senior leaders actions reflect a commitment to the organizations Knowledge Base values?

– Is a Knowledge Base Team Work effort in place?

Web engineering Critical Criteria:

Look at Web engineering outcomes and gather practices for scaling Web engineering.

RDF Schema Critical Criteria:

Understand RDF Schema tasks and secure RDF Schema creativity.

– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Knowledge Base?

– Risk factors: what are the characteristics of Knowledge Base that make it risky?

Enterprise bookmarking Critical Criteria:

Prioritize Enterprise bookmarking tasks and intervene in Enterprise bookmarking processes and leadership.

– How do you determine the key elements that affect Knowledge Base workforce satisfaction? how are these elements determined for different workforce groups and segments?

– Do we have past Knowledge Base Successes?

The Engine Critical Criteria:

Transcribe The Engine strategies and report on setting up The Engine without losing ground.

– When the engineering team is satisfied, and pushes the new features to a full automation run, including load testing, how long does it take to declare the service ready to use?

– How do we Identify specific Knowledge Base investment and emerging trends?

– Is Knowledge Base Required?

– Where are the Engineers?

Semantic triple Critical Criteria:

X-ray Semantic triple failures and revise understanding of Semantic triple architectures.

– How will you measure your Knowledge Base effectiveness?

– Who sets the Knowledge Base standards?

Calculus ratiocinator Critical Criteria:

Face Calculus ratiocinator leadership and look at the big picture.

– What are your results for key measures or indicators of the accomplishment of your Knowledge Base strategy and action plans, including building and strengthening core competencies?

– Who are the people involved in developing and implementing Knowledge Base?

Hypertext Transfer Protocol Critical Criteria:

Review Hypertext Transfer Protocol planning and customize techniques for implementing Hypertext Transfer Protocol controls.

– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Knowledge Base services/products?

Semantically-Interlinked Online Communities Critical Criteria:

Recall Semantically-Interlinked Online Communities visions and summarize a clear Semantically-Interlinked Online Communities focus.

– What new services of functionality will be implemented next with Knowledge Base ?

– What about Knowledge Base Analysis of results?

– Are we Assessing Knowledge Base and Risk?

Question answering Critical Criteria:

Model after Question answering planning and don’t overlook the obvious.

Common Logic Critical Criteria:

Accelerate Common Logic risks and arbitrate Common Logic techniques that enhance teamwork and productivity.

Semantic publishing Critical Criteria:

Refer to Semantic publishing leadership and oversee Semantic publishing management by competencies.

– Does Knowledge Base create potential expectations in other areas that need to be recognized and considered?

– Why should we adopt a Knowledge Base framework?

Automated reasoning Critical Criteria:

Bootstrap Automated reasoning results and point out Automated reasoning tensions in leadership.

– How do mission and objectives affect the Knowledge Base processes of our organization?

– What are internal and external Knowledge Base relations?

Uniform Resource Identifier Critical Criteria:

Troubleshoot Uniform Resource Identifier quality and report on setting up Uniform Resource Identifier without losing ground.

Knowledge-based system Critical Criteria:

Add value to Knowledge-based system visions and visualize why should people listen to you regarding Knowledge-based system.

– What are the record-keeping requirements of Knowledge Base activities?

Web Science Trust Critical Criteria:

Confer over Web Science Trust goals and pay attention to the small things.

– Who is the main stakeholder, with ultimate responsibility for driving Knowledge Base forward?

Knowledge Base Critical Criteria:

Huddle over Knowledge Base risks and adjust implementation of Knowledge Base.

Mind map Critical Criteria:

Talk about Mind map results and probe using an integrated framework to make sure Mind map is getting what it needs.

– How do we make it meaningful in connecting Knowledge Base with what users do day-to-day?

World Wide Web Critical Criteria:

Frame World Wide Web decisions and know what your objective is.

– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new Knowledge Base in a volatile global economy?

– How do we know that any Knowledge Base analysis is complete and comprehensive?

Rule Interchange Format Critical Criteria:

Be responsible for Rule Interchange Format adoptions and devise Rule Interchange Format key steps.

– How will you know that the Knowledge Base project has been successful?

Knowledge retrieval Critical Criteria:

Focus on Knowledge retrieval risks and secure Knowledge retrieval creativity.

Semantic search Critical Criteria:

Discuss Semantic search strategies and summarize a clear Semantic search focus.

Knowledge representation and reasoning Critical Criteria:

Huddle over Knowledge representation and reasoning projects and get out your magnifying glass.

– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a Knowledge Base process. ask yourself: are the records needed as inputs to the Knowledge Base process available?

– What business benefits will Knowledge Base goals deliver if achieved?

Research resource identifier Critical Criteria:

Give examples of Research resource identifier adoptions and observe effective Research resource identifier.

– Think about the people you identified for your Knowledge Base project and the project responsibilities you would assign to them. what kind of training do you think they would need to perform these responsibilities effectively?


This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Knowledge Base Self Assessment:


Author: Gerard Blokdijk

CEO at The Art of Service | http://theartofservice.com



Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.

External links:

To address the criteria in this checklist, these selected resources are provided for sources of further research and information:

Knowledge Base External links:

Indiana University Knowledge Base

Knowledge Base for Precision Oncology

Carbonite Support Knowledge Base

Library 2.0 External links:

Library 2.0 | Tools, Publications & Resources

Last update – TicklishChild’s Library 2.0

NuGet Gallery | NETStandard.Library 2.0.1

Snow Crash External links:

Neal Stephenson – Snow Crash

Snow Crash (TV Movie) – IMDb

Inference engine External links:

Inference engine | computer science | Britannica.com

What is Inference Engine | IGI Global

Topic map External links:

Topic Map | Kauffman.org

[PDF]Accuplacer – Khan Academy Topic Map

[PDF]MultiNet Address Points User Guide Topic Map

Knowledge management External links:

A hub for technical knowledge management. — NDCAC

Lucidea | Knowledge Management Software

Knowledge Management Consulting Firm | Iknow LLC

Information repository External links:

[PDF]Collections Information Repository (CIR) Request …

Secure Information Repository[DOT HQ] – Sign In

Payment Information Repository (PIR)

Rule-based system External links:

[PDF]A Rule-Based System for Real-Time Analysis of …


What is rule-based system? Webopedia Definition

Hilbert’s program External links:

Hilbert’s program then and now – Philsci-Archive

Hilbert’s Program (Stanford Encyclopedia of Philosophy)

Friends of the SEP Society – Preview of Hilbert’s Program PDF

Information storage External links:

[PDF]Information Storage and Management—Storing, …

Home – HigherGround – Information Storage

Web 2.0 External links:

Web 2.0 Tools in Teaching and Learning – University …

Web 2.0 scientific calculator

web 2.0 lawyer

Knowledge Graph External links:

WTF is a knowledge graph? – Hacker Noon

Unigraph – The world’s largest Knowledge Graph

MAANA | Enterprise Knowledge Graph

Logic programming External links:

Logic programming (Book, 1991) [WorldCat.org]

[PDF]15-819K: Logic Programming Project Proposal TITLE

Logic programming (eBook, 1991) [WorldCat.org]

Application-Level Profile Semantics External links:

Application-Level Profile Semantics (ALPS)

Application-Level Profile Semantics (ALPS) – IETF …

Application-Level Profile Semantics · GitHub

Library classification External links:

Library classification | library science | Britannica.com

ERIC – Functions of Library Classification., 1988

Knowledge extraction External links:

Knowledge Extraction | K-Extractor | Lymba Corporation

GitHub – SCI2SUGR/KEEL: KEEL: Knowledge Extraction …

Logical atomism External links:

Logical Atomism | philosophy | Britannica.com

What is logical atomism? – ResearchGate

Semantic network External links:

ERIC – The Semantic Network Model of Creativity: …

1. Semantic Network Theory Flashcards | Quizlet

Versant Object Database External links:

Versant Object Database Arbitrary Commands Execution


Versant Object Database PowerPoint Presentation – …

Internationalized Resource Identifier External links:

IRI means Internationalized Resource Identifier – All …

Internationalized Resource Identifier (The Java™ …

Lotus Notes External links:

What Is Lotus Notes? – julian robichaux

How to Configure the Lotus Notes Client

[PDF]Lotus Notes Client Version 8.5 Reference Guide

Semantic analytics External links:

Semantic Analytics – Get Business Intelligence With …

[PDF]Semantic Analytics in Intelligence: Applying …

SciBite – The Semantic Analytics Company

Characteristica universalis External links:

Characteristica universalis – Revolvy
https://broom02.revolvy.com/topic/Characteristica universalis

CiteSeerX — Characteristica Universalis

Characteristica Universalis on Behance

Data Web External links:

PCS Data Web Center :: Login Page

MHEC Secure Data Web Home

Web engineering External links:

Rational Means | Web Engineering + Design

SIZER WEB ENGINEERING – automation.siemens.com

Web Engineering Düsseldorf (Düsseldorf, Germany) | Meetup

RDF Schema External links:

[PDF]An Indexing Scheme for RDF and RDF Schema based …

What is RDF Schema? Webopedia Definition

What is RDF Schema | IGI Global

Enterprise bookmarking External links:

Social Bookmarking vs. Enterprise Bookmarking – YouTube

Enterprise Bookmarking | Social Knowledge Management

The Engine External links:

The Engine Room

Car Bibles : The Engine Oil Bible

The Engine Shed

Calculus ratiocinator External links:

Calculus ratiocinator – YouTube

Hypertext Transfer Protocol External links:

Hypertext Transfer Protocol (HTTP) Status Code Registry

Hypertext Transfer Protocol (HTTP) – Techopedia.com

Question answering External links:

QANTA: A Deep Question Answering Model

[PDF]CHAPTER 28 Question Answering – Stanford University

[PDF]Question Answering – Stanford University

Common Logic External links:

Logic – Common Logic / Midnight Marauder – YouTube

[PDF]Common Logic Problems – wooster.edu

Common Logic – Home | Facebook

Semantic publishing External links:

Semantic Publishing (@scorvey) | Twitter

What is dynamic semantic publishing? | Semantics

Automated reasoning External links:

Automated Reasoning

ARChem: Automated Reasoning in Chemistry

Uniform Resource Identifier External links:

Uniform Resource Identifier (URI) Schemes

Uniform Resource Identifier (URI) Schemes

Uniform Resource Identifier (URI) list – 3GPP

Knowledge-based system External links:

[PDF]A Knowledge-Based System Design/Information …

Knowledge-Based Systems – Jones & Bartlett Learning

A Knowledge-based System for Hydraulic Maintenance …

Web Science Trust External links:

Web Science Trust – YouTube

Web Science Trust (@websciencetrust) | Twitter

Lyrics containing the term: Web Science Trust
https://www.lyrics.com/lyrics/Web Science Trust

Knowledge Base External links:

Knowledge Base

Indiana University Knowledge Base

Knowledge Base for Precision Oncology

Mind map External links:

Get M8! – Mind Map – Microsoft Store

Bubbl.us – brainstorm and mind map online

The Male Mind Map – Limited Time Offer | Sexy Confidence

World Wide Web External links:

IIS World Wide Web Publishing Service (W3SVC)

Rule Interchange Format External links:

[PDF]W3C rule interchange format – World Wide Web …

What is Rule Interchange Format? Webopedia Definition

What is Rule Interchange Format | IGI Global

Knowledge retrieval External links:

Knowledge Retrieval Jobs – Apply Now | CareerBuilder

Reference Knowledge Retrieval Jobs – careerbuilder.com

Semantic search External links:

Google Semantic Search – Google+

Semantic Search Marketing by Hunch Manifest

What is Semantic Search and Why Should I Care? | SEJ

Knowledge representation and reasoning External links:

CS227:Knowledge Representation and Reasoning, …

Knowledge Representation and Reasoning – …

Research resource identifier External links:

dkNET | Research Resource Identifier