SlideShare a Scribd company logo
The difference between a: Knowledgebase  and a Database M-C Jenkins ( http://www.scienceforseo.com )
Data is extracted and displayed This is the database model XKCD comic image
Knowledge is learning & answering This is the knowledgebase model XKCD comic image
'Data is not information;  information is not knowledge;  knowledge is not wisdom' I have the answer I've have the files Knowledge Data
What is Knowledge? Cognition: the psychological result of perception and learning and reasoning (WordNet) Relevant information that one is able to recall from memory; All cognitive expectancies that an individual or organization actor uses to interpret situations and to generate activities; A specific body of knowledge of any kind, on some subject or in some field; (Wiktionary)
What is Data? A collection of facts from which conclusions may be drawn; (WordNet) Data is a collection of facts, figures and statistics related to an object. Data can be processed to create useful information”. (Blurtit) “ Data is information that has been translated into a form that is more convenient to move or process.” (Techtarget)
What is a Knowledgebase? “ A knowledge base is a special kind of database for knowledge management. It provides the means for the computerized collection, organization, and retrieval of knowledge”. (wiki) “ A knowledge base attempts to capture in abstract (machine interpretable) form a useful representation of a physical or virtual world.” (expertise2go) “ Captures human knowledge and places it into a computer system where it is used to solve complex problems normally requiring a high level of human expertise”. (Wiley)
Knowledge engineering is: “ Knowledge engineering. The process of codifying an expert's knowledge in a form that can be accessed through an expert system”. (expertise2go) “ knowledge engineering: The discipline concerned with the application of computer systems to problems of human endeavour such as thinking, learning, problem solving, decision making, and knowledge transfer”. (btb.gc.ca)
So... Data are raw facts.  Information is data with context and perspective.  Knowledge is information with guidance for action based upon insight and experience.  (University of Melbourne)
What is a Database? “ An organized body of related information” (WordNet) “ A database is a structured collection of records or data” (Wikipedia) “ A collection of information organized in such a way that a computer program can quickly select desired pieces of data. You can think of a database as an electronic filing system.” (webopedia)
What is a Knowledgebase again? “ Machine-readable knowledge bases store knowledge in a computer-readable form, usually for the purpose of having automated deductive reasoning applied to them” (Wikipedia) “ A knowledge base is not a static collection of information, but a dynamic resource that may itself have the capacity to learn, as part of an artificial intelligence expert system” (Techtarget) It is an “expert system”, it uses artificial intelligence as well as data stored inside it to give answers and not simply a list of data resources. (Me)
So... Knowledge can be used to change the intelligence agent's status because of the learning process involved, but data cannot. Data-based systems are only process data and don't output information. "The LHC indeed will produce oceans and oceans of data, but the amount of knowledge will be much smaller." ( Cognections )
Knowledgebase challenges... Knowledge is dynamic. It changes all the time. It’s value and quality change all the time. The sources of input information is gathered from multiple sources. These sources change all the time. The knowledge base changes all the time because the new knowledge changes it. This information or data requires different storage and processing solutions.
And so... Things are not known by one single person or even one single group, it is cumulative. We need to access far more sources of information than for database systems. Knowledgebases are much smarter than databases because they process data and use expert knowledge to give answers, recommendations, and expert advice.
AT&T explain the difference... "Apparatus and methods for integrating a knowledge base management system with a data base system. The knowledge base management system employs compositional descriptions which describe information in terms of concepts. A translation component of the apparatus translates compositional descriptions into data base queries, so that information matching a compositional description may be retrieved from the data base. The translation component further permits display of the retrieved data in terms of the compositional description. The returned information can be automatically integrated into the knowledge base, either item by item or on the basis of the compositional description which was used to return the information." Patent assignee AT&T
WolframAlpha say... “ Knowledge bases are composed of a complex web of bits of knowledge that are all linked together and apart (as in explicitly not linked). The fact the WA will not only process your query but also do the mathematical calculation for you, present you with equations, compute things for you and much more shows that it does indeed deal with knowledge and not data. There is no list of resources, there is an answer. This answer will be in the form of information for you (statistics, graphs etc...) and this is extracted from knowledge. Experience that the system has with with world knowledge.”
Google... It has a large database composed of indexed resources and containing lots of information about those. It is issued with a query and presents a list of relevant resources. It gives you data. See: The Anatomy of a Large-Scale Hypertextual Web Search Engine
Missions... "Google's mission is to organize the world's information and make it universally accessible and useful."  "Wolfram|Alpha's long-term goal is to make all systematic knowledge immediately computable and accessible to everyone. We aim to collect and curate all objective data; implement every known model, method, and algorithm; and make it possible to compute whatever can be computed about anything. Our goal is to build on the achievements of science and other systematizations of knowledge to provide a single source that can be relied on by everyone for definitive answers to factual queries."
So now you can see... A database system is different to a knowledgebase system. A KB system is smarter. Google (although they no doubt run KB's for other things) does not give an answer, it gives resources (data). Wolfram gives answers, and has a knowledgebase, which makes it a knowledge engine
These engines are different beasts: Google is a search engine WolframAlpha is a knowledge engine
Resources Stanford's Protege Knowledgebase tool Build a knowledge base with OWL Ontologies and Knowledge Bases (Nicola Guarino) “Real Time Information is Just Data, Knowledge Comes Later”

More Related Content

What's hot

Graphs in Retail: Know Your Customers and Make Your Recommendations Engine Learn
Graphs in Retail: Know Your Customers and Make Your Recommendations Engine LearnGraphs in Retail: Know Your Customers and Make Your Recommendations Engine Learn
Graphs in Retail: Know Your Customers and Make Your Recommendations Engine Learn
Neo4j
 
Data mining , Knowledge Discovery Process, Classification
Data mining , Knowledge Discovery Process, ClassificationData mining , Knowledge Discovery Process, Classification
Data mining , Knowledge Discovery Process, Classification
Dr. Abdul Ahad Abro
 
Automated Machine Learning
Automated Machine LearningAutomated Machine Learning
Automated Machine Learning
Yuriy Guts
 
Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...
Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...
Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...
Neo4j
 
Data science
Data scienceData science
Data science
Purna Chander
 
Serverless Kafka and Spark in a Multi-Cloud Lakehouse Architecture
Serverless Kafka and Spark in a Multi-Cloud Lakehouse ArchitectureServerless Kafka and Spark in a Multi-Cloud Lakehouse Architecture
Serverless Kafka and Spark in a Multi-Cloud Lakehouse Architecture
Kai Wähner
 
البيانات المفتوحة المترابطة
البيانات المفتوحة المترابطة البيانات المفتوحة المترابطة
البيانات المفتوحة المترابطة
AIMS (Agricultural Information Management Standards)
 
Fine tune and deploy Hugging Face NLP models
Fine tune and deploy Hugging Face NLP modelsFine tune and deploy Hugging Face NLP models
Fine tune and deploy Hugging Face NLP models
OVHcloud
 
Generative AI Masterclass - Model Risk Management.pptx
Generative AI Masterclass - Model Risk Management.pptxGenerative AI Masterclass - Model Risk Management.pptx
Generative AI Masterclass - Model Risk Management.pptx
Sri Ambati
 
Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020
Enterprise Knowledge
 
Data Mining
Data MiningData Mining
Data Mining
ksanthosh
 
Lecture - Data Mining
Lecture - Data MiningLecture - Data Mining
Anomaly detection
Anomaly detectionAnomaly detection
Anomaly detection
QuantUniversity
 
Regulating Generative AI - LLMOps pipelines with Transparency
Regulating Generative AI - LLMOps pipelines with TransparencyRegulating Generative AI - LLMOps pipelines with Transparency
Regulating Generative AI - LLMOps pipelines with Transparency
Debmalya Biswas
 
Scikit Learn intro
Scikit Learn introScikit Learn intro
Scikit Learn intro
9xdot
 
Machine Learning & Amazon SageMaker
Machine Learning & Amazon SageMakerMachine Learning & Amazon SageMaker
Machine Learning & Amazon SageMaker
Amazon Web Services
 
From Data Science to MLOps
From Data Science to MLOpsFrom Data Science to MLOps
From Data Science to MLOps
Carl W. Handlin
 
Big data Presentation
Big data PresentationBig data Presentation
Big data Presentation
Aswadmehar
 
AWS_Meetup_BLR_July_22_Social.pdf
AWS_Meetup_BLR_July_22_Social.pdfAWS_Meetup_BLR_July_22_Social.pdf
AWS_Meetup_BLR_July_22_Social.pdf
Ayyanar Jeyakrishnan
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
Edureka!
 

What's hot (20)

Graphs in Retail: Know Your Customers and Make Your Recommendations Engine Learn
Graphs in Retail: Know Your Customers and Make Your Recommendations Engine LearnGraphs in Retail: Know Your Customers and Make Your Recommendations Engine Learn
Graphs in Retail: Know Your Customers and Make Your Recommendations Engine Learn
 
Data mining , Knowledge Discovery Process, Classification
Data mining , Knowledge Discovery Process, ClassificationData mining , Knowledge Discovery Process, Classification
Data mining , Knowledge Discovery Process, Classification
 
Automated Machine Learning
Automated Machine LearningAutomated Machine Learning
Automated Machine Learning
 
Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...
Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...
Volvo Cars - Retrieving Safety Insights using Graphs (GraphSummit Stockholm 2...
 
Data science
Data scienceData science
Data science
 
Serverless Kafka and Spark in a Multi-Cloud Lakehouse Architecture
Serverless Kafka and Spark in a Multi-Cloud Lakehouse ArchitectureServerless Kafka and Spark in a Multi-Cloud Lakehouse Architecture
Serverless Kafka and Spark in a Multi-Cloud Lakehouse Architecture
 
البيانات المفتوحة المترابطة
البيانات المفتوحة المترابطة البيانات المفتوحة المترابطة
البيانات المفتوحة المترابطة
 
Fine tune and deploy Hugging Face NLP models
Fine tune and deploy Hugging Face NLP modelsFine tune and deploy Hugging Face NLP models
Fine tune and deploy Hugging Face NLP models
 
Generative AI Masterclass - Model Risk Management.pptx
Generative AI Masterclass - Model Risk Management.pptxGenerative AI Masterclass - Model Risk Management.pptx
Generative AI Masterclass - Model Risk Management.pptx
 
Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020Introduction to Knowledge Graphs: Data Summit 2020
Introduction to Knowledge Graphs: Data Summit 2020
 
Data Mining
Data MiningData Mining
Data Mining
 
Lecture - Data Mining
Lecture - Data MiningLecture - Data Mining
Lecture - Data Mining
 
Anomaly detection
Anomaly detectionAnomaly detection
Anomaly detection
 
Regulating Generative AI - LLMOps pipelines with Transparency
Regulating Generative AI - LLMOps pipelines with TransparencyRegulating Generative AI - LLMOps pipelines with Transparency
Regulating Generative AI - LLMOps pipelines with Transparency
 
Scikit Learn intro
Scikit Learn introScikit Learn intro
Scikit Learn intro
 
Machine Learning & Amazon SageMaker
Machine Learning & Amazon SageMakerMachine Learning & Amazon SageMaker
Machine Learning & Amazon SageMaker
 
From Data Science to MLOps
From Data Science to MLOpsFrom Data Science to MLOps
From Data Science to MLOps
 
Big data Presentation
Big data PresentationBig data Presentation
Big data Presentation
 
AWS_Meetup_BLR_July_22_Social.pdf
AWS_Meetup_BLR_July_22_Social.pdfAWS_Meetup_BLR_July_22_Social.pdf
AWS_Meetup_BLR_July_22_Social.pdf
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
 

Similar to Knowledgebase vs Database

Week-1-Introduction to Data Mining.pptx
Week-1-Introduction to Data Mining.pptxWeek-1-Introduction to Data Mining.pptx
Week-1-Introduction to Data Mining.pptx
Take1As
 
Database Essay
Database EssayDatabase Essay
Data Structure and Types
Data Structure and TypesData Structure and Types
Data Structure and Types
Anjani Phuyal
 
Datamining
DataminingDatamining
Datamining
Debashis Pradhan
 
BIAM 410 Final Paper - Beyond the Buzzwords: Big Data, Machine Learning, What...
BIAM 410 Final Paper - Beyond the Buzzwords: Big Data, Machine Learning, What...BIAM 410 Final Paper - Beyond the Buzzwords: Big Data, Machine Learning, What...
BIAM 410 Final Paper - Beyond the Buzzwords: Big Data, Machine Learning, What...
Thomas Rones
 
Human Activities as Linked Data
Human Activities as Linked DataHuman Activities as Linked Data
Human Activities as Linked Data
Paolo Pareti
 
eScience: A Transformed Scientific Method
eScience: A Transformed Scientific MethodeScience: A Transformed Scientific Method
eScience: A Transformed Scientific Method
Duncan Hull
 
Introduction to Data and Computation: Essential capabilities for everyone in ...
Introduction to Data and Computation: Essential capabilities for everyone in ...Introduction to Data and Computation: Essential capabilities for everyone in ...
Introduction to Data and Computation: Essential capabilities for everyone in ...
Kim Flintoff
 
Comparison of Semantic and Syntactic Information Retrieval System on the basi...
Comparison of Semantic and Syntactic Information Retrieval System on the basi...Comparison of Semantic and Syntactic Information Retrieval System on the basi...
Comparison of Semantic and Syntactic Information Retrieval System on the basi...
Waqas Tariq
 
Coping with Data Variety in the Big Data Era: The Semantic Computing Approach
Coping with Data Variety in the Big Data Era: The Semantic Computing ApproachCoping with Data Variety in the Big Data Era: The Semantic Computing Approach
Coping with Data Variety in the Big Data Era: The Semantic Computing Approach
Andre Freitas
 
BrightTALK - Semantic AI
BrightTALK - Semantic AI BrightTALK - Semantic AI
BrightTALK - Semantic AI
Semantic Web Company
 
Python's Role in the Future of Data Analysis
Python's Role in the Future of Data AnalysisPython's Role in the Future of Data Analysis
Python's Role in the Future of Data Analysis
Peter Wang
 
Semantic technologies for the Internet of Things
Semantic technologies for the Internet of Things Semantic technologies for the Internet of Things
Semantic technologies for the Internet of Things
PayamBarnaghi
 
Riding The Semantic Wave
Riding The Semantic WaveRiding The Semantic Wave
Riding The Semantic Wave
Kaniska Mandal
 
TCS_DATA_ANALYSIS_REPORT_ADITYA
TCS_DATA_ANALYSIS_REPORT_ADITYATCS_DATA_ANALYSIS_REPORT_ADITYA
TCS_DATA_ANALYSIS_REPORT_ADITYA
Aditya Srinivasan
 
Database Essay
Database EssayDatabase Essay
Unit 1 Introduction to Data Analytics .pptx
Unit 1 Introduction to Data Analytics .pptxUnit 1 Introduction to Data Analytics .pptx
Unit 1 Introduction to Data Analytics .pptx
vipulkondekar
 
ML crash course
ML crash courseML crash course
ML crash course
mikaelhuss
 
Data mining
Data miningData mining
Data mining
Ritesh Tiwari
 
Essay Database
Essay DatabaseEssay Database

Similar to Knowledgebase vs Database (20)

Week-1-Introduction to Data Mining.pptx
Week-1-Introduction to Data Mining.pptxWeek-1-Introduction to Data Mining.pptx
Week-1-Introduction to Data Mining.pptx
 
Database Essay
Database EssayDatabase Essay
Database Essay
 
Data Structure and Types
Data Structure and TypesData Structure and Types
Data Structure and Types
 
Datamining
DataminingDatamining
Datamining
 
BIAM 410 Final Paper - Beyond the Buzzwords: Big Data, Machine Learning, What...
BIAM 410 Final Paper - Beyond the Buzzwords: Big Data, Machine Learning, What...BIAM 410 Final Paper - Beyond the Buzzwords: Big Data, Machine Learning, What...
BIAM 410 Final Paper - Beyond the Buzzwords: Big Data, Machine Learning, What...
 
Human Activities as Linked Data
Human Activities as Linked DataHuman Activities as Linked Data
Human Activities as Linked Data
 
eScience: A Transformed Scientific Method
eScience: A Transformed Scientific MethodeScience: A Transformed Scientific Method
eScience: A Transformed Scientific Method
 
Introduction to Data and Computation: Essential capabilities for everyone in ...
Introduction to Data and Computation: Essential capabilities for everyone in ...Introduction to Data and Computation: Essential capabilities for everyone in ...
Introduction to Data and Computation: Essential capabilities for everyone in ...
 
Comparison of Semantic and Syntactic Information Retrieval System on the basi...
Comparison of Semantic and Syntactic Information Retrieval System on the basi...Comparison of Semantic and Syntactic Information Retrieval System on the basi...
Comparison of Semantic and Syntactic Information Retrieval System on the basi...
 
Coping with Data Variety in the Big Data Era: The Semantic Computing Approach
Coping with Data Variety in the Big Data Era: The Semantic Computing ApproachCoping with Data Variety in the Big Data Era: The Semantic Computing Approach
Coping with Data Variety in the Big Data Era: The Semantic Computing Approach
 
BrightTALK - Semantic AI
BrightTALK - Semantic AI BrightTALK - Semantic AI
BrightTALK - Semantic AI
 
Python's Role in the Future of Data Analysis
Python's Role in the Future of Data AnalysisPython's Role in the Future of Data Analysis
Python's Role in the Future of Data Analysis
 
Semantic technologies for the Internet of Things
Semantic technologies for the Internet of Things Semantic technologies for the Internet of Things
Semantic technologies for the Internet of Things
 
Riding The Semantic Wave
Riding The Semantic WaveRiding The Semantic Wave
Riding The Semantic Wave
 
TCS_DATA_ANALYSIS_REPORT_ADITYA
TCS_DATA_ANALYSIS_REPORT_ADITYATCS_DATA_ANALYSIS_REPORT_ADITYA
TCS_DATA_ANALYSIS_REPORT_ADITYA
 
Database Essay
Database EssayDatabase Essay
Database Essay
 
Unit 1 Introduction to Data Analytics .pptx
Unit 1 Introduction to Data Analytics .pptxUnit 1 Introduction to Data Analytics .pptx
Unit 1 Introduction to Data Analytics .pptx
 
ML crash course
ML crash courseML crash course
ML crash course
 
Data mining
Data miningData mining
Data mining
 
Essay Database
Essay DatabaseEssay Database
Essay Database
 

More from CJ Jenkins

I am an experience designer
I am an experience designer I am an experience designer
I am an experience designer
CJ Jenkins
 
How Sentiment Analysis works
How Sentiment Analysis worksHow Sentiment Analysis works
How Sentiment Analysis works
CJ Jenkins
 
Using construction grammar in conversational systems
Using construction grammar in conversational systemsUsing construction grammar in conversational systems
Using construction grammar in conversational systems
CJ Jenkins
 
Building a semantic website
Building a semantic websiteBuilding a semantic website
Building a semantic website
CJ Jenkins
 
Search Engine Spiders
Search Engine SpidersSearch Engine Spiders
Search Engine Spiders
CJ Jenkins
 
Twitter for business
Twitter for businessTwitter for business
Twitter for business
CJ Jenkins
 
The search engine index
The search engine indexThe search engine index
The search engine index
CJ Jenkins
 

More from CJ Jenkins (7)

I am an experience designer
I am an experience designer I am an experience designer
I am an experience designer
 
How Sentiment Analysis works
How Sentiment Analysis worksHow Sentiment Analysis works
How Sentiment Analysis works
 
Using construction grammar in conversational systems
Using construction grammar in conversational systemsUsing construction grammar in conversational systems
Using construction grammar in conversational systems
 
Building a semantic website
Building a semantic websiteBuilding a semantic website
Building a semantic website
 
Search Engine Spiders
Search Engine SpidersSearch Engine Spiders
Search Engine Spiders
 
Twitter for business
Twitter for businessTwitter for business
Twitter for business
 
The search engine index
The search engine indexThe search engine index
The search engine index
 

Recently uploaded

TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
TrustArc
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Pixlogix Infotech
 
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation TechniquesWeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
Postman
 
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Brandon Minnick, MBA
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
Daiki Mogmet Ito
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Speck&Tech
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
Zilliz
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Jeffrey Haguewood
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
akankshawande
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Tomaz Bratanic
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Alpen-Adria-Universität
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
Jason Packer
 
5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides
DanBrown980551
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
panagenda
 
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying AheadDigital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Wask
 
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and MilvusGenerating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
Zilliz
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Matthew Sinclair
 

Recently uploaded (20)

TrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc Webinar - 2024 Global Privacy Survey
TrustArc Webinar - 2024 Global Privacy Survey
 
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERPBest 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
 
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation TechniquesWeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
 
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
 
How to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For FlutterHow to use Firebase Data Connect For Flutter
How to use Firebase Data Connect For Flutter
 
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
 
Fueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte WebinarFueling AI with Great Data with Airbyte Webinar
Fueling AI with Great Data with Airbyte Webinar
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing InstancesEnergy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
 
5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides
 
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAUHCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
 
Digital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying AheadDigital Marketing Trends in 2024 | Guide for Staying Ahead
Digital Marketing Trends in 2024 | Guide for Staying Ahead
 
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and MilvusGenerating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
 

Knowledgebase vs Database

  • 1. The difference between a: Knowledgebase and a Database M-C Jenkins ( http://www.scienceforseo.com )
  • 2. Data is extracted and displayed This is the database model XKCD comic image
  • 3. Knowledge is learning & answering This is the knowledgebase model XKCD comic image
  • 4. 'Data is not information; information is not knowledge; knowledge is not wisdom' I have the answer I've have the files Knowledge Data
  • 5. What is Knowledge? Cognition: the psychological result of perception and learning and reasoning (WordNet) Relevant information that one is able to recall from memory; All cognitive expectancies that an individual or organization actor uses to interpret situations and to generate activities; A specific body of knowledge of any kind, on some subject or in some field; (Wiktionary)
  • 6. What is Data? A collection of facts from which conclusions may be drawn; (WordNet) Data is a collection of facts, figures and statistics related to an object. Data can be processed to create useful information”. (Blurtit) “ Data is information that has been translated into a form that is more convenient to move or process.” (Techtarget)
  • 7. What is a Knowledgebase? “ A knowledge base is a special kind of database for knowledge management. It provides the means for the computerized collection, organization, and retrieval of knowledge”. (wiki) “ A knowledge base attempts to capture in abstract (machine interpretable) form a useful representation of a physical or virtual world.” (expertise2go) “ Captures human knowledge and places it into a computer system where it is used to solve complex problems normally requiring a high level of human expertise”. (Wiley)
  • 8. Knowledge engineering is: “ Knowledge engineering. The process of codifying an expert's knowledge in a form that can be accessed through an expert system”. (expertise2go) “ knowledge engineering: The discipline concerned with the application of computer systems to problems of human endeavour such as thinking, learning, problem solving, decision making, and knowledge transfer”. (btb.gc.ca)
  • 9. So... Data are raw facts. Information is data with context and perspective. Knowledge is information with guidance for action based upon insight and experience. (University of Melbourne)
  • 10. What is a Database? “ An organized body of related information” (WordNet) “ A database is a structured collection of records or data” (Wikipedia) “ A collection of information organized in such a way that a computer program can quickly select desired pieces of data. You can think of a database as an electronic filing system.” (webopedia)
  • 11. What is a Knowledgebase again? “ Machine-readable knowledge bases store knowledge in a computer-readable form, usually for the purpose of having automated deductive reasoning applied to them” (Wikipedia) “ A knowledge base is not a static collection of information, but a dynamic resource that may itself have the capacity to learn, as part of an artificial intelligence expert system” (Techtarget) It is an “expert system”, it uses artificial intelligence as well as data stored inside it to give answers and not simply a list of data resources. (Me)
  • 12. So... Knowledge can be used to change the intelligence agent's status because of the learning process involved, but data cannot. Data-based systems are only process data and don't output information. "The LHC indeed will produce oceans and oceans of data, but the amount of knowledge will be much smaller." ( Cognections )
  • 13. Knowledgebase challenges... Knowledge is dynamic. It changes all the time. It’s value and quality change all the time. The sources of input information is gathered from multiple sources. These sources change all the time. The knowledge base changes all the time because the new knowledge changes it. This information or data requires different storage and processing solutions.
  • 14. And so... Things are not known by one single person or even one single group, it is cumulative. We need to access far more sources of information than for database systems. Knowledgebases are much smarter than databases because they process data and use expert knowledge to give answers, recommendations, and expert advice.
  • 15. AT&T explain the difference... "Apparatus and methods for integrating a knowledge base management system with a data base system. The knowledge base management system employs compositional descriptions which describe information in terms of concepts. A translation component of the apparatus translates compositional descriptions into data base queries, so that information matching a compositional description may be retrieved from the data base. The translation component further permits display of the retrieved data in terms of the compositional description. The returned information can be automatically integrated into the knowledge base, either item by item or on the basis of the compositional description which was used to return the information." Patent assignee AT&T
  • 16. WolframAlpha say... “ Knowledge bases are composed of a complex web of bits of knowledge that are all linked together and apart (as in explicitly not linked). The fact the WA will not only process your query but also do the mathematical calculation for you, present you with equations, compute things for you and much more shows that it does indeed deal with knowledge and not data. There is no list of resources, there is an answer. This answer will be in the form of information for you (statistics, graphs etc...) and this is extracted from knowledge. Experience that the system has with with world knowledge.”
  • 17. Google... It has a large database composed of indexed resources and containing lots of information about those. It is issued with a query and presents a list of relevant resources. It gives you data. See: The Anatomy of a Large-Scale Hypertextual Web Search Engine
  • 18. Missions... "Google's mission is to organize the world's information and make it universally accessible and useful." "Wolfram|Alpha's long-term goal is to make all systematic knowledge immediately computable and accessible to everyone. We aim to collect and curate all objective data; implement every known model, method, and algorithm; and make it possible to compute whatever can be computed about anything. Our goal is to build on the achievements of science and other systematizations of knowledge to provide a single source that can be relied on by everyone for definitive answers to factual queries."
  • 19. So now you can see... A database system is different to a knowledgebase system. A KB system is smarter. Google (although they no doubt run KB's for other things) does not give an answer, it gives resources (data). Wolfram gives answers, and has a knowledgebase, which makes it a knowledge engine
  • 20. These engines are different beasts: Google is a search engine WolframAlpha is a knowledge engine
  • 21. Resources Stanford's Protege Knowledgebase tool Build a knowledge base with OWL Ontologies and Knowledge Bases (Nicola Guarino) “Real Time Information is Just Data, Knowledge Comes Later”