First of all a database is a concrete technical solution to store and organize data - it is mostly also limited on just these functionality. In contrast to that, a knowledge bas is a technology to store "knowledge". For this purpose it can use a database, but it is not limited on these functions. A knowledge base can use many databases or can combine or enrich it with information from public data sources. So, a knowledge base is more or less big and a heterogeneous source for many kinds of information.

@Dirk....does it mean that database can be converted to knowledge base by adding some additional aspects!!

It is not easy to answer your question. In general, yes, a database can be converted to a knowledgebase. But mostly databases are used FOR a knowledgebase too.

From my perspective the terms database and knowledgebase are mostly used synonym. The major difference is that a knowledgebase can (but must not) be more - e.g. it can include also multimedia files, whereas databases are limited in that way - but in the background a knowledgebase can use normal databases too. So I prefer the picture that a knowledge base is more an add-on for a default database, because they provide more or less the same data storing functionality, as well as additional features can be added, such as a multimedia inclusion or references to foreign data sources.

Thanks Dirk

A knowledge base is a particular kind of database. From a knowledge base we require that it stores and evaluates information in a similar way a human would perceive a domain, however normally bound to binary logic. That means that "tables" correspond to classes which can be identified with categories in the user domain and relationships that are related as a user would perceive it. More technically, we require class and relationship subsumption (a "dog" is a "mammal", "reading a book" is "using a book"). Currently, RDFS and OWL provide the most popular data models for knowledge bases, but using them does not prevent someone to represent knowledge in a wrong way. The test (with the user) is the "ontological commitment" of the classes and properties used.

Thanks Rahmad....

Data is a collection of facts, figures and statistics related to an object. Data can be processed to create useful information”. 

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

I think that the answer depends on the context of the question. Because these terms seem to mean different things in different contexts.

Someone would say that the difference is that a DB stores data, while a KB stores knowledge. And, in this way, the difference between DB and KB would be reduced to a difference between data and knowledge. And this difference is always debatable.

In other contexts, comparing DB and KD, is like comparing oranges and apples.

Some people understand the KB as something abstract; as an aggregate that can include, for example, an ontology, a collection of facts, a set of rules, etc. And, in this point of view, a KB can be stored in a DB. For example, according to this sense, someone could represent an ontology, facts as triples in an Oracle DB.

I have just found an old (but interesting) paper about that question.

Knowledge Bases vs Databases. Michael L. Brodie, John Mylopoulos. On Knowledge Base Management Systems Topics in Information Systems 1986, pp 83-86

http://link.springer.com/chapter/10.1007/978-1-4612-4980-1_9#page-1

We could say simply that knowledge base contains statements and sentences, I.e facts. While database is made up of tables containing data

A database is the data managed by one or more database engines that has a related schema or common set of applications using it.

A knowledge base (KB) is a technology used to store complex structured and unstructured information used by a computer system. The initial use of the term was in connection with expert systems which were the first knowledge-based systems

In fact we can say that : A knowledge base is a type of database, and this name is typically used with applications that involve some sort of AI functionality such as expert systems data stores or machine learning stores.

Simply the difference is that a DB stores data, while a KB stores knowledge.

Real-world is comprised of objects or entities and their relationships.

In the database, we only organize or represent those objects and their relationships through some shared information (attributes).

However, a knowledge is a next level in the data hierarchy, where we add some rules (or sometimes called as heuristics) to manipulate these objects and their relationship for reasoning. Logically, when we try to organize those rules/heuristics along with the data it becomes knowledge base. This is how I summarize the two terms.

Here is a link for  a very slide show explain the differences between knowledge base and data base 

http://www.slideshare.net/mcjenkins/knwoedgebase-vs-database

 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)

Ok ASAD

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. 

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

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

databases, include millions of pieces of information that, when inserted into a common frame, can be easily accessed by an employee or analyst and connections made between multiple bits of information. Databases are structured approbation to fixed requirements, an enable users to aperture the desired information quickly and efficiently.

Knowledge bases, are far more combination, and require far greater count capabilities, and basically represent the realization of artful cleverness. Whereas databases are strictly useful for accessing information on a desired topic.

Regards

KS Al-Niaeem

 Thanks Dr Khalidah for participation and for your valued comment .... I do agree with your opinion.

If we are talking about  differences between a DB (database) system and KB (knowledge base) systems, then we must consider the differences in implementation practices, the technologies used are much different based on the needs and applications of systems, though we can build a KB system not from but upon an existing database system, but that may not be a smart move. Like for KBS, we need to add an AI layer on top of our database layer (if we need facts from the Database). The new layer would contain a knowledge representation (KB) and then inference mechanism.

But, we must keep in mind, the core purposes of both systems are not related at all, the information stored and required operations, are totally different. They are not alternative solutions to a common problem as both has their own needs and applications.

Database System: We need to maintain a record of transactions, e.g Inventory systems, and library software, etc... An example technology used, for instance, is relational databases interpreted by some querying languages. The system behaves like an efficient store room.

Knowledge-based System: We often need to infer new knowledge in light of an authenticated knowledge base and current facts, or we need to give an expert opinion/answer for a specific problem domain query. The knowledge often comes and represented in the form of rules, a pair of antecedent and consequent. The core technology basis the formal logic  e.g. First Order (Predicate) logic ... available tools are CLIPS, Prolog, MYCIN etc. The nature of information, its representation, and type of query is changed. The system behaves as an expert (Human) of one specifc domain.

Let me take a completely different position: Neither databases nor knowledge bases store knowledge. They only store information. Knowledge can so far only be in a human head, because only humans so far can relate the identifiers in an information system with the world of reference, at least as long as we do not talk about mathematical constructs as subjects. I.e. they are carriers of the interpretation functions between referents and referees. Any (plausible) information can "induce" knowledge in humans. The only difference a knowledge base makes, is that it aims at a structural and logical similarity of the information keeping with the human way to relate things with a persistent identity with explicit propositions, possible also rules, under the constraint of being formally logically consistent and not in contradiction with empirical reality within a useful precision.

This makes knowledge bases particularly effective for integrating heterogeneous information.

I'd regard it as decoration to name a query "what do you know", since the machine will not know the author anyhow, not more than any database. The fact that databases have in general partial information about the world of reference is also not peculiar to knowledge bases.

Open World Assumption (OWA) vs Closed World Assumption (CWA).

When asking a relational database if "Is there a tuple x such that Q(x)?", the system can only answer "yes" or "no". In a relational database, if a tuple does not exist as an instance of a relation R, then it exists as an instance in the complement ⌐R

The opposite is observed in Open World Assumption (OWA). In a KB, which is intrinsically incomplete in portraying the world, by asking whether "Is there an employee x such that P(x)?" the answers can be "yes", "no" or "don't know". The absence of such information in the KB means that this knowledge was not made explicit but does not make it false.

Brodie, M.L., Mylopoulos, J. (1986). Knowledge Bases vs Databases. In: Brodie, M.L., Mylopoulos, J. (eds) On Knowledge Base Management Systems. Topics in Information Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4980-1_9