What is ExpDB
ExpDB (a.k.a. Experience DB) is a software system which consists in a database of experiences, different situations in general, that are thought at a higher abstract level, the purpose being to manage diverse knowledge, in a controlled and organized manner. It allows persisting knowledge by categorizing it and by filtering it, based on its relevance. Thus, ExpDB builds a database meant to include only the most relevant information.
The stored knowledge can be modified, adapted to new situations; it can be used as a set of past experiences that can be used for providing solutions to new encountered situations, by relating the new experiences to past ones, which exist in the database.
In order to achieve this, ExpDB uses Case-Based Reasoning (CBR) engine. CBR can provide solutions for new situations by comparing them with previous similar encountered situations. By doing so, CBR may perform as a problem resolving method.
To contribute to very good representation of knowledge, ExpDB uses ontology as a data model. Ontology is used to specify knowledge domain, representing a well defined vocabulary which describes objects and relations between them. A grammar uses the terms from the vocabulary, being capable to express meanings, for the specified domain.
What ExpDB does is to relate a certain domain of knowledge (specified using ontology) with the CBR core. This way, the manner of specifying and defining knowledge becomes very flexible.
Using the ontology concept, ExpDB has the ability to perform reasoning over the knowledge, being able to infer new knowledge, based on the one that it already has.
Features
The features that ExpDB offers are the following:
- Store information in structured manner;
- Compare pieces of similar information;
- Retrieving the past experience which is the most similar with a new experience;
- Manipulate already stored experiences in order to allow knowledge to adapt;
- Specify the way by which similar experiences are compared;
- Apply a CBR cycle that allows to process information based on Case-Based Reasoning principles (the 4-R).
Architecture
Information can be persisted in ExpDB in two ways:
- using a XML file system;
- a relational database.
or
ExpDB uses as CBR core the jColibri engine. Similar experiences (which belong to the same domain) are called cases in CBR terminology. Cases are grouped by using a so called case structure. The case structure, like cases as well, has an XML format by which it specifies how information is structured. All the cases that have the same structure, form a case type.
Each case type has one or more similarity functions associated. They are used in order to describe the way a new case is compared with existing cases and to establish which the most similar cases are.
As presented before, ExpDB can use information described with ontology. By the aid of the OWL (Web Ontology Language) and using the powerful semantic web framework called JENA, information described using ontology can contribute to create case structures. Ontology classes and individual attributes are taken and translated in a case structure.
In conclusion, ExpDB is a flexible and complex solution for Knowledge Management that originally integrates the CBR paradigm with the Ontology paradigm. This way ExpDB contributes at a detailed description of different domains.
To have a look at ExpDB, you can watch online two tutorials about ExpDB:
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Hi Ciprian, that’a an interesting presentation.
October 17, 2007 at 2:27 pmI have some questions about it:
Why did you write it?
Who has developed the ExpDB and why?
Can you give one example where ExpDB can be used?
Hi Bogdana, thank you for your opinion. I’ll now answer to your questions.
I wrote about ExpDB because in my opinion it is an interesting subject. ExpDB is a research project, developed mainly for the KoBaS project, by myself and other colleagues here at Wittmann&Partner. KoBaS project aims to enable the quick customization of solutions in order to provide an advanced task and process planning and machine configuration, maintenance, training and management support (you can read more about KoBaS here: http://www.kobasproject.com).
In fact, I wasn’t involved in the project from the beginning, but when I’ve got the opportunity to work on developing ExpDB, I’ve quickly started to like it.
Why? Because (simply put) it was and still is very interesting to me to be able to create a database with information which tends to be the most representative (by providing similarity functions which enable the adaptation feature).
I’d also like to tell you that (at least in my opinion) ExpDB can be further developed, by being better organized and by providing more features for example. The project is mainly based on jColibri (as I’m sure you’ve read in my article) which recently reached version 2 (ExpDB uses v. 1.1). jColibri2 is better structured and gives a higher degree of importance to textual CBR, text clustering, text retrieval. So, using these new facilities, ExpDB can offer better document management. But this is just an example. I believe that other things can also be provided.
Were can ExpDB be used? Well I could say that in every software application which can be approached in a Case-Based Reasoning manner. If you store information regarding something why not to be able to filter that information aiming to keep only the most relevant one?
An example which comes in my mind now is something like this: a hospital were medics treat patients and they deal with a lot of different cases. Of course probably a lot of them are standard and diagnosing them is pretty straight forward. But… for those few cases which require a more particular approach, which is difficult to find latter when a similar case appears, wouldn’t be better to memorize that treatment? When a similar case emerges the doctor will know what to do. And for that situation maybe latter on, a better solution is found so we don’t really need the old one any longer. But how do you know when a case is similar to another? It would be nice that a computer would be able to suggest to the doctor a way to approach his case…
I hope that my example is good enough, but mainly in such situations ExpDB can be good add.
And finally, let me say one more thing: ExpDB, jColibri are designed to be abstract. So, at least theoretically, any problem that has a CBR approach can use jColibri and ExpDB in particular. ExpDB is not better than jColibri, it doesn’t try to replace it, it just uses jColibri in a more practical manner, by wrapping it in order to create a CBR engine which is ready to use.
I hope I’ve managed to answer to your questions. If you have further questions, suggestions, critics, please leave them here and I’ll try to answer to them the best way I can.
October 18, 2007 at 1:15 pmHi, this article is interesting. I watched online demos and I think ExPdb is a useful tool about cbr working. I like test expdb because I ´m work with jcolibri too. So I have a question: where i can get this tool?
April 3, 2008 at 3:54 amgreat!
June 30, 2010 at 9:30 am