Mapping Knowledge Into A Database Model
Emile Segev, Université du Québec, Canada
ABSTRACT:
In a highly competitive business environment, organizations are looking for improved tools which could provide them a greater opportunity to succeed and to create a strategic advantage in their market. Their primary concern therefore is continuous, effective and secure access to their accumulated knowledge. Knowledge Management tools and methods are emerging, primarily for the use of big organizations, but more and more small and medium enterprise (SME) are interested in adopting them. Knowledge is a step ahead of Information, and deals with the capturing and the gathering of Information along its steps and rules related to a Working Process, in order to perform the latter at an optimal level. The dilemma is, that in order to access knowledge, one must store it, in the most effective and efficient way. This paper offers various definitions of Knowledge by differing authors, examines the general difficulties and the problems of Capturing and Storing Knowledge, and presents our particular attempt to map and store it into a database structure. It relates to the author’s current ongoing project, which objective is to convert a plain text knowledge system, into a common database system, for the use of a Property Management enterprise. The motivation behind our attempt is, once knowledge is stored in such a structure, we believe it will attain our dual objective: an effective and efficient access to knowledge that is stored in a secure manner.
Keywords: Knowledge, Knowledge storage, Knowledge management, Database structure, DBMS
Importance Of Knowledge
We are in an era of Knowledge revolution, where knowledge occupies the center stage. Its continuous generation, sharing and implementation have become crucial for firms and countries. This revolution is supported by the revolution in information technologies (Pillania, 2008). The latter is to support existing KM efforts in its various activities and possibly, to suggest newer and more effective ways to deploy them. The relevance of KM is not argued by the academic or the practionners communities, nor is it a subject of demonstrations. In today’s highly competitive business environment, organizations are looking for KM tools, which could provide them the highest effectiveness, a greater opportunity to succeed and to create a strategic advantage in their market.
What Is Knowledge?
To make sure we are in the right direction and using a common vocabulary, let’s examine some of the definitions of Knowledge. In recent years, the term Knowledge Management has been used, to describe the efforts of organizations to capture, store, and deploy Knowledge (Preece et al, 2001). For some, Knowledge is a somewhat elusive concept; here is a pragmatic description of knowledge in organizations: Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms (Davenport and Prusak, 1998; 5). We usually distinguish 'knowledge' from 'information', and information from 'data', on the basis of value-adding processes which transform raw material (for example, transaction records) into communicable messages (such as documents) and then into knowledge and other higher-order concepts. These value-adding processes include in the first instance contextualization, categorization, calculation, conversion and condensation; and in the second, connection, comparison, and conversation. Other authors - notably Thomas Stewart - dismiss the notion of a data-to-wisdom hierarchy as bogus and unhelpful on the grounds that "one man's knowledge is another man's data".(Stewart 1997; 69)
Knowledge Management And Its Facets
Another theme discussed amongst the experts is the distinction between the explicit Knowledge and the tacit knowledge. Here are some insights. A more important distinction - which is fundamental to the concept of knowledge management - is that between 'explicit' and 'tacit' knowledge, explained by Ikujiro Nonaka. "Explicit knowledge is formal and systematic. For this reason it can be easily communicated and shared, in product specifications or a scientific formula or a computer program. Tacit knowledge is highly personal. It is hard to formalize and therefore difficult, if not impossible, to communicate." (Nonaka, 1991)
Most authors identify the different facets of KM as being one of Capturing, Organizing and Storing, while everyone clearly insists on the Sharing Aspect of KM. It is obviously the goal of any KM efforts.
Ramjani (Ramjani, 2000) identifies the following steps or stages in KM:
Ø Develop Knowledge (acquire, capture, create,,)
Ø Preserve Knowledge (store, securing,,)
Ø Update knowledge (evolving, improving,,)
Ø Transfer knowledge (communication, deploying,,)
Ø Transform knowledge (compiling, standardizing,,)
Ø Assess knowledge (appraising, evaluating,,)
Ø Apply knowledge (using, enacting,,)
The Case Of PMGT Inc.
In our attempt to map Knowledge into a Database Model, we used the knowledge
of an actual organization located in
From the beginning PMGT had to divide the entire process into sub-processes
which are outlined later on this article.
All are presently well documented in various computer files, mostly
Excel and plain text documents containing company’s procedures to
follow. This is the ‘’
In other words, Management did not have a method of ensuring accountability
for actions and decisions taken by employees, since the actual system could not provide the authors
and origin of the Knowledge, nor the subjects who enacted the actions and
decisions. At this point, the managers
wanted to improve and bring their actual KM system, to the Next level, as they called it. This is
when we stepped in, to use this opportunity as an experimental base for our
study. We knew from the beginning that
the resources of this small organization are not sufficient to maintain a very
sophisticated KM program such as LOOM.
PMGT Inc, has managed real
estate residential properties for more than 25 years. Along the years, it has
accumulated most valuable experience in the various processes involved in their
activities. The change and mobility of
the employees and the will to retain all
their experience in place, has motivated the company to invest in a Knowledge System where the
objective is to capture the knowledge and store it as quickly as possible, in
order to make it easily available to all employees. PMGT has established an edge over its
competitors in terms of effectiveness and it is now the time to build a more structured KM tool . Our goal is to bring forward the present
rudimentary system into an automated one
which could be accessible in effective
and secure manners. We must design and
develop a more structured system, which will be mainly stored and supported by
a Relational DBMS and later, if necessary, coupled with XML files. Our priority is the storage aspect of all the
actual knowledge, held in these documents.
Knowledge Storage
Most knowledge management activities are a combination of business processes and information technology (Bukowitz, W. and Williams, 1999). In our KM system we are indeed using Business Processes, or as we call them, working processes. We investigated the literature and found that several authors have mentioned DBMS as means of Knowledge storage. In terms of technology, most current knowledge management activities rely on database and internet systems: it is typically stored in databases either as simple tables or semi-structured text (for example, in Lotus Notes) (Preece et al, 2001). In order to retrieve Knowledge in the best and most secure way, we must capture it in a system which allows rapid selective queries in a controlled environment. Therefore a DBMS is a good effective tool. Knowledge is broken down into permanent atomic "facts" which can be stored in a standard relational database and processed very efficiently. It also provides for the efficient querying of a knowledge base, efficient inference of new knowledge and translation into and out of natural language. Queries can also be processed with full natural language explanations of where the answers came from (Tunstall-Pedoe, 2006).
How Is KM Stored?
Knowledge, in all of its forms, whether explicit or tacit, includes rules, steps, actions and so forth, must be stored in some manner.
Ø This order seems to be from the least to the most sophisticated tool.
Ø Plain or structured (ex groupware program) text format
Ø Hyperlink form using XML, used mainly within the Internet environment, XML is specialized to manipulate libraries. XML's purpose is to aid information systems in sharing structured data, especially via the Internet, (Bray et Al, 2006). The data is defined in a Hierarchal format, which enables, for example, a library, to input the reference data of all its the books. The user interface for entering the data is in a form of a Table. XML, the interface, will be a table, but the storage is Internet compatible using hyperlink, to access another structure, related to the present information linked..
Ø Database structures
Ø Sophisticated and costly KM representation systems such as Classic, Loom or G2, which are aimed for the larger scale organizations.
Ø Combination of the above.
Choice For KM Storage
From the start, we knew that it was an experimental project and as a SME, the option of the more sophisticated options, were discarded. There is little use of sophisticated knowledge representation systems such as Classic, Loom, or G2. Few organizations have a systematic process for capturing knowledge, as distinct from their conventional information-capture procedures (Preece et al 2001). Based on this premise, and based on the author’s experience, a lighter solution was wanted, an inner solution, a self sufficient one, so as not to depend on any outside resources, using tools, unfamiliar to the employees. We also decided that a solution based on XML platform was not necessary at the moment. We had some evidence that KM can be stored and managed by a DBMS. However, we did not exclude the possibility, that in the course of the project, we may have to combine our system to an XML solution and build a more intelligent, effective and efficient tools, embodying the security of the very confidentiality of the Knowledge, captured in the system. Hence our decision was to start with a simple prototype involving one Process only. We chose the most important one for PMGT that is the Application Rental Apartment, (codified ARA).
Methodology
Ø We have the list of all working processes, that is: P(A,1) to P(A,n)
Ø Our Methodology is cautious and will follow this procedure:
Ø Keep and Maintain the present system in use
Ø Develop P(A,1) to P(M,1)
Ø Test P(M,1) in an operational working environment
Ø Bring the necessary corrections and modifications and validate P(M,1)
Ø Replace P(A,1) by P(M,1)
Ø Iterate procedure to all remaining P(A, n)
Ø Once the cycle is finished, the new system would replace the existing one and would become the operational KM System in use by PMGT.
How Did We Proceed?
At first, we had to define what are the facts, steps, rules, actions, documented and undocumented information which were relevant to the Process in study. We had to gather all the tacit knowledge which is ‘’nowhere’’ seen i.e. it is everything that is said among all conversations of the employees, not only when officially working but also when they exchange impressions and experiences of work habits, according to context. For example, in the process that we are in the course of developing ARA, there are these facts which we captured from the employees, as being tacit knowledge, which is in many ways, intuitive. It is complex and multifaceted process as it may involve the engaging of various types of juridical procedures. The employee, in charge of this process says: “It may be a very short or a very long, time consuming and complicated process”, as we will see later.
Capturing And Retaining PMGT Knowledge
In this exercise, we must first ‘’extract ‘’ the tacit and non tacit knowledge from the individuals who retain it to be captured in a more structured manner. Focus would be on the employees who possess the most experience and who have been acting to perform the process on behalf of the organization. They often have intuitive knowledge based on their experience performing the same Process, under different conditions, situations and contexts. Their valuable experience must be expressed, captured, classified and stored, into our data structure model. We may, along the way, modify the Database structure in order to address tasks or relations, in the process, which are difficult or impossible to store in the current structure, and vice versa. We adapt the Process components to the DB structure, and we may at some situations adapt the structure by performing several alterations, in order to be able to integrate the components of the Process.
Implementing The KM System In A DB Structure
|
|
Figure 1: The Model Used To
Translate And Store The Mental Process ¨Extracted¨ From An Experienced Worker
Our structured system is based on
this model, whereas the Mental Process is translated into a structured form
which in turn, is converted into Steps Rules and Actions, as illustrated in the
above figure. This could be expressed as follows:
PM → PS: {Steps, (Rules),
Actions}
PM and PS, being, the Mental and Structured process
respectively.
PMi → PSi
: { Step(PMi) + (Rules (PMi))
+ Actions(PMi)}
Process i = (Step1 + Step2 +… Stepn )
Stepi = (Rule1
+ Rule2 + ………..Rulen )
+ (Action1 + Action2 +
…………..+ Actionn )
Hence,
Process i = (Stepi…….
Stepn ) + (Rulei ……..Rulen ) +
(Actioni …………..+ Actionn )
or
Processi = ∑ (Stepi to n, (Rulei to n ), Actioni to
n )
We will see later, that Rules are
optional, as we may have situations consisting of a sequence of Actions, with
no Rules attached.
The Data Base Content
The following DB model is a
simplified content for the application being studied in this project. First, we define the Processes involved in
the application, then we present in a more detailed manner one of the
Processes. Our hypothesis is: once the
system is validated throughout the said Process, it would most probably
function on the others. The only difference between the Processes is their respective
number of steps and their complexity, as expressed by the set of Rules
involved. For the purpose of this article we present only ARA- Step-5.
T_Process
|
Code-P |
Description |
|
ARA |
Application Rental Apartment |
|
ARC |
Application Rental Commercial Unit |
|
RCL |
Rent Collection |
|
TLR |
Tenant Late paying the Rent |
|
CMT |
Tenant Call For Maintenance |
|
TSK |
Tenant Skipping |
|
TDM |
Tenant causes Damages to Unit |
|
TLV |
Tenant wants to leave & break Lease |
|
ARI |
Annual Rental Increase |
T_Process_Steps
|
Code_P |
Step |
Description |
Code_F |
|
ARA |
1 |
Applicant fills Form and Sign |
FRM1 |
|
ARA |
2 |
Check all fields and Instructions on the form |
|
|
ARA |
3 |
Enter Form in RMS |
|
|
ARA |
4 |
Send Form-RMS by Internet to credit Check |
FRM1 |
|
ARA |
5 |
Reception &process Credit Check response |
|
|
ARA |
6 |
Fill & Sign LA |
FRM4 |
T_Forms
|
Code-F |
Description |
Nb Pages |
|
FRM1 |
Printed form Applicant for residential unit fills |
1 |
|
FRM2 |
Notice of Lease Renewal |
2 |
|
FRM3 |
Application to End the Lease |
3 |
|
FRM4 |
Lease Application |
6 |
T_Rules_Set
|
Code_P |
Step |
Code_R |
Description |
Value |
Units |
Other_1 |
A-1 |
A-2 |
A-3 |
A-4 |
|
ARA |
5 |
R1 |
CC Negative |
|
|
|
A1 |
A2 |
|
|
|
ARA |
5 |
R2 |
Lease Less |
12 |
MM |
|
A3 |
A4 |
A5 |
A6 |
|
ARA |
5 |
R3 |
Lease GE |
12 |
MM |
|
A3 |
A4 |
A5 |
A7 |
|
ARA |
5 |
|
|
|
|
|
A8 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
CC=Credit
Check
T_Actions
|
Code-A |
Description |
Approval |
|
A1 |
Reject Application |
Agent |
|
A2 |
Send response to Client |
Peer |
|
A3 |
Print Lease |
Peer |
|
A4 |
Applicant signs |
Peer |
|
A6 |
PMT 3 first months rent |
Accountant |
|
A7 |
PMT 1 month rent |
Accountant |
|
A8 |
Approval |
|
We present here a simplified structure, which could be used as a base in
designing a small KM system in a Relational Model. Fields could be defined as Hyperlink to a
Document. The latter may be text, audio, video and a mixture of these
media. We present a scheme which could
summarize the structure of the proposed Data Base.
|
|
Figure 2: The Global Scheme Including The
Cardinalities, Of The Database Model
The Global scheme reflects and validates the illustrated model as presented
in figure-1. We can see the Process Steps being either translated directly into
Actions or into Rules, in order to be transformed and broken down into
Actions. The Rules in this case, are,
the Process Filters, before they are broken down into Actions. This Scheme is not in a Normalized form. Our intention was to make it as clear as
possible for the reader. The Normalized scheme for this Data structure could be
the following:
|
|
Figure 3: The Global Scheme And Cardinalities, Of The
Database Model, In A Normalized Form
Conclusion
In Today’s business world, vast amounts of data and information are filtered through an organization. A method for representing, capturing, storing and retrieving real-world knowledge on a DBMS structure is presented here. We described in detail the model and its content, in a simple manner. In this experimental study, the goal of the author is not the relevance of the various KM tools, but rather to suggest a simple and rapid solution to a small organization, in need of a more structured KM. DBMS are common tools and are easily and rapidly implemented. The small organization lacks technical resources and could not manage sophisticated and cumbersome systems, catered exclusively for the Management of Knowledge. This could be viewed as a transit solution till the more sophisticated tools could be applied. The model, need to be presented in a more detail form before the Implementation phase, in which, we intend to put these concepts into a RDBMS. It could be the subject of a subsequent article. We will present, in a more comprehensive way the Design of the data structure, as well as some forms of complementary structures, such as XML or others.
References
Bray, T. Paoli, J., Sperberg-McQueen, C.M, Maler, E. and Yergeau, F. (September 2006). "Extensible Markup Language (XML) 1.0 (Fourth Edition)-Origin and Goals". World Wide Web Consortium; retrieved on October 29, 2006.
Bukowitz, W. and Williams, R. (1999) Knowledge Management Fieldbook,Prentice-Hall.
Harvard Business Review on Knowledge Management,
Nonaka,
Preece, A., Flett, A.,
Sleeman, D., Curry, D., Meany, N. and Perry, P. (2001) Better Knowledge
Management Through Knowledge Engineering: A Case Study in Drilling
Optimisation, Aberdeen, UK.
Pillania, R.K. (2006) State-of-Art of Knowledge Storage and Access in Indian Industry (July 13, 2008). Journal of Information & Knowledge Management, 5 (1), pp. 55-61; Available at SSRN: http://ssrn.com/abstract=1159386
Rajamani, U. (2000). Unpublished material
Stewart, T. A. (1997) Intellectual capital: the new wealth of organizations.
Tunstall-Pedoe, W. (
About the Author:
Dr. Emile Segev has instructed as an Adjunct Professor at the