The present paper is a component of an exploratory research project focused on discovering new ways to build, organize and consolidate organizational memory for an economic entity by means of the new a€sSemantic Weba€t technologies and also encloses someorganizational memory, organizational knowledge, semantic web, knowledge management

Mangiuc Dragos Marian

English

Research Papers in Economics

981 
THE ROLE OF THE SEMANTIC WEB IN STRUCTURING ORGANIZATIONAL KNOWLEDGE 
 
Mangiuc Dragoş Marian  
The Academy of Economic Studies in Bucharest Faculty of Accounting and Management Information Systems 
Bozieni 8, Bl. 831, Sc. A, Et.9, Ap.906, Sector 6, Bucureşti mangiuc@gmail.com Tel. 0723 – 22 78 76 
 
The present paper is a component of an exploratory research project focused on discovering new ways to build, organize and 
consolidate organizational memory for an economic entity by means of  the new  “Semantic  Web” technologies and also 
encloses some of the results of a previous doctoral research in the field of information technology assistance for the financial 
audit. The paper is an attempt to synthesize the ways organizational memory and organizational knowledge management may 
be optimized by means of the new “Semantic Web” philosophy. This paper offers a picture of where the typical organization is, 
and where it needs to be, in order to become a knowledge-aware organization and leverage the technologies of the “Semantic 
Web”. As a consequence, a knowledge-centric process was defined, along with a “how-to” roadmap for crafting a company’s 
way to the Semantic Web. 
 
Keywords: organizational memory, organizational knowledge, semantic web, knowledge management  
 
JEL code: M15 
 
Introduction 
In order to benefit from the “new wave” of semantic technologies, any modern organization must have a strategic 
view and also a reasonable understanding of the Semantic Web, XML, Web services, RDF, taxonomies, and 
ontologies. Each of these technologies has its distinct role in the build of organizational memory and the structure 
of organizational knowledge. It is the purpose of this paper to provide an opinion on how a company could be 
driven to take advantage of these technologies now so that it could start gather the rewards of the Semantic Web 
and prepare for the future. The paper focuses on three areas: diagnosing the problems of information management, 
providing an architectural vision for a modern organization, and providing some hints of how that vision may come 
true. 
 
Research Methodology 
The paper is a component of a wider research project called “Research in the Field of Modeling And Building 
Organizational Memory. OMCAAF – A New Methodological Framework for Financial and Accounting Cognitive 
Acquis Capitalization”, and also continues a previous doctoral research in the field of computer-assisted financial 
audit tools and techniques, whose final results were publicly defended in order to be validated by the scientific and 
academic community. The main goal of the aforementioned research was the identification of some new areas of 
applicability for the modern knowledge-based information technologies in the field of financial audit. 
In order to provide a set of valid and well-documented opinions about the realistic ways of augmenting the use of 
organizational memory by means of the modern information technologies, the author’s proposals were preceded by 
an ample process of documentation and analysis of the field literature, allowing to get into terms with the main 
schools  and  opinion  trends  in  the  area,  as  well  as  the  actual  level  of  interconnection  among  the  disciplines 
contributing to the present content of the “organizational memory”, “organizational knowledge” and “Semantic 
Web”  concepts.  When  possible,  practitioners’  expectations  identification  was  attempted,  both  by  means  of 
questionnaires and direct interviews. In case some other author’s opinion was enclosed, whether in exact quotation 
or synthetic form, a complete mention of the source identification information was made. 
By defending the research results at the proceedings of such a scientific conference, attended by both scholars and 
practitioners bearing some interest in the research area, the author attempts to get further validation of his opinions, 
both confirmation and rejection of the aforementioned opinions’ scientific and practical importance being welcome. 
 
The usual organizational issue: too much information, too little knowledge 
The most significant issue today for a typical organization is that information management is mostly chaotic. One 
important  cause  for  the  status  quo  is  the  huge  amount  of  information  coming  in—from  a  wide  variety  of 
information sources (Berners-Lee, 1991). Making matters worse are the various formats of the data (paper, email, 
along with a wide variety of electronic media formats). Due to the amount of information coming in from various 
sources, its management gets more and more difficult. The “standard” organization is usually enclosing a lot of 
people  getting  overwhelmed  with  information  (Fensel,  2007).  Along  with  a  missing  cohesive  information 
management  vision,  the  typical  organization  has  lots  of  information,  but  very  little  knowledge.  The  typical 
knowledge management process in an organization is depicted in the following figure (Figure 1). 
 982 
 
Figure 6 – The typical knowledge management process 
 
The stages of this process usually are: 
 -  The  information  capture  –  is  the  first  stage  in  information  management.  Usually,  an  employee  of  the 
organization  takes  information  from  somewhere  (newspaper,  radio,  Internet,  database,  phone  call,  customer 
contact, email) and brings it to the organization in some way. Many times, this is where the process stops (Ewalt, 
2002). The employee may send it via email to someone, where it is lost in the “constellation” of emails that 
overwhelm the organization. If the data isn’t lost in this way, a paper, a presentation, or a status report is usually 
written. 
 - The information production – is the second stage, (if information gets that far), where the data is put into a 
database, recorded to a digital file, or indexed into a search engine. Entering information is always the first step, but 
the problem is that each division, group, or project in the company enters the information into different systems. 
But  a large-scale organization  may  enclose tens  or even  hundreds  of  different  software systems  dealing  with 
information.  Moreover,  a  financial  database  with  the  company’s  invoices,  bills,  and  collections  may  add 
information to that total. Finally, the corporate human resources database must be taken into account. All the 
aforementioned software systems work like “information pipe” systems, able to perform a specific task, at the 
expense of “trapping” the data and reducing the organization’s business agility and the capacity to adapt to new 
situations (Heflin et al., 2002). 
 - The information integration – is the third stage, but it can also be missed, depending on the complexity of the 
organization’s information architecture. Because of all the “information pipe” systems, there is usually no good 
way to gather all the information providers into a coherent picture. That is, any attempt to combine information in 
any way is a tiresome process, involving data conversions, incompatible software systems, and frustrated systems 
integrators (Patel-Schneider et al., 2006). There is no repeatable process for integrating the systems, because each 
database and software system is designed differently and has different interfaces for communication purposes. As a 
result,  there  is  usually  little  or  no  integration  of  the  databases,  because  it  is  both  prohibitively  difficult  and 
expensive.  When  there  an  integration  solution  arises,  organizations  usually  pay  a  (very  expensive)  systems 
integrator  to  create  a  new  and  expensive  “information  pipe”  system  that  integrates  with  the  existing  systems 
(Biezunski, 2003). 
- The information search – is the fourth stage, depicting the process of “discovery” of the corporation’s internal 
resources. This is usually random and time-consuming, involving many different systems. The user may have to 
log in to multiple databases and search engines, and manually compare and distinguish the information to get a big 
picture or coherent answer (Obrst and Liu, 2007). Even the results from search engines are usually based on 
keywords and Boolean logic, so they may or may not be relevant. 
 - The application of the search results - is the final stage of the process. After the tiresome search process, the 
result is usually a presentation or paper report. Many times, this process of creating the report involves several 
employees. The approval process is done by manual reviews and is slow. After the new product is created, the 
information may or may not be filed somewhere; it may be sent to a wrong or non-existent destination. If the report 
is filed, perhaps it is filed onto a Web server that may or may not be indexed by all (or even one) of the corporate 
search engines. If the new document is integrated into one of the corporate databases, there is no way to tell if the 
information has been superseded or is obsolete, which parts of the document are authoritative, and if the current 
version of the document has been approved by the organization. Lastly, there is information reuse – the ability to 
discover months or years later, and to refine, annotate, and incorporate past knowledge (Baader and Hollunder, 
2001). 
If any of these challenges are every day phenomena for an organization, then the organization may be in need of 
the Semantic Web. A well driven and well managed company will leverage the Semantic Web technologies to craft 
an information architecture vision, effective over every part of the organization life cycle. 
 
   983 
The Knowledge-Centric Organization – A Big Step Ahead 
A knowledge-centric organization will incorporate Semantic Web technologies into every part of the work life 
cycle,  including  production,  presentation,  analysis,  dissemination,  archiving,  reuse,  annotation,  searches,  and 
versioning. This section is a hint on how the semantic-oriented knowledge management process should be (see 
Figure 2): 
 
Discovery and Production 
The discovery and production phase is where an individual receives information and intends to translate it into 
organizational knowledge. The process should be an integral part of the corporate workflow process. This is an area 
where organizations should be aggressive an greedy in capturing information, because the effectiveness of reuse 
will be directly proportional to the quantity and quality of information captured. It is important that any new piece 
of  information  is  marked  up  with  XML,  using  a  relevant  corporate  schema.  Moreover,  the individual should 
digitally sign the XML document using the XML Signature specification to provide strong assurance that the 
validity of the information has been verified. The annotation process may further arise, the employee may want to 
use RDF to annotate the new information with own notes or comments, adding to the XML document, but without 
breaking the digital signature seal of the original material. Finally, the author should digitally sign the annotation 
with XML signature. It is of main importance that before the information is integrated, its contents to be mapped to 
topics in the taxonomy and entities in the corporate ontology so that pieces of the information can be compared to 
other pieces of information in the corporate knowledge base. Once this is done, it is time to store the information in 
an  application  with a Web  service interface, and any  new  Web  service  should  be  registered in the  corporate 
registry, along with its taxonomic classifications. 
 
 
Figure 7 – The semantic-oriented knowledge management process 
 
Search and Retrieval 
As data is stored in an easily accessible format (Web services) and is associated with an ontology and a taxonomy, 
retrieval of information is much easier than the random process described in the previous section. Integration of all 
the Web services is not difficult because they all have a SOAP interface, and are registered in a corporate Web 
service registry; it is easy for an application to find what it is looking for (Berners-Lee et al., 2001). Because of the 
hard work performed during the discovery and production process, the search and retrieval process is simpler and 
provides important functionality:  
 - Discovery of knowledge via taxonomies – this is the newfound power and possibly the killer app of the Semantic 
Web  –  the  mining  associations.  In  the  field  of  electronic  commerce,  associations  offer  additional  buying 
opportunities to customers. 
 - Pattern-based searches – all data can be semantically linked by relationships in the ontology, so patterns that 
would only be seen in the past by old data mining techniques that did not directly utilize meaning, can now be 
dynamically found with semantic searches. 
 - Manual and agent-based searches – although all of the searches can be manual, software agents can be endowed 
with rules to continually search the knowledge base and provide users with up-to-the-second results and alerts. 
 - Rule-based orchestration queries – Web services can be combined to provide modular functionality, so rules 
may be used to merge various searches from different Web services.  
 - Automated inference support – the corporate ontology explicitly represents concepts and their relationships in a 
logical  and  machine-interpretable  form,  so  automated  inference  over  the  ontology  and  its  knowledge  bases 
becomes possible. Given a specific query, an ontology-based inference engine can perform deduction and other 
forms  of  automated  reasoning  to  generate  the  possible  implications  of  the  query,  thus  returning  much  more 
meaningful results. The inference engine may discover inconsistencies or even contradictions in the ontology or 
knowledge bases (Wreder and Deng, 2007).  
 
Application of Results 
The  final  information  production  stage  of  the  knowledge-centric  organization’s  knowledge  process  is  the 
application of results. If a new report has been created the responsible person should use the production process, 
depicted earlier in the “Discovery and Production” section. Another application in the last stage of the knowledge 984 
process  may  be  simple  data  annotation,  requiring  that  the  author  of  the  annotation  should  digitally  sign  the 
annotation. Before the new annotation items are added, version control should be added to the document, and 
finally  the  document  should  be  stored  in  the  corporate  information  base.  If  an  organization  has  a  content 
management and workflow process that includes version control, annotation, and trust assertions, it will be easier to 
find information and apply the conclusions that were made earlier. 
 
How could the “semantic” vision come true? 
Most companies need to change their business process in order to take advantage of Semantic Web technologies. 
Luckily, these changes can be gradually implemented, and the organization can easily evolve into a knowledge-
centric organization. The most challenging aspect may not be the technology; it may be changing the mind-set of 
the employees. Changing behavior and the ways that all levels think about accessing, integrating, and leveraging 
knowledge is critical: 
 
How to Prepare for Change 
The organization needs to be prepared. The stakeholders impacted by the change must be identified and led through 
the change process. A clear purpose and some clear goals and milestones are needed: 
 - A clear purpose for changing your information management process needs to be developed. 
 - Clear goals must be set. 
 - Stakeholders must be identified and a change plan must be developed. 
 - A core team that will help communicate the vision must be picked. 
 
How to Begin Learning 
In the author’s opinion, a major time investment should be made in understanding the ideas and technologies 
behind  the  knowledge-centric  process  and  all  the  implied  technical  staff  must  get  to  a  reasonable  level  of 
knowledge. The following actions should be taken: 
 - The management staff must understand the main concept of the Semantic Web and the benefits of its adoption for 
the organization 
 - The technical staff to should be able to master the details of the soon-to-be-adopted technologies. 
 
How to Create an Organization’s Strategy 
Now that management and the technical staff are “on board”, it is time to design an organizational knowledge 
management strategy: 
  - Detailed technical goals must be set. For example: 
  - Corporate documents must be marked-up in XML. 
  - Applications should be exposed as Web services. 
  - Web services orchestration tools should be built. 
  - A corporate Web services registry should be established. 
  - Ontologies should be built. 
  - Tools that will help the production process should be used. 
  - Search tools should be integrated 
  - An enterprise portal should be used as a catalyst for knowledge engineering. 
  - A plan with a workflow change strategy must be developed. 
  - Appropriate staff must be set in place. 
  - A schedule must be set. 
 
Conclusions 
The  present  research  is  an  attempt  to identify  the  role  of the  Semantic Web  in  structuring  knowledge  at the 
organization level. The paper is an attempt to present an accurate view of the place where most of the typical large-
scale organizations are today, and also the author’s opinion on the place they need to be in order to become 
knowledge-centric  organizations  and  leverage  the  technologies  of  the  Semantic  Web.  As  a  consequence,  a 
knowledge-centric process was defined and a “how-to” roadmap for crafting an organization’s path to the Semantic 
Web was proposed. 
 
   985 
Bibliography 
1. Baader, F., Hollunder, B. – KRIS: Knowledge Representation and Inference System, Implemented Knowledge 
Representation and Reasoning Systems Journal, SIGART Bulletin 2, no. 3, June 2001 
2. Berners-Lee, T. – What the Semantic Web Can Represent, September 1991, Available on-line at 
http://www.w3.org/DesignIssues/RDFnot.html 
3. Berners-Lee, T., Hendler, J., Lassila, O. – The Semantic Web, The Scientific American, May 2001 
4. Biezunski, M. – XML Topic Maps: Creating and Using Topic Maps for the Web, Addison-Wesley Publishing, 
2003 
5. Ewalt, D. – The Next Web, Information Week, October, 2002 
6. Fensel, D. – Semantic Enabled Web Services, XML-Web Services ONE Conference, June 7, 2007 
7. Heflin, J., Volz, R., Dale, J. – Requirements for a Web Ontology Language, W3C Working Draft, July 8, 2002 
8. Obrst, L., Liu, H. – Knowledge Representation, Ontological Engineering, and Topic Maps, Addison-Wesley 
Publishing, 2007 
9.  Patel-Schneider,  P.  F.,  McGuinness,  D.  L.,  Brachman,  R.,  Resnick,  L.  A.,  Borgida,  A  -  The  CLASSIC 
Knowledge Representation System: Guiding Principles and Implementation Rationale, Implemented Knowledge 
Representation and Reasoning Systems, SIGART Bulletin 5, no. 3, June 2006 
10.  Wreder,  K.,  Deng,  Y.  –  Architecture-Centered  Enterprise  System  Development  and  Integration  Based  on 
Distributed Object Technology Standard, Institute of Electrical and Electronics Engineers, Inc., 2007 
   

A - The CLASSIC Knowledge Representation System: Guiding Principles and Implementation Rationale, Implemented Knowledge Representation and Reasoning Systems,

Knowledge Representation and Inference System, Implemented Knowledge Representation and Reasoning Systems Journal,

Knowledge Representation, Ontological Engineering, and Topic Maps,

Requirements for a Web Ontology Language, W3C Working Draft,

Semantic Enabled Web Services,

The Next Web, Information Week,

The Semantic Web, The Scientific American,

What the Semantic Web Can Represent,

XML Topic Maps: Creating and Using Topic Maps for the Web,

THE ROLE OF THE SEMANTIC WEB IN STRUCTURING ORGANIZATIONAL KNOWLEDGE

http://steconomice.uoradea.ro/anale/volume/2009/v4-management-and-marketing/201.pdf

THE ROLE OF THE SEMANTIC WEB IN STRUCTURING ORGANIZATIONAL KNOWLEDGE

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics