This research exposes the necessary elements in the technological area and the socio-technical area, to create a knowledge management system, capable of pushing the information that is relevant to each of the knowledge workers of an organization.
This covers the integration of the aforementioned parts for the creation of the system and the recommended steps to follow for its installation. Then enter the most basic possible applications of this system, giving an example of the new tools that the infrastructure it generates could provide. Extending a recommendation from organizations that could benefit from it.
Methodology
The IEEExplore database was consulted at the Tecnológico de Monterrey Digital Library to obtain relevant information articles from; taxonomy, XML, knowledge portals, competency models, knowledge representation and indexing.
A search for published articles (white papers) with topics related to; Taxonomy, knowledge tools, knowledge worker, metadata, knowledge bases, knowledge portals, competition models, semantics, search engines and tagging.
Introduction
This article will handle the concepts and technological tools that are considered necessary for the creation of a knowledge management system dedicated to taking advantage of a taxonomy, the profiles of individuals and the areas of competence of an organization. That it will have the ability to take the information stored in the bases of an organization, to segment it, analyze it and classify it according to a taxonomy. The system will push relevant information to each individual who interacts with it, aligned to their profile and competencies.
According to everything that will be covered, it is important to clarify that there are already referent efforts in the matter, but none as integrated as what is sought to present. Subsequently, information on technologies and tools that are linked from the sociological and technological aspects with the achievement of the creation of a system like the one that has been described will be managed.
This information is integrated presenting the technologies and strategies to follow to create the knowledge management system.
Framework
"Relevant knowledge at the socio-technical level for the development of a taxonomy consistent with the organization for the development of the system"
Taxonomy and Classification
The Delphi group document (2004) calls the taxonomy; list of hierarchical or poly-hierarchical topics. It may not include a definition of topics, but only a hierarchical relationship of these. The taxonomy itself does not have design or development formats. It is used to create a navigation structure through a collection of content.
Hagerdon (2001) defines classification as the process by which information, whether in document or data format, is grouped in such a way that it is easier to find.
As benefits of its use, we find that the taxonomy and the use of the classification allow us to create relationships that facilitate the search and grouping of relevant information, avoiding noise in the results of any search, presenting relevant information. Furthermore, it is possible to take advantage of the knowledge of taxonomy to create models of content similarity. All this is necessary to be able to create a representation of the knowledge of the organizations and to be able to use tools like the one developed in LILOG that was specifically designed for extraction of knowledge in German to represent real-world knowledge.
Semantics
Fromm (2004) describes semantics as a branch of linguistics that deals with the study of meaning, changes in meaning, and the principles that govern the relationship between sentences or words and their meanings, while the semantics of information it is the semantic representation for our systems, data, documents, or agents. Information semantics represents the organizational and cultural contexts embedded within missions, hierarchies, vocabularies, workflows, and organizational work patterns
The concept of knowledge Knowledge
worker
Taylor (1998) defines the knowledge worker within the same classification as the “symbolic” analyst, which is all those individuals dedicated in some way or another to solving problems; research scientists, design engineers, software engineers, civil engineers, biotechnology engineers, health engineers, public relations executives, investors. Also included is much of the work done by business administration consultants, financial consultants, tax consultants, energy consultants, agricultural consultants, arms consultants, architectural consultants, management information specialists, organizational development specialists, headhunters corporate, and systems analysts, executives and marketing strategists,art directors, architects, publishers, writers, journalists, musicians, television and film producers, and even university professors.
Knowledge tools
According to Ruggles (1997). Widely defined knowledge tools allow the generation, coding and transfer of knowledge. Like any tool they are designed to lighten the burden of work through automation, allowing resources to be applied to the task for which they are best designed. It is important to note that not all knowledge tools are based on computation.
Knowledge bases
Soergel (1996) presents that the main function of a knowledge base is to map a space of concepts, where these are related to terms and provide definitions that finally provide information and serve as a guide tool.
Knowledge Portals
Portals that pro-actively deliver links, in real time, to content and individuals that are directly relevant to the user's tasks. They can also be developed like any other portal to run on the web, as is the case of the ICAR Knowlege portal, which was created for a research organization (“A prototypal environment for collaborative work within a research organization”, 2003).
The importance of a portal as such is that where more than 200 people work, too much time is spent trying to capitalize on internal knowledge, if it is even attempted.
Competency Models
Copithorne (2003) points out that competencies are observable and measurable knowledge, skills, attitudes and other job attributes that predict performance ability in a given function according to a criterion.
Copithorne's (2003) Fig. 1 model suggests that competition models should be created according to the organization's objectives, segmenting them into the same functions of the organization.
Bonjour (2002) from an external perspective marks that a model of a particular competition should be a black box that yields an expected result as a result of the inputs of what is sought and the framework of action available.
"Technologically relevant knowledge for automatic categorization for system development"
Metadata
Quite colloquially Dornfest and Brickley (2001) describe Metadata as the material in card catalogs, TV guides, taxonomies, tables of contents - borrowing a Zen concept, it's the finger pointing to the moon. They are labels like "title," "author," "type," "height," and "language" used to describe a book, a person, a television program, a species among others. Metadata is simply data about data.
There are organizations dedicated to the use and creation of metadata management and standards such as the Dublin Core. The Dublin Core (DMCI) is an international, interdisciplinary group, founded in 1994, DCMI's that seeks to use a minimal system of metadata constructs to make it easier to find things online. The application of this technology can be extrapolated to any knowledge system.
XML tagging
Tagging is according to the document “Tagging versus Clustering” (2001) an intelligent function that analyzes a document in parts, assigns it in accordance with a defined taxonomy, choosing categories in which it frames the main topics contained within it.
XML is for Pokorny (2000) a standard for the representation of data and its exchange. XML data can be generated by applications and consumed by applications.
XML comes to solve search problems by extracting specific information from tags that have not been predesigned, thus increasing semantics.
Indexing and search engines
Indexing is the ability to take a document and separate it into relevant topics, this is the biggest function that a search engine covers that later stores the results to be called when a search referring to the topic is performed.
FREE "Fast Regular Expression indexing Engine" as not shown by Junghoo (2005) is an example of this. It is dedicated more than anything to taking a previously defined index by locating corresponding strings and analyzing these even more.
Proposal
"Integration of technological and socio-technical aspects in a knowledge management system, and its development strategy"
Everything previously analyzed is integrated into a whole that behaves as shown in Fig. 2.
The model is explained from two points of view. First, when any document is entered into the system, that is, any piece of information / knowledge, a classification engine extracts the organization's taxonomy from a base and analyzes the document, classifying it with tagging and metadata, to finally insert it in the database. knowledge. From the other extreme, when a knowledge worker accesses her computer, the portal extracts her personal model of competences and extracts the latest from the Knowledge Base. With the individual's information and access to the database, the most recent and relevant to their competencies are pushed.
The implementation strategy can take several forms, but in general it can be said that the following steps must be covered.
- Generate the organization's competency model. Generate the relevant taxonomy based on the competency model. Define the knowledge base. Create the portal that will serve as an interface. Define the competencies of each of the knowledge workers and add them to the base of competence models. Generate the classification engine with its corresponding semantic rules. Upload all previous documents to the knowledge base using the classification engine.
Finally, the system is ready to be used and both the taxonomy and the models can be adapted to the needs that time demands.
"Examples of possible applications of the knowledge management system."
The main application of the system is that of a portal that pushes relevant information from the organization, according to the individual who manages it, without search efforts. Being that it can be any data format and any type of information, that application can be broken down in several ways. To mention some, you can present separately:
- Training courses. Success stories. Project documentation. Research Documents.
Additionally, a competency model and a classification engine can also generate other types of tools.
To mention an example and illustrate the point, we will talk in little detail about an equipment classification tool. This tool could take the description of a project, its delivery time and the number of members that can participate in it. Do with this information an analysis to determine the necessary competencies for each project and create various combinations of individuals to attack each project.
As this last example, there are other possible tools that could be generated from the use of the infrastructure of this system.
Thus, the companies that would strongly benefit from the entire system would be the knowledge-intensive ones, where taking advantage of and maximizing it is crucial. A good example of companies of this nature are those that engage in any form of consulting.
conclusion
Within the presented, this list presents the most relevant topics covered in the technological line and the socio-technical line;
- Metadata, search engines and indexing, XML and tagging, knowledge concepts, taxonomy and classification, semantics, competition models.
These two aspects give rise to the tool that was described in the document. It of course requires extensive work on competencies and taxonomy in addition to classification technology.
Currently there is no built-in example that has an application on a system like the one suggested. It is also important to clarify that the tool provides the possibility of pushing information to people for whom it is relevant, but monitoring the use of this information is beyond the scope of this research.
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