Knowledge Management tools

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Knowledge Management tools for forest management DSS's

Description of potential KM tools

Avatar (virtual)

  • Description: An avatar is a computer user's representation of himself/herself or alter ego, whether in the form of a three-dimensional model used in computer games, or a two-dimensional icon (picture) used on Internet forums and other communities. An avatar is an image that a user chooses to represent himself in virtual communities, places of aggregation, discussion or online plays. The word, in Sanskrit and native of the Hindu tradition, means “incarnation”, exactly represents the assumption of a physical god’s body. In the Internet language, an Avatar is “the personage” that a real person chooses to appear to others people in the virtual world. This image, which may vary in theme and size (usually determined in advance by the regulations of virtual communities), can depict a fictional character (e.g. a cartoon, a comic), the reality (for example. vocalist or favourite actor), or even the most varied subjects, such as comic strips, text, and more. The place of greater use of avatars are the forums, instant messaging, and online role-playing games where it is customary to create an alter ego. Some sites asked to set up an avatar inspired by a particular theme to make it uniform to use in order to improve the sense of belonging to the virtual community. For example, the site of the Village of Ofelon requires an avatar of medieval inspiration, along with a nickname in the subject, tends to create a setting of knights of the Middle Ages.


Agents

  • Description:
    1. In approach of Data Mining (DM): One of the most promising techniques for retrieving information from databases, especially external ones, is the use of intelligents.
    2. In approach of Knowledge Management (KM): IAs are software systems that learn how users work and provide assistance in their daily tasks. Typically, they are used to find out and identify knowledge.
    3. In approach of Artificial Intelligence (AI) and Expert Systems (ES): IAs are small programs that reside on computers to conduct certain tasks automatically. An IA runs in the background, monitors the environment, and reacts to certain trigger conditions.

(Source: Efraim Turban, Jay E. Aronson, Ting-Peng Liang, Ramesh Sharda: Decision Support and Business Intelligence Systems, Eighth Edition, Pearson International Edition)


Best practices and lessons learned

  • Description: Typically present the situation, the options, choices taken, and the results for a typical decision problem. Best practices are those attributes ( e.g., structures, disciplines, processes, controls, metrics, tools, and staffing qualifications) demonstrated to be effective guidelines for the successful management of diverse programs and projects. Lessons learned are experiences acquired in the execution of programs and projects which can provided value-added direction to the formulation and execution of future development and operational initiatives. They are widely used in natural resource management and can be extensively found on the internet. "Story telling" allow people to gain more understanding and have greater recall then they do from written reports. Stories can be used to capture lectures on a particular topic, to capture after action reports, to record difficult to codify tacit knowledge, and for many other purposes.


Community of practice

  • Description: Support groups of individuals with similar work responsibilities but who are not part of a formally designated work team. Many communities of practice communicate through a web-based system.


Web Content Management System

  • Description: Abbreviated as CMS, a content management system, also called a Web management system, is software or a group or suite of applications and tools that enable an organization to seamlessly create, edit, review and publish electronic text. Many content management systems offer a Web-based GUI, enabling publishers to access the CMS online using only a Web browser. Also, a CMS designed for Web publishing will provide options and features to index and search documents and also specify keywords and other metadata for search engine crawlers.


Content management sites (scientific)

  • Description: Collects knowledge in some kind of web-based content management system. A Content Management System based portal or site first goal is the information service based on data and information in the adott environment. If we follow our basic knowledgements, we will get the next orientation: data (rough facts) -> information (conceived data) -> knowledge (inserted information into context). This means, that we can build a CMS portal only with basic informations and data. Not all of the people will be pleased with theese informations, but it cant be our goal. If we took the portal into strong basics, then there will evolve workgroups and communities ont he site. From this point the teamwork is much easier. Not all the users can use this website as a knowledge management system. A lot of people will see only a thematic portal, because they havent the minimal qualification for the adott specialty. The principal part of a portal is the forum and the surfaces, where the users can change information and craftsmanship. The everyday use of will decise, that the basic CMS system will be a KMS or not. The knowledge in a content management system is not only the words on the page. Instead, the knowledge is gained via users, the processes and opportunities used to capture organisational knowledge.


Database Management System (DBMS)

  • Description: A common way to organize original source material in a database structure. It is irrelevant whether the data is numeric or graphic or computer files. Web-based methods have been developed to manage database online. Data mining techniques are useful in retrieving information from huge databases – several techniques are developed in order to find appropriate results and quick solutions with efficient search algorithms. Database Management Systems store raw data and we need data mining (DM), because of its help useful information can be gathered from data. When data are transformed into knowledge, DM is a significant step in this process.


Expert System (or Knowledge-based system)

  • Description: Expert systems are designed in such a way that a rulebase and an inference engine are interlinked to simulate the reasoning process that a human expert pursues in analyzing a problem and arriving at a conclusion. In these systems a vast amount of knowledge is stored in the knowledge base. The knowledge base could consist of "if then" statements that resemble the sequence of mental steps that are involved in the human reasoning process.


Frequently asked questions

  • Description: In the course of performing a job, people naturally identify questions that their coworkers or their clients ask repeatedly. It is worthwhile to document and develop useful and standardized answers for these types of repetitive questions. Web-based systems also exist that specialize in the management of these questions (e.g., knowledge management systems, below).


Knowledge management systems

  • Description: Network- or web-based systems for the entry, organization, storage, and sharing of knowledge in some knowledge domain.


Knowledge map (cognitive maps, mind maps)

  • Description: Establish a classification scheme called a taxonomy of knowledge, provide a frame of reference for many knowledge management products, and serve as a critical first step for identifying available knowledge. The more sophisticated versions of tools in this category include ontology editors.


Online Scientific Journals

  • Description: Managing and making accessible published books and scientific journal articles has long been the province of science libraries. These services are also available on the internet either free of charge. More and more scientific journals have placed all or part of the content of their original research articles online. Search engines allow to find relevant articles and the number of citations refering to them.


Simulation systems more

  • Description: Are a popular way to organize specific problem solving knowledge and provide precise, quantitative answers to guide natural resource managers. Most such models have not yet been converted to execute over the internet, however, many simulation models can be downloaded from the internet and then executed on a stand-alone computer.


Yellow-page directories

  • Description: Aid in finding hard-to-access tacit knowledge resources by providing access to experts. They also organize existing web sites and serve up a variety of explicit knowledge assets in understandable ways.


Wiki

  • Description: Free-content information collaboratories allow to create and distribute free information content, e.g., encyclopedias, wiki. Articles are edited by volunteers and are subject to change by nearly anyone. They cover a wide range of topics, but lack the authority of traditional materials and lack the chance of a quality control regarding the content.


Web portal

  • Description: Provide links to many other sites that can either be accessed directly or can be found by following an organized sequence of related categories. The provider of a web portal is responsible for structuring and filtering of web-addresses relating to a special theme.


Workflow Systems

  • Description: With Workflow Systems (WFS) we can support standardized business processes. The WFS determine the information flow. The aim of WFS is to build the optimal process steps to persons in the right place for the specified task. A WFS has knowledge for processes: set of skills for the task, rules how should be work, guidelines, path of the information, etc. With other tools (Database Management Systems, Content Management Systems), WFS can contain additional knowledge, for example governmental and industrial standards.


Other tools

  • Description:
  • Examples: [http:// ]

Classification of potential KM tools

Criteria to classify KM tools

KM approaches for Problem identification

  • Allow a documentation in order to transfer knowledge to next generation
  • encourage decision makers to discover new problems and opportunities by exposing themselves to new information, situations, issues, and ideas
  • help decision makers in recognizing upcoming problems for which solutions have been developed previously

KM approaches for Problem structuring / modelling

  • allow to actively create new knowledge when faced with a new problem and to develop novel solutions
  • Allow to identify expert knowledge, facts and experiences in relation to decision problem
  • Allow to codify available knowledge for machine / computer
  • allow to reduce complexity
  • support the engagement/involvement of experts
  • allow to combine various forms of information (qualitative / quantitative)

KM approaches for Problem solving / decision making

  • Allow to capture and retain knowledge, making it available to decision makers who are seeking solutions from previously solved problems
  • facilitate decisions that are reproducable
  • facilitate a rationale decision making process
  • improve decision making ability
  • increase productivity of decision maker (within cognitive, time and economic limits - effective and efficient decisions)
  • support decision-making phases
    • development (e.g. identify or analyze alternatives)
    • selection (e.g. advice about which alternative to choose)

Criteria according to the decision problem

  • Decision situation (unilateral, collegial, participatory)
  • Level of planning (operational, tactical, strategic planning)
  • Challenges / key problems in forestry domain?
  • Which goods and services are supported?

Criteria according to stakeholders / users /organisations

  • allow participation (active / passive)
  • Technical skills of users required
  • Level of acceptance of users in terms of usability, reliability, easyness,…
  • Kind of introduction of the tool to users
  • Role of stakeholder within the process (expert, decision maker, public)
  • Who owns the knowledge in organizations? How to make use of the knowledge available? Who coordinates knowledge?
  • Type of organization (public bodies, forest enterprises,…)
  • To whom give access to information / knowledge (skill, commercial , privacy)
  • Data mining of private enterprises (CRM?) of relevance

Criteria for development issues - technical aspects

  • Allows to generate interfaces between tools/techniques
  • Allows a definition of interfaces between methods and models
  • Rules for selecting information (in hierarchical decision making processes, robustness, reliability, …)
  • allows to be adapted to new challenges, problems are they flexible enough?

Classification of KM tools according to problem solving

Gray's classification [1] recognizes different types of managing knowledge with regards action motivations in two different types of problems. The motivation can either be problem identification or problem solving, and the problem can be either unique/new or previously solved. Combining these in 2*2 matrix shows us four types of KM: (1) Discovering new issues, (2) Creating knowledge, (3) Acquiring knowledge, and (4) Raising awareness. Shifting between these ascendingly can be seen as (a) identifying, (b) preserving/storing, and (c) distributing/transferring knowledge (see Fig. 1 below).

Gray redrawn.png

Fig. 1. Knowledge management types within decision problems after Gray (2003).

Table for the Classification of KM tools

Tool Classification 1 Classification 2
Knowledge maps
Databases
Expert systems
Free-content information collaboratories
Web portals
Electronic yellow-page directories
Communities of practice
Frequently asked questions
Scientific content management sites
Online scientific journals
Library services
Best practices and lessons learned
Lectures and story telling
Apprenticeship programs
Web-based learning
Simulation models


Other options to classify...

References

  1. ↑ Peter H. Gray, A problem-solving perspective on knowledge management practices, Decision Support Systems, Volume 31, Issue 1, May 2001, Pages 87-102. Available here
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