Difference between revisions of "Wg3 workplan"
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The work concentrates on the review of knowledge management (KM) methods to acquire, verify, and validate knowledge from single to multiple experts, and methods to represent knowledge and transfer information in general. The categorization of approaches, tools, techniques and methods will be done according to the phases of DSS development (1) and DSS application (2). | The work concentrates on the review of knowledge management (KM) methods to acquire, verify, and validate knowledge from single to multiple experts, and methods to represent knowledge and transfer information in general. The categorization of approaches, tools, techniques and methods will be done according to the phases of DSS development (1) and DSS application (2). | ||
| − | + | #According to DSS development we will evaluate KM - approaches which are used and sometimes required in the development process (requirements analysis, concept and design, software implementation, integration / test, user documentation, install, maintenance and support) in order to conceptualize, develop and integrate DSS. | |
| − | + | #We will evaluate KM - approaches which are part of existing DSS and used in the application process (intelligence, design, choice, monitoring) in order to generate, acquire, verify, validate, store, transfer, and apply knowledge in natural resource management. | |
==Activities== | ==Activities== | ||
Revision as of 17:50, 13 January 2010
Contents
Workplan
Objectives
The work concentrates on the review of knowledge management (KM) methods to acquire, verify, and validate knowledge from single to multiple experts, and methods to represent knowledge and transfer information in general. The categorization of approaches, tools, techniques and methods will be done according to the phases of DSS development (1) and DSS application (2).
- According to DSS development we will evaluate KM - approaches which are used and sometimes required in the development process (requirements analysis, concept and design, software implementation, integration / test, user documentation, install, maintenance and support) in order to conceptualize, develop and integrate DSS.
- We will evaluate KM - approaches which are part of existing DSS and used in the application process (intelligence, design, choice, monitoring) in order to generate, acquire, verify, validate, store, transfer, and apply knowledge in natural resource management.
Activities
Work Program
According to objective1 following activities will be implemented:
In most cases various KM - approaches (compare table 1) will be used to develop components of DSS and they will be partly integrated where information, data and conceptual knowledge is captured. To get an overview about the possible techniques we will not concentrate on approaches applied in natural resource management only, but possible KM - approaches of other fields in DSS development, too.
- possible KM approaches / techniques / methods will be listed, the list of Table 1 might serve as a starting point
- Success criteria for the evaluation of KM approaches will be listed
- DSS cases described in the DSS review (WG1) will be analyzed according to the KM approaches used in the development process
- benefits and limitations of different KM approaches / techniques / tools in the process of DSS development will be described
According to objective 2 the following activities will be implemented:
- possible KM approaches and methods will be listed, the list of Table 1 might serve as a starting point
- DSS cases described in the DSS review (WG1) will be analyzed according to the KM approaches implemented
- Success criteria for the evaluation of the KM approaches will be listed
- The way how KM approaches, communication tools and methods for information transfer in general are integrated into DSS will be described and categorized according to their contribution to support decision makers in the decision making phases intelligence, design, choice, monitoring
- A categorization according to their contribution to problem solving and problem recognition in the decision-making process will be done in the following manner:
- practices and tools that encourage decision makers to discover new problems and opportunities by exposing themselves to new information, situations, issues, and ideas (e.g., discussion forums, virtual communities, workshops, and conferences)
- practices and tools that allow decision makers to actively create new knowledge when faced with a new problem and to develop novel solutions (e.g., developing expert systems, cognitive mapping, data mining, neural networks)
- practices and tools that capture and retain knowledge, making it available to decision makers who are seeking solutions from previously solved problems (e.g. applying expert systems)
- practices and tools which might help decision makers in recognizing upcoming problems for which solutions have been developed previously (e.g. Bayesian Belief Networks)
List of KM approaches, tools and techniques
For the review of appropriate KM approaches it will be important to distinguish between tools and the techniques which are used to run the "tools". For instance, a database contains data and information which are managed by a database management system (DBMS) and several data mining techniques can be used to retrieve data and information. On the other hand there exists a multitude of techniques for input/output and storage, as well as for categorization and sharing of data and information in a database. In this context several techniques and tools are an integral part of a database management system and it will be necessary to categorize and describe the tool (DBMS) and the techniques (e.g. data input, data mining) in the review. In order to clarify possible overlaps to WG 4 it will be important to concentrate on the tools and techniques itself, but not focusing on the "process" to apply them; the participatory aspect should be tackled in WG 4. Table 1 gives a short overview of some "tools" which comprise several "techniques" or "methods".
Table 1: "Tools" using information technology and knowledge management techniques, which could be an integral part of DSS development and application
| Tools | Description |
|---|---|
| Knowledge maps (cognitive maps, mind maps) | 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. |
| Databases | 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. |
| Expert Systems | There are various expert systems in which 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. On the other hand Artifical neural networks (ANN) consists of an adaptive interconnected group of artificial neurons and processes that changes its structure based on external or internal information that flows through the network during the learning phase. The utility of ANN models lies in the fact that they can be used to infer a function from observations. This is particularly useful in applications where the complexity of the data or task makes the design of such a function by hand impractical |
| Free-content information collaboratories | Create and distribute free information content, e.g., encyclopedia. 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 portals | 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. |
| Electronic yellow-page directories | 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.
Communities of practice 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. |
| Frequently asked questions | 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. |
| Scientific content management sites | Collects knowledge in some kind of web-based content management system. First, the knowledge has to be found, organized, synthesized, reviewed for quality, and uploaded for availability. Second, the knowledge content has to be updated and maintained so it keeps its currency. Software systems exist that support both of these functions. |
| Online scientific journals | 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. |
| Library services | 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. |
| Best practices and lessons learned | Typically present the situation, the options, choices taken, and the results for a typical decision problem. They are widely used in natural resource management and can be extensively found on the internet. |
| Lectures and 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. Web-based software systems exist that support this knowledge management tool.
Apprenticeship programs Are typically one-on-one type relationships where an expert coaches a less experience person in various forms. |
| Web-based learning | Allows to translate a typical classroom experience to an online media to offer students the opportunity to learn codified knowledge in a structure way at their own pace. |
| Simulation models | 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. |
Outputs planned for year
- Common understanding of the proposed activities is achieved after presentation and discussion at the first WG meeting
- Presentation of a review of available problem structuring methods (PSM's) in relation to objective 1 during the first work group meeting in Riga
- List of possible KM approaches / techniques / methods is produced
- Success criteria for the evaluation of KM approaches are discussed and described
- Categorization of KM approaches is done according to their contribution to support the decision making phases
- Mid term report on WG 3 activities
