In the literature, there are several categorisations or taxonomy of various information and knowledge management tools.

Liao (2003) surveyed knowledge management development within a published literature and classified articles from 1995 to 2002 about KM technologies into seven categories: (a) KM Framework, (b) Knowledge-Based Systems (KBS, (c) Data Mining (DM), (d) Information and Communication Technology (ICT), (e) Artificial Intelligence (AI)/Expert Systems (ES), (f) Database Technology (DT), (g) Modelling.

KM Framework. Liao defined KM framework as technological frameworks created from different KM theories such as: Knowledge creation (Nonaka et al, 1996), Knowledge assets (Wilkins et al, 1997), (Wiig et al, 1997), Organizational learning (Heijst et al, 1997), Organizational innovation (Johannessen et al, 1999), Intellectual capital (Liebowitz and Wright, 1999), Strategy management (Drew, 1999), (Hendriks and Vriens, 1999), Organizational impact (Hendriks and Vriens, 1999), Systems thinking (Rubenstein-Montano et al, 2001), Artificial intelligence/Expert systems (Liebowitz, 2001), Knowledge inertia (Liao, 2002), etc.

KBS systems are human centered and they have their roots on artificial intelligence research, as they attempt to emulate human knowledge in computer systems (Wiig, 1994). They have 4 main components: a knowledge base, an inference engine, a knowledge engineering tool, and a specific user interface (Dhaliwal & Benbasat, 1996). They also include all applications that can help manage the knowledge of an organization such as expert systems, rule-based systems, groupware, and database management systems (Laudon & Laudon, 2002). Examples of KBS are: Alexip, for the supervision of refining and petrochemical processes; FAILSAFE supports product quality; AppBuilder, develops decision support systems; HACCP is a KBS for change management.

Data Mining is an interdisciplinary field, it is comprised by the fields of artificial intelligence, computer science, machine learning, database management, data visualization, mathematic algorithms, and statistics. Tyndale (2002) defines data mining as "the process of selecting, exploring, and modeling large amounts of data to uncover previously unknown patterns." (p. 6). It is a technology based on knowledge discovery on databases. A very popular example of the use of Data Mining is the one used by the online store Amazon, to recommend to the user similar products to the ones he/she is looking for.

Information and Communication Technology category is broadly based on ICTs for exchanging and sharing data. Using applications or platforms that make use of the Internet, Intranets or Virtual Private Networks. ICT cn be used in decision support systems, new product development process, organizational learning, to support knowledge transfer, knowledge integration, ontology, engineering design, information sharing, e-learning, simulation, , and virtual enterprises (Liao, 2003, p. 5).

Expert systems are used for capturing knowledge. They are knowledge-intensive computer programs that capture the human expertise in limited domains of knowledge" (Laudon & Laudon, 2002). For computers to be able to make sense of this knowledge, it has to be modelled in a way that computers are able to process it. Expert systems are used in visualization,education, agriculture, knowledge representation, semantic networks, human resource management, project management, ecosystems, knowledge engineering, information retrieval, personalization, lessons learned systems, and water resources (Liao, 2003, p. 5).

A database is a collection of data organized to efficiently serve many applications by centralizing the data and minimizing redundant data (McFadden, Hoffer, & Prescott, 2000). This type of system allows data centralization and provides access to this data to different applications. Database technology is used in hierarchical modeling, knowledge refinement, machine learning, error analysis, knowledge representation, knowledge discovery, ontology, database design, knowledge reuse, knowledge repository, geosciences, and web applications (Liao, 2003, p. 6).

Modelling intends to build relationships based on logical model design for different domains of knowledge or problems. "Modeling technology can provide quantitative methods to analyze subjective data to represent or acquire human knowledge with inductive logic programming or algorithms so that artificial intelligence, cognitive science and other research fields could have broader platforms to implement technologies for KM development." (Liao, 2003, p. 6).