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Knowledge Management - Tools

Information is the new currency in the world economy. We are in the age of knowledge, and this knowledge is a key asset for both organizations and society in general (Green, Liu, & Qi, 2009). In almost any setting, a person or organization needs a good tool set and great resources in order to achieve the goal of managing the knowledge being acquired or created. This is true even if it is as simple as pulling a paper and pen from a desk drawer. Still, when efficiency is being sought, effective and more efficient tools and resources must be sought as well.

For clarification purposes, it must be made clear that there is a stark difference between a tool and a resource. A tool is a specific thing being utilized in regard to the specific task undertaken. A resource on the other hand is a place to find the specific tool desired. It is not to say however that one cannot be the other or that either cannot be used cohesively when seeking a desired or specific result.


There is an ever increasing tool set in regard to KM (Knowledge Management). As a species, we have continued to add to our tool set since the dawn of civilization, and the realm of KM is no exception. The foundation of KM is built via tools that create synergistic relationships between the needs of the people and the organization (Beard, 2003). In either a professional or non-professional perspective, there are a few tools that stand out as exceptional.

Data Mining is a highly effective tool in many fields if employed properly. Data Mining is the process of collecting raw data and turning it into useful information. Actually, there are a few different types of mining: data mining, text mining (TM), and web mining (Zhang & Segall, 2010). Mining can be done numerous different ways but tends to be most effective when using computer software designed to seek out patterns inside of large batches of data.

Businesses can discover more about their customer’s habits and advertise more directly based on the customers wants and needs. This is often done via “loyalty cards” or discount cards provided by different commercial entities. Communication organizations such as Cox or AT&T could discover viewing patterns and play commercials that more in line with the interests of the customer, in turn making it more advantageous for the advertiser.

There are also some non-commercial aspects to be considered in regard to Data Mining. Certain organizations can track or learn more about an individual’s buying habits, personal habits, political leaning, affiliations, etc. These organizations could include government, security, law enforcement, and so on. However, it does not end there. Criminal organizations have the same capabilities.

Mashups are a great way to present information. In regard to web based applications, a blog for instance could integrate maps, Youtube videos, aggregate news sources, and so on into one seamlessly integrated application (Dalkir, 2013). These are extremely handy when dealing with complex issues or even when needing to provide reference materials in regard to a specific topic. Today, these types of mashups are doing so with a specific point of integrating social media.

Social Media is a great tool when it comes to both knowledge dissemination and retrieval. While some of the information is quite irrelevant in any regard, when something big occurs such as world event, people who utilize social media can spread information very rapidly and to almost any part of the world in a matter of minutes. Of course, social media has in many ways become its own “mashup”, and we are beginning to see integration between multiple formats becoming the standard.

Google + for instance, is now fully integrated with Youtube and you must have one in order to the have other. Both of these provide the option to integrate with Facebook, blogs, and so on. On a similar note, one of the more ignored benefits of social media is that an organization can utilize social media applications to get information from external sources into the organization (Vuori & Okkonen, 2012). Examples include competitor positions, trends, reviews, etc.


In all of the available KM resources, there are few that stand out as fulfilling multiple specified functions that are successful in producing a desired or intended result in regard to professional and even non-professional KM.

Websites in general are great resources in regard to KM. Depending on how a website is built and for what purpose it serves; a website can provide a plethora of resources within itself. There are evidently thousands of KM sites on the Web. Three of which have been identified as the mega portals for the topic of KM:; Knowledge Management Resource Center; and DM Review (Tulloch, 2003).

A website is nothing more than a location connected to the Internet that maintains one or more pages on the World Wide Web. So basically, this could include locations such as Deets Library or even Youtube, both of which are undisputable resources that include a vast amount of information on numerous specific topics.

More specifically, Blogs and Wikis are great place to locate information and are considered great resources according to Dalkir (2013). This can be due to any number of reasons but include the idea that the originator of the information can be provided and scrutinized in one location. Resources found by the originator are often provided by the originator within the text provided. Hence, these make great resources in regard to a specific set of data. On the other hand, blogs can also be applied as tools for knowledge management (KM) as well (Din, Norman, Kamarulzaman, Shah, Karim, Salleh, & Mastor, 2012).

As mentioned previously, Youtube is another great resource for numerous reasons. It retains and distributes videos that are uploaded by users from around the globe. It has integrated social media and general media to the point where if someone likes the information being provided, a simple click of the mouse can launch the video to that specific user’s entire list of connected users. Furthermore, the platform allows for users to take and integrate videos into their own websites and blogs, which only adds to the ability of information distribution.


There appears to be some confusion or differing beliefs in regard to the “tool versus resource” paradigm. For instance, Dalkir (2013) lists Youtube as a “Visual Resource”, while Makkonen, Siakas, & Vaidya, (2011) address Youtube as a Knowledge Management tool.

This should not take away from the power of either. While it is true that there is a stark difference between a tool and a resource, that difference tends to be based on the perspective of individual or organization using it, and how exactly it is being used. One can be the other and both can be used cohesively when seeking a desired or specific result, and both appear to create value.

In the end, “knowledge” itself is probably better defined as the resource being sought and anything being employed to gather or distribute it can be a tool and/or a resource as well.


Beard, R. (2003). Web alert: knowledge management. Quality In Primary Care, 11(2), 155-157.

Dalkir, K. (2011). Knowledge management in theory and practice. Cambridge, Mass: MIT Press.

Din, R., Norman, H., Kamarulzaman, M. F., Shah, P. M., Karim, A., Salleh, N. S. M., . . . Mastor, K. A. (2012). Creation of a knowledge society via the use of mobile blog: A model of integrated meaningful hybrid E-training. Asian Social Science, 8(16), 45-56. Retrieved from

Green, G., Liu, L., & Qi, B. (2009). Knowledge-based management information systems for the effective business performance of SMEs. Journal of International Technology and Information Management, 18(2), 201-222. Retrieved from

Makkonen, P., Siakas, K., & Vaidya, S. (2011). Teaching knowledge management by combining wikis and screen capture videos. Campus - Wide Information Systems, 28(5), 360-366. doi:

Tulloch, M. (2003). Knowledge Management on the Web. Journal Of Business & Finance Librarianship, 8(3/4), 213.

Vuori, V., & Okkonen, J. (2012). Refining information and knowledge by social media applications. VINE, 42(1), 117-128. doi:

Zhang, Q., & Segall, R. S. (2010). Review of data, text and web mining software. Kybernetes, 39(4), 625-655. doi:

David Robertson

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