Knowledge Management: The new challenge of the 21st century

This is my own reflection after studying in the “Gestion des connaissances” class, UOKM Winter 2017, with my modern, cosmopolitan and inquisitive professor, Pierre Levy

Parujee Akarasewi (Writer)


@plevy (Twitter) – University of Ottawa

Before I wrote this work, a memory of having to buy a new external drive last December at Best Buy popped into my mind. I honestly had ZERO knowledge about data and knowledge management at that time, and almost bought a 5Tb drive for my catalogue of 5,000 selfies. Seriously! Fortunately, at that time I was able to consult some IT-savvy friends to give me advice, complete with all the technical language and explanations that that left me without a clue as to what he was talking about. All I know is that 1 Tb is enough for my narcissistic collection of 5,000 selfies.


Once I started to take in the material of the Knowledge Management class with Professor Pierre Levy, I was exposed to many types and techniques of knowledge and data management on many platforms using many types of storage… I realized that we can save and manage data in more ways than just a USB flash drive or saving it to external storage.

In class, I learned to save, manage and share the knowledge that we have learnt during class through the class’s accounts using the #UOKM hashtag on the Twitter and Facebook social networks, complete with emojis, videos and links to articles. Frankly, this is a creative, intellectual way to use social networks, better than just clicking “Like”, and scrolling up and down to see pictures from friends.

My curiosity went into overdrive from the beginning of the class in January until the last class. I came to know that data curation is the key to Google’s management of massive quantities of data, “Big Data”, organized and put into different categories.

We cannot deny that we are all now in the Cyberspace Era, which has come into existence through multiple technologies. It requires collective intelligence and a community effort to help individuals towards a better and uniform understanding of new technologies like Bitcoin (a new E-currency for investments) and Blockchain (security for banks and money transfers) through well thought-out innovations in education, such as the use of social media, teach-back design, crowdsourcing, learning approaches through videogames, formative analysis, future learning, translanguaging, data journalism, open science, and so forth.

In fact, from what we learned in class, knowledge management, or KM, has many definitions: it is the whole process dealing with knowledge that is established in an organization in order to create, capture, manage, share and apply this knowledge in order to carry out the strategy to achieve the organization’s objectives; or the process of multi-disciplinary management by regrouping initiatives, methods and techniques that allow the perception, analysis, organization, addition to institutional memory and sharing of this knowledge by members of an organization. The knowledge can be the product of the organization itself, or learnt from external organizations in order to achieve its business goals.

At the organizational level, the behaviors, processes and technologies are filled in

  1. to allow personnel to understand each of these things individually and know how they apply to everyone, and
  2. see the big picture that applies to the entire organization, in order to be able to adjust, so that
  3. the organization can find out what they do not know and what they can apply for.


Humans can think, communicate and present things that are hard to present, but they can also create knowledge and, using symbols for better communication, transfer it from generation to generation.

Big Data

big data

 I used to contradict my father, telling him that mathematics are not important…

I have since come to realize that I was wrong, because mathematics now run the world. In order to manage the data at the foundation of knowledge, they have become the tools of statistics and analysis.

Imagine Big Data as a wizard: he must be a powerful and brilliant one. He can predict the future, identify phenomena, and create statistical models of the results. He can also identify causes for phenomena through statistical analysis and the application of the wonderful magic tricks of algorithms. This wizard will interpret all the data, and will always play an important role in verifying hypotheses and scientific models, and communicating the results to others. We cannot refuse this great wizard control over us in the cyberworld.

On the other hand, the advance of technology has been retarded in many companies: they have blindfolded themselves, which is why their evolution will inevitably be found to be lacking in enormous opportunities for the future, and even for the present.

None of this should scare us, because Big Data, with its statistics and algorithms, is still a million years from replacing the intelligence of human analysis, the experience of scientists, peer validation, the evolutionary comparison of data, etc.

In the book “Free Culture”, Lawrence Lessig defends “free culture” as freedom balanced with control. He sees culture as the growth of creativity when built upon permission when using the intellectual property of others.


He defines “piracy” in two ways: stealing for one’s own benefit, cutting into the income of creators; and striking a balance between the interests of IP owners and society to create a new business model. He makes a compelling case for the balance between owners and society so that we may have freely available culture that encourages new creation.

The author’s intention in making this book freely available and accessible to everyone was to create, to “kick start”, so to speak, a culture of freedom in copyright law so that tomorrow’s culture may grow without hindrance out of today’s.

When we take into account Big Data, though, the law might not be able to protect any intellectual creations in the cyber world, because of sharing and the wizard algorithms that I will explain in a later section.


Data Curation

This fancy expression is a new term and new method applied in modern technology and social media when saving data, information and knowledge. We can find old data, qualify it, and keep the right or favorite content for all time with tools like, Evernote, etc. We use hashtags and emoji to express our feelings toward the content we read. (For example, when I posted in the class Facebook page that I would be late due to the traffic my bus was facing, the professor commented on my post with an angry face emoji. That prodded me to run to class after I got off the bus, to try not to be that late. Ha-ha+) *** But please note: according to my KM-savvy Prof. Levy, Facebook, Twitter and other social media type are information platforms, not the sources of knowledge: the content that we post and repost is the real source. The more we share, the more data is stored on the platform, which is why those wizardly mathematical algorithms know what we like and keep sending us what we want to see on our page.

Data curation can manage all the data in the data schema through tags that categorize the data as a model. It comprises collective and artificial intelligence in order to make the data accessible and systematic.

Collective intelligence


Collective intelligence is intelligence distributed everywhere using everyone, constantly valued, and coordinated in real time, which results in an effective mobilization of skills, the aim being to channel knowledge to think together, according to the book that professor Levy assigned to me, “The Knowledge-creating Company” by our kind Japanese “grandpa”, Ikujiro Nonaka. In short, in this book I found that a person acquires implicit knowledge (procedural or understanding) through her efforts in research and development (R&D) for new product development.

Nonaka also stated that “organizational knowledge creation is like a ‘derivative’ of new product development.” Or in other words, knowledge is created in the interactions between frontline employees and so forth. This book helped me to realize that the next generation of wars will be fought with data, not harmful weapons. The more data we have, the more chance to win, as happened in the Japanese revolution.

Artificial intelligence



Finally, What is Artificial intelligence? Artificial intelligent is the simulation of human intelligence processes by computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction.

All in all, a semester tackling knowledge management with a scholar such as Professor Levy is tremendously valuable for my future professional and daily life. I hope my readers can learn as much as I have, and see the importance of knowledge management for the future, because the future war is a war of knowledge, not of weapons…





General ideas about the context of aviation work

The roles within the hierarchy of people in the aircraft are the captain as the commander of the plane, first-officer, flight engineer, purser as the head of the cabin crews, and other flight attendants, usually 2-4 based on the number of passengers. For example, if a flight has over 120 passengers, at least 3 cabin crew are required, including pursers. There are two different organizations dealing with different parts of the plane working together. The work of cockpit crew is mainly concerned with technical matters and the safety of lives, in contrast to the cabin crew team, which presents the image of the airline in terms of being well-versed in sociability and public service. Certainly gender dominance plays a part in the job roles along with the company’s class system: pilots are predominantly male, and cabin crews are predominately female.

Due to the realities of the situation, the captain, the co-pilot and all of the cabin crew have to be at the airport at least 3 hour before the flight’s boarding.

According to Rebecca D. Chute (1996), who researched the reason for the reluctance of flight attendants to come forward with information to the cockpit, there are four main factors which cause miscommunication between these workers and have a serious impact on emergency situations: cultural directives, status differential, past experiences of the flight attendants, and the ambiguity of the Federal aviation regulation (FAR) requiring all flight crews to go through CRM training sessions, which created a degree of submerged hostility and led to gripe sessions.

As for the roles of actual cockpit crews and cabin crews, the captain is the head manager for technical and safety matters, but the purser is the manager of the cabin crew, which serves commercial purposes related to the airline’s brand image.

The airplane used in this movie is the McDonnell Douglas MD-80, which can have 130-170 passengers on board, but is not designed for flying upside down like the Air Force’s much smaller fighter aircraft. This series of plane is well-known among airlines and pilots for being troublesome due to mechanical problems. As the movie illustrates to the audience, the weight of the passengers was not problematic in this incident; rather the accident in scene 4 happened due to a heavy storm and a mechanical failure. This movie is fiction based on a true story, and the production has a good general idea and put in good study about how work in real life aviation is really carried out, even if there are a few mistakes. This movie may be based on a true story, but there is the fact that the filmmaker forgot about the flight engineer: instead of having the purser help fly the plane and bring an end to the accident, it was the flight engineer who did that in the real situation, and the upside-down plane is not possible, because all commercial aircraft are not designed to spin or invert.





Chute, R. D., & Winter, E. L. (1996). Cockpit-Cabin Communication: II. Shall We Tell the Pilots? The International Journal of Aviation Psychology, 6(3), 211-231. doi:10.1207/s15327108ijap0603_1

Movie on project : Flight

*** This is an excerpt of my original work. I personally think that it is very important and very interesting for those who doubt or have the same interest as I do.

“Performing” in Mintzberg’s role


A description of the interpretive perspective: “performing” Mintzberg’s roles

The nature of managerial communication

Studying the nature of managerial roles focuses on the actual behavior of managers in daily activities. There are three general sets of roles of managerial behavior: interpersonal, informational and decisional roles.  Interpersonal roles link directly to the status and authority of a manager, roles such as a figurehead; informational roles are created to receive and transmit information; and decisional roles refer to the activities which have a critical impact on organizational decisions. The interpretive researcher concentrates significantly on the communicative process of organizational life to see how these three roles perform in the real world. The center of interpretive study is that communication is multifunctional: it is assumed that social construction makes reality, which is maintained and created by the communication process in the real world.

Managerial Performance

Life can be seen as stage management by viewing behavior as a performance. This metaphor helps us to understand the meaning of human behavior as a symbolic process with expressive and instrumental functions. As stated in Nick Trujillo (1989) regarding Victor Turner’s suggestion that many actions in many performances fulfill the different meanings of reality, “Performances are those very actions whereby individual reveal their cultural reality to themselves and to others”: the action begins after individuals reveal their cultural reality to themselves and others, and reconstruct the symbolic process by treating things as real. As Bruno Latour said, “Faire, c’est faire faire.” Reality is where the action happens.

Are performances interactional? As Nick Trujillo mentioned, “Managerial performances as communicative phenomena are always socially enacted by multiple participants” (Trujillo, 1989). Most organization are managed with hierarchical, leadership and decision-making systems along with the performance of management, thus managers are only the action parts of the organization.

Performance has two meanings: one is that, situationally or randomly, it is the inherent contextual nature of any communication event; and the other is that it is historically embedded, which means that it happens at a specific time in the ongoing current of events. Managerial performance involves mass action and meanings to introduce the importance of that current into the organization’s reality.

It is normal that managers lose their existent scripted lines because of standard procedures and routine work, for instance, the interactions stemming from multiple interpretations of interpersonal, informational and decisional performances — these factors want to make things harder when we think of managerial communication.

When we talk about interpersonal performance, hierarchy is the key factor for each member in defining their own roles and relationships within the organization under the rules and agreements for mutual recognition. Content and the aspect of linkage are in every message; their dimension of transferring the information which favors the aspect of relationship is known as the meta-communicative aspect.

The selectivity of hierarchies makes organizational relationships which can be selected and strategically called on at a particular time while maintaining a distance between higher and lower positions in the sense of interpersonal performances. Everyone in the organization is included as a part of each other’s conversation.



Trujillo, N. (1989). “Performing” Mintzberg’s roles: The nature of managerial communication. 1983, Beverly Hills: Sage. Communication and Organization: An Interpretative Approach, 73-97. doi:10.1177/017084068400500424

*** This is an excerpt of my original work. I personally think that it is very important and very interesting for those who doubt or have the same interest as I do.

*** This is only an excerpt of my original work. I personally think that it is very important and very interesting for those who doubt or have the same interest as I do.

La curation collaborative des données

Par Parujee Akarasewi,Mickey

À nos jours, on accumule des données sans les savoir à travers les plates-formes de médias sociaux et sur la masse d’applications de récolte des données spécialisées, par exemple, Evernote, etc. Les utilisateurs emploient les hashtags afin de les classifier et les commentaires et les emojis pour exprimer leurs émotions et faire référence à leurs données. De plus en plus la partage et les commentaires de ces affiches deviennent des données eux-mêmes alors les médias sociaux nous proposent des algorithmes de fouille, d’apprentissage machine, de reconnaissance de forme et de filtrage collaboratif qui nous aident à gérer le déluge du contenu et les hordes d’utilisateurs. Pourtant l’alimentation de la base de même que la catégorisation et l’évaluation des données sont encore contrôlés par les utilisateurs. La curation veut dire le souci des données que nous devons gérer et accumuler. Sa seule raison d’être est de produire et de partager les informations de façon significative.

L’auteur nous invite à contempler les sphères d’activité où la curation des données s’exige en tant qu’outil indispensable, telles que la conservation des héritages, la recherche en sciences humaines, l’apprentissage collaboratif, la production et la diffusion des nouvelles, le renseignement à sources ouvertes et la gestion des connaissances.


Extrait :

La curation collaborative de données