Knowledge Mapping in a Research and Development Group
A Pilot Study
Erivan Souza da Silva Filho, Davi Viana, Jacilane Rabelo and Tayana Conte
USES Research Group, Instituto de Computação, Universidade Federal do Amazonas, Manaus, Brazil
Keywords: Knowledge Management, Knowledge Mapping, Knowledge Map.
Abstract: In Enterprise Systems, representing the flow of knowledge may indicate how participants work using their
knowledge. Such representation allows the understanding of how knowledge circulates between the
development team and improvement opportunities. Knowledge Management supports the management of
knowledge through techniques that identify how knowledge behaves in projects. One of these techniques is
Knowledge Mapping, which supports representing how participants share their knowledge, which sources
of knowledge are consulted and which people it helps during a project. However, to draw up a knowledge
map, we need a process for capturing and analyzing data that can extract information that reflect these
aspects. This work aims at presenting a process for Knowledge Mapping to develop a map indicating what
knowledge the participants used, who or what they accessed and indications of its core competencies.
Additionally, this paper discusses a pilot study regarding the application of the proposed process. As a
result, we generated a knowledge map for a software engineering research and development group, in which
contains a set of profiles and features what the main skills that a participant uses are.
1 INTRODUCTION
The main asset of Software Companies is
knowledge. Thus, it is necessary to manage this
knowledge and use their experiences in development
activities (Hansen and Kautz, 2004). In any
industrial or academic environment, there are people
who have knowledge, and it may be of interest to
promote such knowledge management (Krbálek and
Vacek, 2011).
Knowledge management is the process of
creating, validating, representing, distributing and
applying knowledge (Bhatt, 2001). Knowledge
management also refers to identifying and increasing
the collective knowledge in an organization to help
it become more competitive (Alavi and Leidner,
2001).
The goal of these efforts is to provide members
of the organization with the knowledge they need to
maximize their effectiveness, thus improving the
efficiency of the organization (Mitchell and Seaman,
2011). The environment or territory in the context of
knowledge management is not geographical, but
intellectual (Eppler, 2001), where we need
techniques that seek to represent the main aspects of
that environment.
One of the techniques in Knowledge
Management that seeks to represent these aspects is
Knowledge Mapping. Knowledge mapping is a
process of surveying, assessing and linking the
information, knowledge, competencies and
proficiencies held by individuals and groups within
an organization (Anandarajan and Akhilesh, 2012).
The result of a mapping is a Knowledge Map
that shows the relationships among the procedures,
concepts and skills, which provides easy and
effective access to sources of knowledge (Balaid et
al., 2013). The main purpose and benefit of a
knowledge map are to show people from within the
company where to go when they need knowledge
(Davenport and Prusak, 1998).
This paper presents a process of knowledge
mapping that aims at representing the flow of the
employees’ knowledge within software
organizations. We combined some approaches in
order to create such process. This paper also
describes the results of a pilot study in which the
proposed process was applied in a Research and
Development (R&D) group.
The remainder of this paper is organized as
follows. Section 2 presents our theoretical reference.
Section 3 presents the developed knowledge
mapping process. Section 4 shows planning process
306
Filho, E., Viana, D., Rabelo, J. and Conte, T.
Knowledge Mapping in a Research and Development Group - A Pilot Study.
In Proceedings of the 18th International Conference on Enterprise Information Systems (ICEIS 2016) - Volume 1, pages 306-317
ISBN: 978-989-758-187-8
Copyright
c
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
of the pilot study. Section 5 discusses the results
obtained in the pilot study. Finally, Section 6
presents our conclusions and future work.
2 THEORETICAL REFERENCE
Individual knowledge is necessary for the
development of knowledge within an organization
(Bhatt, 2001). Knowledge within an organization is
a collection of knowledge, experiences and
information which people or groups employ to carry
out their tasks (Vasconcelos et al., 2005). This
section shows the theoretical reference and the main
concepts for this work.
2.1 Knowledge Management
Human resources are the main assets of many
companies where knowledge has to be preserved and
passed from the individual to the organizational
level, enabling continuous improvement and
learning (Lindvall et al., 2003). Companies
generally understand Knowledge as how information
is encoded with a high proportion of human value-
added, including perception, interpretation, context,
experience, wisdom, and so on (Davenport and
Völpel, 2001).
Davenport and Prusak (1998) made a distinction
between data and information. Data is a group of
distinct facts and goals related to events. Information
aims at changing the way in which the receiver
perceives something, exercising some impact on
his/her judgment and behavior.
Nonaka and Takeuchi (1995) states that
knowledge, unlike information, is about beliefs and
commitment, and characterize it into two types:
explicit and tacit. Explicit or codified knowledge can
be articulated in formal or textual language. Tacit
knowledge is the personal knowledge, incorporated
to the individual experience, and that involves
intangible factors (e.g. personal beliefs, perspectives
and value systems).
Knowledge Management is a method that
simplifies the process of sharing, distributing,
creating and comprehending a company's knowledge
(Bjørnson and Dingsøyr, 2008). Its goal is to solve
problems regarding the identification, localization
and usage of knowledge (Rus and Lindvall, 2002).
A prerequisite for the strengthening of
knowledge management is a good understanding of
how knowledge flows within the organization
(Hansen and Kautz, 2004). The identification of the
knowledge flow shows us the way on which new
concepts and ideas are spread, which can be useful
to facilitate changes in management initiatives
(Gourova et al., 2012). One of the applied
techniques for searching and defining organizational
knowledge flow is knowledge mapping.
2.2 Knowledge Mapping
Knowledge mapping is a process, method, or tool
made for analyzing knowledge in order to discover
characteristics or meanings, and view knowledge in
a comprehensible and transparent manner (Jafari et
al., 2009). The purpose of knowledge mapping is to
seek a better orientation in a given domain and
access knowledge from the right people at the right
time (Krbálek and Vacek, 2011).
One of the advantages of knowledge mapping
includes the freedom to organize without restriction,
meaning that there are no limits to the number of
ideas and connections that can be made (Nada et al.,
2009). Knowledge mapping usually takes part of
Knowledge Audit processes and methodologies.
Elias et al. (2010) define Knowledge Audit (KA)
as the identification, analysis and evaluation of the
activities, processes and practices for managing the
knowledge that a company already has.
Knowledge Audit is used to provide an
investigation into the organization's knowledge
about the health of knowledge (Elias et al., 2010),
identifying and understanding the knowledge needs
in organizational processes.
Meanwhile, by using Knowledge Mapping
techniques would show a logical structure of
relationships between tacit human knowledge and
explicit knowledge in documents (Krbálek and
Vacek, 2011). The result of knowledge mapping is a
knowledge map.
2.3 Knowledge Map
Knowledge Map is a diagram that can represent
words, ideas, tasks, or other items linked to and
arranged in radial order around a central key word or
idea (Nada et al., 2009). Furthermore, it is an
interactive and open representation that organizes
and builds structures and procedural knowledge used
in the pursuit of exploration and problem solving
(Anandarajan and Akhilesh, 2012).
Knowledge maps also provide a holistic view of
knowledge resources (Balaid et al., 2013). Eppler
(2001) distinguishes five types of Knowledge Maps,
shown in Table 1. The five maps can be combined to
generate new mapping techniques.
Knowledge Mapping in a Research and Development Group - A Pilot Study
307
Table 1: Types of Knowledge Maps (Eppler, 2001).
Name Description
Knowledge
Source Maps
These are maps that structure a population
of experts from a company through search
criteria, such as their knowledge domain,
p
roximity, length of service or geographical
distribution.
Knowledge
Asset Maps
This type of map visually describes the
storage of knowledge of a person, a group,
a unit or an organization.
Knowledge
Structure
Maps
It is the overall architecture of a knowledge
domain and shows how parts relate to each
other. It assists managers in understanding
and interpreting a specialized field.
Knowledge
Application
Maps
It shows what kind of knowledge must be
applied at certain stages of the design
p
rocess or in a specific business situation. It
answers the question of which people are
involved in an intensive knowledge
process, such as auditing, consulting,
research or product development.
Knowledge
Development
Maps
These maps can serve as development
p
athways or visual learning which provide
a common corporate vision for
organizational learning.
2.4 Related Work
There are different techniques to map organizational
knowledge, and each technique can use a set of
tools, approaches, objectives and specific
characteristics (Jafari et al., 2009). In the following
paragraphs, we show the main works that served as
the theoretical basis for our mapping proposal.
Hansen and Krautz (2004) proposed using Rich
Pictures (mechanism that uses pictograms for
representation) as a technique to map the flow of
organizational knowledge. The methodology
consists of two large main stages: preparation phase
and mapping phase.
Preparation Phase: Based on the collected
data, (s)he created an initial map of the
organization.
Mapping phase: It results in a knowledge map
that describes actors and knowledge flow, as
well as key features of the organization.
Hwang and Kim (2003) defined that a map is
composed of two main components: diagrams that
are graphical representations of components; and
specifications, which are descriptions of the
components. The authors also suggested creating a
profile of the extracted knowledge, establishing a
structure representing the characteristics of the
mapped knowledge.
According to Kim and Hwang (2003),
knowledge maps should achieve:
1. Formalization of all the knowledge
inventories in the organization;
2. Perception of the relationship between
knowledge;
3. Efficient Navigation of knowledge
inventories;
4. Promotion of socialization/outsourcing of
knowledge by connecting the experts’
domains with knowledge explorers.
Eppler (2001) has developed five steps that must
be performed to design and build a Knowledge Map.
These are:
1st. Step: To identify the knowledge-intensive
processes, problems or issues within the
organization. The resulting map should focus
on improving the intensive knowledge.
2nd. Step: To deduce the sources of knowledge,
assets or relevant process elements or
problems.
3rd. Step: To codify these elements in a way that
it makes them more accessible to the
organization.
4th. Step: To integrate this codified knowledge or
documents information in a visual interface
that allows the user to navigate or search for
it.
5th. Step: To provide means for updating the
Knowledge Map. A Knowledge Map is as
good as the links it provides. If these links
are outdated or obsolete, the map is useless.
The mapping techniques found in the literature
show some approaches focusing on the flow of
knowledge within the organization and the definition
of knowledge sources. However, improved
techniques may be applied to represent participants’
knowledge based on knowledge flow.
Finally, Elias et al. (2007) proposed a
methodology to identify and analyze knowledge
flows in work processes. Such stages are:
1. To identify the main documents and people
involved in the process;
2. To analyze the knowledge sources identified
in the first step;
3.
To identify how the knowledge and sources
are involved in the activities performed in the
process;
4. To analyze to find the problems that could be
affecting knowledge flows identified.
The purpose of this paper is to integrate and
improve these previous methods and generate a set
of profiles of the participants in a software project
team. From the data of these profiles, we can verify
what is the most used knowledge by participants.
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3 PROCESS OF KNOWLEDGE
MAPPING IN SOFTWARE
TEAMS
Our Process of Knowledge Mapping is mainly based
on the work of Hansen and Kautz (2004), since their
method allows enhancements or modifications.
Furthermore, the work by Kim and Hwang (2003)
contributes to the profiling strategy and the work by
Eppler (2001) contributes to the definition of the
steps to build the knowledge maps.
The main objective of the map is to find the core
competencies of the participants based on their
interaction with other team members and with
sources of knowledge. The procedure of the
Knowledge mapping consists of two phases:
Data Collection Phase: The data that will
compose the Knowledge Map will be
collected. The collected data can come from
two sources in the organization: the project or
organization. Regardless of the origin, this
phase will organize the data that will be
employed to build a map of the structure;
Mapping Phase: It is the organization of the
data and the construction of the Knowledge
Map. According to Table 1, the produced map
is classified as a Knowledge Source Map,
showing the sources of explicit (websites,
books or documents) and tacit (participants)
knowledge. Moreover, a profile for each
participant will be produced, indicating
his/her main accessed knowledge.
The moderator of the Knowledge Mapping
Process can play many roles such as facilitator
(during the data collection phase) or map developer
(during the mapping stage).
3.1 Data Collection Phase
The purpose of the data collection phase is to extract
the necessary information to create the
Knowledge Map, as shown in Figure 1.
Figure 1: Activities of the data collection stage from the
Knowledge Mapping process.
1. The Mapping Guide is a presentation showing
the participants which activities they will do
during the meeting. The purpose of the
presentation is to support the facilitator of the
meeting and present a practical visual guide
to participants;
2. We apply the questionnaire to the participants
who will create the Knowledge Map;
3. Analyzing Artifacts. The purpose of this
activity is to see how organizations or group
view the participants and to triangulate the
facts with the questionnaire information.
We describe these activities in the following
subsections.
3.1.1 Presentation of the Mapping Guide
The Mapping Guide should be presented to the
participants of the meeting before the questionnaire.
The structure of the presentation follows the
following steps:
Presentation of the Facilitator and his role for
the group;
Explanation of what is tacit and explicit
knowledge;
Brief explanation of Knowledge Management
(optional);
Brief explanation of what is Knowledge
Mapping (if this is the first mapping);
Presentation of the questionnaire structure;
Presentation of the activity guides to the
participants;
Presentation of the questions on Knowledge
Mapping.
Knowing the question of the knowledge mapping
helps us to focus on the knowledge that we want and
to capture accurate information, aiming to avoid
extracting information that has nothing to do with
the knowledge we demand.
3.1.2 Knowledge Mapping Questionnaire
The Knowledge Mapping questionnaire has a logical
structure that seeks to find three aspects: what
activities the participant exerted during the
execution of the project, what or who (s)he
researched to acquire knowledge and who (s)he
helped.
Participants must be left free to consult each
other, and they must have available resources to
consult when they have questions while filling out
the questionnaire. The reason for using these
resources is that some people may not be able to
remember some relevant information.
Knowledge Mapping in a Research and Development Group - A Pilot Study
309
The first part of the Knowledge Mapping survey
(see Figure 2) is related to the Applied Topic of
knowledge of the activities (s)he carried out. The
purpose of this information is to know what
knowledge (s)he applied.
Figure 2: Field to describe which activities were
conducted.
The field in Figure 3 is related to Who /What
(s)he consulted to carry out his/her activities. The
participant may indicate if (s)he consulted a person
or an artifact and they should describe the name of
the consulted person or artifact in the "Name of
Person or Artifact" field. Then s/he must
complement with a brief description regarding what
was consulted. Some fields present different sizes
because it might be possible that the participant has
more than one consult to a device or person.
Figure 3: Field to describe the consults that were
performed.
Finally, the participant must inform in the field
shown in Figure 4 Which people (s)he helped
during his/her activities. Based on this and the
previous field, we can triangulate the information
aiming to find the flow of knowledge among
participants and to know what kind of knowledge
takes place among them.
Figure 4: Field where the participant informs who (s)he
helped.
3.1.3 Artifact Analysis
The artifact analysis is defined as the analysis of
information from project-related documents that
may be potential sources of knowledge. Its purpose
is to explicit knowledge sources that will integrate
the knowledge map.
3.2 Mapping Phase
The mapping phase will analyze the collected data in
the data collection phase and will generate the
knowledge map of the project team. Initially, we
organize all the collected data on a table, as shown
in Figure 5. Then, we produce the representation of
the knowledge map sources (either by using physical
materials with a whiteboard or through digital tools).
Finally, we will generate the profile of each
participant.
Figure 5: Activities from the Knowledge Mapping Phase.
3.2.1 Organizing the Data Matrix
Mapping questionnaires are analyzed at this stage
and the moderator, who is implementing the
Knowledge Mapping process, should examine each
of them as (s)he carries out the parallel activities of
this phase.
In the actors-artifacts relationship (where the
actors are the participants), we organize all the data
in a table following the format in Table 2. In the
horizontal lines, we insert all the names of the
project participants that have been mentioned in the
fields "who you consulted" and "who you helped"
from the questionnaires.
Table 2: Structure of Actors-Artifact in the Data Matrix.
Actors Participant
1
Participant
N
Artifacts Artifact 1
(Type)
Participant 1 Id 1 Id 2
Participant N
The columns are filled with the same name of the
participants defined horizontally. After dividing the
"artifacts", we can enter the names of the mentioned
artifacts by any participant within the questionnaires.
While reading what artifacts were mentioned by
the participants in the questionnaire, we should
avoid duplication and then generalize when two
participants refer to the same artifact. For example,
two participants can mention the Stackoverflow
online forum of questions and answers differently,
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where one says "Search Stackoverflow forum"
while another says "stackoverflow.com". Both
participants refer to the same artifact, the
Stackoverflow forum, so we will not insert two
different columns for it. Instead, we can name the
same column as "Stackoverflow (website)", where
the parentheses in keyword help identifying what
this artifact is.
After finishing to fill out the table, the cells are
filled with an identifier of the description of the
consulted information by the participant. For this,
we will use a table for supporting where we will
store the consult description gathered in the fields
"who you consulted" and "who you helped" from the
questionnaires. It is exemplified in Table 3.
Table 3: Structure to assist description of relationships.
Id Relationship description Participant
1 Description of Id 1 Participant 1
2 Description of Id 2 Participant 2
Finally, we have the name of the participants
horizontally, while what they accessed (whether it is
other participants or artifacts) is shown vertically.
3.2.2 Generating Representations in Map
The representation on the map can be done by a
support tool which must have the following
characteristics:
Change colors or pictures of the node;
Create edges between nodes;
Assign weights and Text on the edges;
Assign texts to the nodes.
After choosing the tool to be used, the activities
of the process of knowledge mapping creation are
initiated.
Based on the Data Matrix information built in the
previous activity, we will perform the following
steps to build the map:
1. Write what project members are;
2. Write what the artifacts informed by the
participant are;
3. Center map members and leave the artifacts at
the edges;
4. Insert an edge between nodes, namely
between a member and an artifact, or between
members;
5. Assign which or what are the relationships
from such edge, based on the auxiliary table
of the Data Matrix called Relationship
Description;
6. Repeat from step 4 until all edges are created;
7. Document the map and its version.
After that, it is estimated that this map shows
which members consult others and about what, and
what artifacts are found during a project. It is
recommended the review of the map by a second
person in order to avoid omissions or errors.
3.2.3 Generating Participants’ Profile
The profile of the participants is a representation
indicating what skills or competencies (s)he is
applying. They reference not only what (s)he
informs, but what other participants inform. The
map should also show how we can find him/her,
what knowledge (s)he masters, what his/her sources
of knowledge are and with whom (s)he
communicates.
To generate the participant's profile, we will use
the Data Matrix information, the analysis of the
artifacts and the Knowledge Map as basis looking
for:
What are the main topics of knowledge (s)he
employed in his/her activities?;
What sources of knowledge does (s)he use?;
What people has (s)he worked with or had
some knowledge flow?.
This information will fill the items about the
participant's profile in Table 4.
Table 4: Participant Profile structure.
Participant Name
<The full name entered by the
participant.>
Position or Role
<Position or role of participant.>
Email
<Participant contact E-mail.>
Telephone
<Participant contact number.>
Keywords of major skills
<Keywords that describe he/she skills. The keywords
are the codes identified below.>
Knowledge sources
<What sources of explicit knowledge he/she consult
based on the knowledge map.>
People whom (s)he is related in the map
<Which people the participant has a knowledge transfer
based on knowledge map.>
Worked projects within the Group
<Project works within the research group.>
Knowledge flow
<The topics of knowledge informed by the
participants.>
Knowledge in…
<Knowledge flow code.> <Full description of flow.>
The fields Name, E-mail, Position or Role, and
Telephone are extracted from the information
previously collected. The information from the
Knowledge Sources field will be collected analyzing
Knowledge Mapping in a Research and Development Group - A Pilot Study
311
the data matrix based on the columns of the artifacts
that the user entered. As shown in Figure 6, we use
the participant's line and check the column of the
artifacts used by him/her. This will be the
information that will compose the field.
The people to whom (s)he is related in the
map field will consist of all participants and people
outside the project with whom the participant had
any knowledge flow. In addition to identifying the
participants, we assign weights according to the total
sum of the flows between two participants, as seen
in Figure 7.
Figure 6: Capturing information about artifacts used by a
participant.
Figure 7: How to identify people connected to a
participant.
Regarding the Worked projects within the
Group field, this information will be extracted
based on the analysis of the artifacts. In case that
there is no identification, the field is filled with
“None identified”.
The Participant Knowledge Topics is the
information that participants provided in the
knowledge topic field of carried out activities in the
questionnaire research, Subsection 3.1.2. After
entering the information, we will generate codes for
what was inserted. In addition, two descriptions may
belong to the same code and thus increase the weight
of this information, as seen in Table 5.
Knowledge flow will be the cross analysis of the
Data Matrix for each participant (see Figure 8). The
reason is that while the row shows just what the
participant said, the column complements what
others have reported about him/her. The Id
(identifier) and his name should be placed in
sequence in the field to be codified in the future.
Table 5: Knowledge topics of a participant.
Participant Knowledge Topics
Review of material on Molic interaction modeling;
Mockups together with Molic (diagrams);
Case studies;
Defects inspection;
Inspection techniques for Molic diagrams;
TAM (Technological Acceptance Model).
Molic (3)
Review of material on Molic
interaction modeling;
Mockups together with Molic
(diagrams);
Inspection techniques for
Molic diagrams.
TAM (1)
TAM (Technological Acceptance
Model.
Case studies (1)
Case studies.
Defects inspection
(1)
Defects inspection.
Figure 8: Way to capture the flow of knowledge from one
participant.
After entering all the flows belonging to the
participant, we will code with words that identify a
concept or represent these flows (see Figure 9). The
Knowledge in … field will be composed of all the
coding of flows. Some encodings may have more
than one flow, and the flow may belong to more than
one coding.
Figure 9: Analysis and codification of knowledge flows.
It is recommended the execution of codification
by someone with knowledge of the organizational
culture. Thus, the creation of codes is closer to
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reflect the reality of the organization.
4 PILOT STUDY IN A RESEARCH
AND DEVELOPMENT GROUP
The focus of the pilot study is to conduct a
feasibility study of the Knowledge Mapping process.
The primary purpose of a feasibility study is not to
find a definitive answer, but to create a body of
knowledge about the application of the technology
(Mafra et al., 2006).
As a result, we gain knowledge regarding if the
process we are developing is feasible, if it produces
a consistent result while identifying its limitations
which, according to Shull et al. (2004), allows:
The refinement of technology;
The generation of new hypotheses on the
application (in this case, the process of
Knowledge Mapping) to be investigated in
future studies.
The pilot study was applied in a software
engineering and usability research group, which is
formed by six Ph.D. candidates and four master
students working on research and development in
the areas of Software Engineering and Human-
Computer Interaction. Thus, there are
representatives of the population and, because it is a
pilot study, we sought first to carry out the study
within the research group and then evaluate in an
industrial environment. The focus of the knowledge
map was to find information related to types of
knowledge that participants had applied or were
applying in their research or in R & D (Research and
Development) projects.
4.1 The Steps of the Pilot Study
The pilot study followed three steps detailed below.
1. Preparation: Contains the pilot study design,
the creation of instruments and training of
possible applicators of activity of Data
Collection;
2. Implementation: The group in which the
proposed technology would be applied
attends a meeting in order to collect data. In
this case, the Knowledge Mapping process;
3. Analysis and generation of results: The
collected information will go through the data
analysis of the Knowledge Mapping process.
By running the pilot study, we can verify the
main aspects required for the application of the
proposed technology (the process of mapping of
knowledge) and analyze its limitations to evolve it in
the future.
4.2 Preparation
In this phase, we plan and prepare all the
instrumentation and contact the people that are
necessary for the implementation of the Knowledge
Mapping process. The main purpose of the
preparation is to address threats to validity. Based on
the recommendations by Wohlin et al. (2012), the
following threats were addressed:
Internal Validity (Instrumentation): This is the
effect caused by the artifacts used in the execution of
the experiment. In the case of a poorly-planned
experiment, its results will be negatively affected.
Thus, a second researcher reviewed the artifacts
created by the author process.
Construct Validity (Expected Experimenter):
The author of the knowledge mapping process can
consciously or unconsciously cause bias in the
results of a study based on what (s)he expects the
results of the experiment will be. When
implementing the experiment, we asked another
researcher with no involvement in this research to
apply the process. However, in the analysis phase
and the generation of results, the author of the
process performed the analysis.
External Validity (Interaction of Participants
and Treatment): It occurs when a sample does not
represent the population we want to generalize. The
focus of the process is to map software project
teams. We chose a research group and R & D
(Research and Development) projects due to
convenience and the similarity of their themes and
situations.
4.2.1 Instrumentation
For the pilot study, the following instruments that
supported the whole process were developed:
Approach Manual: a Knowledge Mapping
process manual was prepared explaining step by step
how to apply and generate a knowledge map, how to
collect data, which tools to use and what the end
products of the process would be.
Knowledge Mapping Questionnaire: a
questionnaire that aims to capture key information
needed to generate the knowledge map and profiles
of the participants.
Presentation of the Mapping Guide: a
presentation guide that supports the moderator when
applying the questionnaire and participants during
the data collection. The presentation consists of 12
Knowledge Mapping in a Research and Development Group - A Pilot Study
313
slides that show the objectives of the data collection,
the structure of the questionnaire and a behavior
guide for participants to follow during the session.
4.2.2 Guest Researcher
A researcher with no relation to the research was
asked to administer the questionnaire to the
participants. At a meeting, the author of the proposal
presented the research objectives, the guide of the
approach and the tools (questionnaire and
presentation) for the guest researcher.
Additionally, we collected suggestions from the
invited researcher to better conduct the experiment,
which allowed gathering initial feedback for the
improvement of the technical instrumentation. After
the transfer of information, the execution of the
study was scheduled with the group of participants.
4.3 Execution
Execution is the application of knowledge mapping
questionnaire with the participants that will create
the knowledge map. The questionnaire was printed
and distributed to participants with no time limit to
fill it out, and we allowed the interaction among
them. The guest researcher assumed the role of
facilitator, which sought to conduct all data
collection and answer questions from the
participants.
The participants took around thirty minutes to
answer the questionnaire. The author of the proposal
was absent during the execution process of the data
collection in order to avoid any bias in the pilot
study. After finishing the execution, the data was
delivered to the author of the process for analysis.
4.4 Analysis and Generating Results
We explain the performed data analysis in this
section. The results are related to the knowledge
map of the team and the profiles of participants. For
the execution of this phase, we did not invite another
researcher, because the process needed a closer
analysis from the authors of the proposal.
At this stage, all the Knowledge Mapping phase
must have been executed, as described in Subsection
3.2, for the activities of Organizing Data Matrix
and Generating Representation in Map.
For the Generating Participant´s Profile
activity, which is the analysis and creation of all
profiles, there is no reliable estimate to be informed
due to the improvement of the technique while
performing the activity. We explain the results of
this pilot study in the following section.
5 RESULTS
This section presents the results of the
implementation of the Knowledge Mapping process.
In addition, lessons learned and results of the
implementation of the knowledge mapping process
are presented.
5.1 Knowledge Mapping Results
As presented in Section 4.3, in the execution of the
study, we employed a printed questionnaire
(subsection 3.1.2) with ten participants in an R & D
(Research and Development) group. Ten
questionnaires were analyzed in the mapping stage.
A spreadsheet was used to support the creation of
the Data Matrix.
For the matrix, two tabs have been created. The
first one shows the connections between participants
with participants or artifacts, as described in
Subsection 3.2.1. A sample result can be seen in
Figure 10.
Figure 10: First tab of the Data Matrix.
The second tab stores the description Ids
generated in each cell. Moreover, it stores the
participant's name and if the data is going in or out
Figure 11).
Figure 11: Second tab of the Data Matrix.
Then, we generated the graphical representation
of the Knowledge Map based on the steps described
in Subsection 3.2.2. We applied the NetMiner 4.2.1
tool due to its ease of use. The generated result can
be seen in Figure 12.
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314
Figure 12: Group map generated by NetMiner (available
at: http://www.netminer.com/).
The map elements were created based on the
Data Matrix. As recommended in the approach’s
manual, participants were centralized on the map
and indicated people or artifacts were allocated at
the edges of the map.
Knowledge maps can provide a set of knowledge
sources and flows. In addition, managers can use
this information for decision-making. However, it is
important to carry out a systematic analysis of such
knowledge maps to reveal relevant insights of the
organization (Chan and Liebowitz, 2005).
Consequently, we applied Social Network Analysis
(SNA) to systematically investigate some aspects of
knowledge flow depicted by the knowledge maps.
In the map, we identified two central connectors.
The central connectors are people with whom other
participants interact more (Cross and Prusak, 2002),
they are the participants from 3 to 10 (green circle
with a blue border in Figure 14). Participant 5 is
classified as Border Key (Cross and Prusak, 2002),
which communicates with more people outside the
network and serves as an ambassador between the
network’s internal and external knowledge.
We can check the level of reciprocity that is the
similarity between the entries of two participants
(Tichy et al., 1979). The strongest connections are
between the participants 1 and 3, followed by the
participants 9 and 10.
Additionally, we can analyze that Participant 8
behaves like a person with the most access to
artifacts (Red border in Figure 14). Moreover,
Participant 5 (Orange border in Figure 14) is the
person who consults the higher number of people
within the network, which may be an indicator that
(s)he had the current highest level of learning.
After creating the knowledge map graphically
and in the matrix, we analyzed and generated the
profiles of the participants based on the steps of
Subsection 3.2.3. We define the key words that
represent the main competences of each participant
and using such information, we identified his/her
and the group’s main knowledge. Table 6 presents a
profile created for one of the participants.
Table 6: Profile from a participant.
Participant Name
Participant 10
Position or Role
PhD student
Email
XXX
Telephone
XXX
Keywords of major skills
Systematic Literature Review (6),
Paper Writing (4), Statistical Analysis (3)
Usability (3) Pilot Study (3),
Modeling themes (3), Review proposal (3).
Knowledge sources
ACM;
Scopus;
Ieee;
Books of HCI.
People whom (s)he is related in the map
Participant 9 < Weight 7>
Participant 6 < Weight 7>
Participant 4 < Weight 4>
Participant 3 < Weight 4>
Participant 3 < Weight 3>
Participant 5 < Weight 3>
Participant 2 < Weight 2>
Participant 1 < Weight 2>
Worked projects within the Group
None Identified
Finally, we produced the two main products of the
Knowledge Mapping process: the group's knowledge
map and a set of profiles for each participant.
Group leaders received the data for analysis and
assessment. Moreover, the analysis of the participants,
based on the maps and in the matrix, includes: who
accessed other participants, who accessed more
artifacts, which participants had the strongest
connection (edges or knowledge flow) and what the
strongest knowledge domain of the group was.
5.2 Lessons Learned of the Knowledge
Mapping Process
We requested the participants to answer the
questionnaires based on the main question of the
mapping. Thus, the questionnaire words and
Knowledge Mapping in a Research and Development Group - A Pilot Study
315
examples should be according to the defined
mapping question.
The participants must be free to communicate
with each other, so that they can easily retrieve
information when filling out the questionnaires.
Research on books, websites or document names
should be allowed for a richer filling of the
questionnaire.
During the mapping step, the matrix was
modified based on the original idea with respect to
the field describing the relations. A column with the
name of the participants was inserted to provide a
better way of identifying who owned that description
in a bigger data set.
Once completing the knowledge map, we started
the creation of the profiles from the participants. In
the beginning, the first version of the proposed
structure did not work to generate the profile of the
participants. This was due to the lack of a review
process of the results for filling fields correctly.
Improvements in the participants' profile form
were: 1) The structure has been redesigned to
display necessary information from each participant
profile. 2) A knowledge technique for identifying
the applied knowledge of the participants was
defined to analyze the flow of knowledge among the
participants. 3) The steps of the analysis and profile
creation activities have been rewritten. The main
goal for such change is that others can properly
apply the process without help or interference of the
authors of the process.
6 CONCLUSIONS AND FUTURE
WORK
The Knowledge Mapping process presented in this
paper maps a group of participants and creates
profiles for each participant. In addition, we carried
out a pilot study where it was found that this process
is feasible.
Each profile displays, besides basic information
on how to find the participant in the organization,
with whom (s)he is connected to on the map and
what activities (s)he performs. The profile also
displays indicators of the main competences (s)he is
carrying out in the group using information that
other participants employ from him/her.
The executed knowledge mapping process within
the study produced a map where one can check
which connections a participant has with each
knowledge source, either being explicit (websites,
books, and so on) or tacit (access to people). Also, it
is possible to check on each edge which knowledge
is flowing.
The advantages found to justify the creation of a
knowledge map in the study are:
To check what main competences a
participant is in fact executing. Based on this,
we can verify if (s)he is applying something
for which (s)he was designed or if there are
any mistakes in the execution of his/her
activities;
To check for anomalies in the knowledge
flow of a participant. Perhaps a participant is
requiring a source of knowledge that does not
fit into his/her roles. It can mean a learning
signal or irregularity;
To check if the flow of information between
members is happening. In an integrated team,
we can see through a map if two members are
or not interacting when they should be. For
example, the analyst responsible for gathering
requirement and the developer;
To identify the current knowledge in a group
or software team. Based on the identified
keywords within the profiles, we can draw
conclusions from what knowledge the group
or team is employing and which have high
scores.
Finally, as future work, we intend to:
Apply the Knowledge Mapping Process in a
Case Study with software projects teams;
Automate the data analysis process and the
creation of profiles;
Compare Knowledge Mapping with network
analysis techniques such as Social Network
Analysis;
Apply the Knowledge Mapping Process in a
Knowledge Audit Process as Elias et al.
(2010).
ACKNOWLEDGEMENTS
We would like to thank the support granted by
CAPES; by FAPEAM through processes:
062.00600/2014; 062.00578/2014 and by CAPES
process AEX 10932/14-3. We would like to thank
all the subjects who participated in this study.
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