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

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.

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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,

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

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

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;

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.

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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

Participant

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

Telephone

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

Knowledge flow

<The topics of knowledge informed by the

participants.>

Knowledge in…

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

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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

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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

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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