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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>ReCredible: Topic Maps for Knowledge Management and E- learning</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Laura Kamandulytė-Merfeldienė</string-name>
          <email>laura@recredible.com</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Rytis Maskeliūnas</string-name>
          <email>rytis@recredible.com</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Vaidas Repečka</string-name>
          <email>vaidas@recredible.com</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Kaunas University of Technology recredible.com</institution>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Vytautas Magnus University recredible.com</institution>
        </aff>
      </contrib-group>
      <abstract>
        <p>Topic Map technology (ISO 13250) is a way to facilitate the management and navigation of knowledge by creating meta-level perspectives of the underlying concepts, and the relationships between concepts that are expressed by domain ontologies. Topic maps are known to be an effective tool for organizing and navigating information, and for integrating different kinds of knowledge resources. In addition, Topic Map technology can become the core of an e-learning portal that will allow users to explore and navigate datasets through faceted searches and graph browsing, to discover related information and to understand concepts and their relationships better than using traditional reading of continuous texts. This paper discusses the need for an innovative virtual study environment. The focus is on our work on the development of the innovative platform, 'ReCredible' that will allow users to find information quickly and to learn more easily using Topic Maps.</p>
      </abstract>
      <kwd-group>
        <kwd>General Terms Algorithms</kwd>
        <kwd>Management</kwd>
        <kwd>Measurement</kwd>
        <kwd>Standardization</kwd>
        <kwd>Languages</kwd>
        <kwd>Theory</kwd>
        <kwd>Verification</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>Design,</title>
      <p>1. INTRODUCTION
Fascinating technological advances and an overwhelming
amount of information even within specific topics has prompted
the growth of new technologies for knowledge management.
Topic Map technology (ISO 13250) is known to be an effective
tool for facilitating the management and navigation of
information. The core of topic maps can be summarized very
succinctly: a topic map consists of a collection of topics, each of
which represents some concept. Topics are related to each other
by associations. A topic may also be related to any number of
resources by its occurrences. The definition of allowed types is
known as the ontology of the topic map. Topic Maps are similar
to concept maps and mind maps in many respects, though only
Topic Maps are standardized.</p>
      <p>We describe a novel solution in our ontology-driven Topic Map
portal ‘ReCredible’ that interlinks concepts, definitions, related
information and online resources via semantic, related Topic
Maps. Our basic idea is to convert unstructured information to
lightweight ontologies that are optimized for visual browsing,
content discovery and curation, and to use this for educational
purposes. This idea has been stimulated by the theories described
below.</p>
      <sec id="sec-1-1">
        <title>2. MOTIVATION OF THE SOLUTION</title>
        <p>
          Meaningful learning theory says that learners must relate new
knowledge to relevant concepts they already know [
          <xref ref-type="bibr" rid="ref1">1</xref>
          ].
Meaningful learning involves recognition of the links between
concepts. According to Ausubel [
          <xref ref-type="bibr" rid="ref1">1</xref>
          ], knowledge is hierarchically
organized, so we learn by constructing a network of concepts and
adding to them. The concept map, developed by Novak’s
research group at Cornell University in the early 1970s, is an
instructional device that uses this aspect of theory to find a better
way to represent conceptual understandings [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ]. Novak found
that the use of concept maps could help students learn how to
learn meaningfully [
          <xref ref-type="bibr" rid="ref2">2</xref>
          ].
        </p>
        <p>
          According to Novak et al. [
          <xref ref-type="bibr" rid="ref3">3</xref>
          ], advances in graphical user
interfaces and technologies in the 1990s allowed for the
development of computer-based concept mapping editors. The
development of concept mapping tools such as CmapTools [
          <xref ref-type="bibr" rid="ref4">4</xref>
          ]
enabled the collaborative construction of concept maps, and
publishing and sharing of concept maps on the Web [
          <xref ref-type="bibr" rid="ref3">3</xref>
          ].
During the last decade concept mapping has been applied to
teaching and learning of different subjects and courses, including
medicine [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ], [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ], physics [
          <xref ref-type="bibr" rid="ref7">7</xref>
          ], [8], [
          <xref ref-type="bibr" rid="ref10">9</xref>
          ], biology [
          <xref ref-type="bibr" rid="ref11">10</xref>
          ], [
          <xref ref-type="bibr" rid="ref12">11</xref>
          ],
chemistry [
          <xref ref-type="bibr" rid="ref13">12</xref>
          ], [
          <xref ref-type="bibr" rid="ref14">13</xref>
          ], business and management [
          <xref ref-type="bibr" rid="ref15">14</xref>
          ],
mathematics [
          <xref ref-type="bibr" rid="ref16">15</xref>
          ], social studies [
          <xref ref-type="bibr" rid="ref17">16</xref>
          ], [
          <xref ref-type="bibr" rid="ref18">17</xref>
          ], learning foreign
languages [
          <xref ref-type="bibr" rid="ref19">18</xref>
          ], [
          <xref ref-type="bibr" rid="ref20">19</xref>
          ], etc. Concept mapping has been shown to be
effective when used as an assessment tool at all levels of
education. When used with pre-school or elementary school
children, concept maps also facilitate language learning and
learning to read as well as promoting better ways to learn [
          <xref ref-type="bibr" rid="ref3">3</xref>
          ]. It
is clear that concept mapping has had a large impact on
facilitating easy understanding of the subject to be learned, and
on the organization of the learning content. In addition, concept
maps have been identified as an effective tool for evaluation,
displaying students’ prior knowledge, summarizing what has
been learned, note taking, aiding study, planning, scaffolding for
understanding, consolidating educational experiences, improving
affective conditions for learning, teaching critical thinking and
supporting cooperation and collaboration [
          <xref ref-type="bibr" rid="ref21">20</xref>
          ].
        </p>
        <p>Despite the fact that concept map technology is an effective tool
for the learning process, it is not used universally. Although
texts, videos, pictures, presentation slides and other forms of
material representation are used every day in learning activities,
concept maps are not so popular. The most important reason is
that constructing concept maps is not easy – it requires effort and
time to build a good map. Concept mapping or mind mapping
tools are not simple to use. Specialists or domain experts create
domain ontologies, but this is done with sophisticated software
and is therefore not a feasible method for the ordinary user.
There is a lack of the tools needed for constructing concept maps
that are both easy to use and don’t rely on some knowledge of the
underlying theory. In addition, there are no mobile applications
or online courses on the web that would provide learning
material in the form of the concept maps or would incorporate the
concept maps in e-learning content. For these reasons we have
used Topic Maps, which are a standardized means of
representing polymorph structures in a comprehensive way for
building an innovative e-learning tool for knowledge
management and e-learning.</p>
      </sec>
      <sec id="sec-1-2">
        <title>3. DESCRIPTION OF THE SOLUTION</title>
        <p>As mentioned above, ReCredible.com beta (along with the
ReCredible mobile applications for iPad and IPhone devices) is
a personal learning environment based on the concept of topic
maps. This section discusses this powerful way to manage,
structure and navigate knowledge, and describes the use of the
intuitive, visual interface of the ReCredible system for learning
purposes. We offer a new methodology for the development and
maintenance of the Topic Maps e-learning portal and briefly
present a pilot application.</p>
      </sec>
      <sec id="sec-1-3">
        <title>3.1 Focus of ReCredible</title>
        <p>
          In virtual study environments, Topic Maps technology is
applicable as follows. Each e-course focuses on a certain
discipline, which has its own terminology. This terminology is
conceptualized by the discipline (domain) ontology. The Topic
Map application of study resources can be built above this
ontology. Such a Topic Map application visualizes the discipline
terminology, which helps students to understand the structures of
studied disciplines [
          <xref ref-type="bibr" rid="ref22">21</xref>
          ]. In addition, together with the discipline
ontologies, used for subject categorization of resources, it is
possible to apply a kind of course ontology for arranging units
and elements that together form the course content. Therefore
teachers can define the recommended order of resources
(presentations, documents, exercises etc.) to be studied using the
Topic Map portal, as well as in the e-course’s study content
module in the current virtual study environments [
          <xref ref-type="bibr" rid="ref22">21</xref>
          ].
The ReCredible system focuses on the development of topic
maps for e-learning content but it offers opportunities to integrate
different kind of e-learning resources (e-courses material, videos,
presentations, exercises, and links to online courses) as well.
Currently, ReCredible beta users can browse Topic Maps for
different content and search for information. Tools for different
resources integration are being developed and will be available
soon.
        </p>
        <p>All the concepts, definitions, related information and online
resources are interlinked via semantic, related concept maps in
ReCredible. Topic Maps technology allows users to find
information quickly without reading all the text, and to memorize
it easily, looking at the knowledge as a whole. ReCredible could
become the way that people explore and learn about topics and
concepts, enjoying easy navigation and a visual experience. The
ReCredible system provides an alternative to traditional learning
methods and reading of continuous texts. This will become
increasingly important in the era of touch screens, smart glasses,
and motion sensing. In addition, the use of Topic Map
technology will allow the application to assess the user’s
interests and knowledge automatically based on his search in the
ReCredible concept maps, and to offer the most useful topics and
concepts to the user, as well as related online resources which
would be interesting for him. Unlike other e-learning courses or
tools, ReCredible assesses the user’s interests in just a few
seconds because of the use of Topic Maps where all the
knowledge is interlinked.</p>
        <p>ReCredible converts unstructured information to lightweight
ontologies that are optimized for visual browsing, content
discovery and curation. We are basically trying to democratize
ontology creation so every user of ReCredible can take part in the
creation of the Topic Maps and e-learning material. Registered
user can edit Topic Maps, add information, and create new Topic
Maps in very simple and intuitive way. Educational institutions
will receive APIs so that they can include plugins of ReCredible
in their systems.</p>
        <p>As has been described above, the main idea of ReCredible is to
provide a Topic Map based system for knowledge finding and
elearning. This idea has several advantages.
1. The concept map of the knowledge. These days mankind
creates and stores more information in a single day than was
created and stored in previous centuries. It is paradoxical, but
people are reading less and less, and finding it harder to work
out which parts are most important for them in the mass of
information. The information given in ReCredible is linked via
Topic Maps in the same way your mind links concepts, allowing
the user to find the exact information very quickly without
reading different texts.
2. Personalization of learning process. The platform breaks
learning into bite-sized chunks and offers each part as a “snack”
so it is possible to choose your own way of reading concepts.
3. User-friendly, intuitive navigation enabled by ontologies.
Typical e-learning tools or online courses consist of various
information that includes texts, pictures and links, but a better
way to understand and memorize information is graphic
visualization. ReCredible converts unstructured information to
simplified visualized ontologies that are optimized for visual
browsing, content discovery and curation. The attractive
visualization of Topic Maps helps users to memorize information
very intuitively.</p>
      </sec>
      <sec id="sec-1-4">
        <title>3.2 Development of ReCredible technology</title>
        <p>
          Current Topic Map technology (ISO 13250) is on its way
towards consolidating its position as a powerful way to manage
structure and navigate knowledge. The general idea behind topic
maps is to organize information by subjects and relations
between subjects [
          <xref ref-type="bibr" rid="ref23">22</xref>
          ].
        </p>
        <p>
          No methodology of Topic Map application creation is presented
in the basic ISO/IEC Topic Map standard, so the consecution
totally depends on authors of particular Topic Map applications
and on software used for the implementation of Topic Maps
applications. General Topic Map developers’ guides suggest
adopting either a top-down, or bottom-up methodology. The
former works by defining the application area, and the second by
summarizing the available information and knowledge resources
to be covered by the Topic Map application [
          <xref ref-type="bibr" rid="ref22">21</xref>
          ].
        </p>
        <p>In both approaches, the next Topic Map application development
contains the following steps:
- definition of functional requirements and the purpose
of the future Topic Map
- definition of schema of the Topic Maps based portal
the ontology
- selection of the tool for implementation of the Topic</p>
        <p>
          Maps solution
- population of instances, including evaluation of
fulfilling all restrictions and constraints
- optional revision of the schema of the Topic Maps [
          <xref ref-type="bibr" rid="ref22">21</xref>
          ]
The Topic Map model defines three basic building blocks: topic,
association and occurrence [
          <xref ref-type="bibr" rid="ref24">23</xref>
          ]. Topics are computer
representations, either of particular subjects of our world, or
abstract categories that exist in this world. Occurrences are
characteristics of topics and are true in the context of the
particular scope. The occurrence is a string value - either a
statement about the topic, or a link to the resource (monograph,
article, image, sound file etc.). Associations are essential for
establishing the network structure of topic. Two or more topics
are in an association if there is some relationship between them.
The solution developed on recredible.com includes the
semiautomatic generation of Topic Maps and visualization of the
generated Topic Maps. The entire system works on a
clientserver principle. The system proceeds according to three major
steps: a) a topic is created using an online editor; b) the topic is
converted into our topic map format and hosted on our servers; c)
the topic is published and made accessible via a frontend of
choice (visualized on a touchscreen or web-enabled frontend).
These steps are illustrated in Figures 1 and 2.
        </p>
        <p>Selection of atopic
Knowledgesources</p>
        <p>Dataextraction
Manual mining
(books, col ections
of text, etc.)</p>
        <p>Automated mining
(wikipedia, dbpedia,</p>
        <p>etc.)
Pre-processingand determining</p>
        <p>semantic information
Concept
selection</p>
        <p>Relation
Retrieval</p>
        <p>Constraint</p>
        <p>Discovery
Buildingan ontology</p>
        <p>Integrated
knowledgebase</p>
        <p>Integrated topic map
Figure 1 illustrates the simplified building of a Topic Map. Each
Topic Map is chosen very carefully by determining which
domain the ontology will cover, what we are going to use the
ontology for, what types of answers the information should
provide, and who will use the ontology. The process itself is
started by data extraction from various sources. This is done
either manually from books and text, or automatically from
structured sources of information (such as Wikipedia, DBpedia,
FreeBase, etc.). Developing an ontology includes defining
classes in the ontology, arranging the classes in a taxonomic
(subclass–superclass) hierarchy, defining slots, describing
allowed values for these slots and filling in the values for slots
for instances. Everything is saved and maintained in our
knowledge base.</p>
        <p>Atopic isloaded on to</p>
        <p>server
Atopic map is
retrieved from
adatabase
Datarepresentation
and visualization
processisstarted
Categorizingis</p>
        <p>doneand
appropriatecolor</p>
        <p>isattached
Sizeand intesity is
determined and set
for each of thenodes</p>
        <p>Positioningis
calculated and</p>
        <p>saved
Appropriatedatais
written to adatabase
Information isready for
accessviaaweb service</p>
      </sec>
      <sec id="sec-1-5">
        <title>3.3 Visualisation of ReCredible Topic</title>
      </sec>
      <sec id="sec-1-6">
        <title>Maps</title>
        <p>Information visualization is a well-studied scientific topic, and
unfortunately remains an unsolved problem. Since the earliest
cave paintings, Homo Sapiens have always pursued an effective
way to visualize information. Our knowledge perception systems
and abilities are the result of evolution. Graphical perceptions are
processed pre-attentively and rapidly, and are accessible
intuitively without the need for active cognition. ReCredible
visualization solution allows us to access, control, explore,
combine and manipulate various types of knowledge, also
helping us to create new insights. Knowledge visualization and
visual thinking are gaining importance in all areas of science,
ebusiness and society. Knowledge visualization aims to facilitate
the mutual transfer of facts, insights, experiences, values,
expectations, perspectives, opinions and predictions.
State-of-theart visual approaches aim to support the creation, application and
communication of knowledge and insights – particularly in
situations where people from different educational, cultural and
professional backgrounds collaborate. This method of
information display offers an easier way to dive into the data
itself, much like a human brain works. The main problems are
effectively creating and transferring insights between various
information sets, various users, and effectively various minds, as
well as managing and reducing the complexity of standard
presentations, thus allowing a more effective interpretation and
understanding by such increasing the amount of parsed data,
supporting learning, communication and interaction through
novel and easier-to-grasp approaches and techniques. To ensure
that visualizations can to match the problem, purpose and
knowledge in mind, new visualizations are often required to
support various tasks.</p>
        <p>
          Visualization of ontologies is not an easy task. Ontology is
something more than a hierarchy of concepts. Relations among
concepts and each concept have various attributes. We think that
the following five questions should be answered in any good
knowledge visualization model [
          <xref ref-type="bibr" rid="ref25">24</xref>
          ]:
•
•
•
•
        </p>
        <p>What is the aim and the effect of externalizing
knowledge into visual representations?</p>
      </sec>
    </sec>
    <sec id="sec-2">
      <title>What is relevant and should be visualized?</title>
    </sec>
    <sec id="sec-3">
      <title>Which audience should be addressed?</title>
    </sec>
    <sec id="sec-4">
      <title>What is the interest of the recipient?</title>
      <p>• What is the most efficient way to visualize the
knowledge?
We have developed techniques specifically for visualization of
our application. The backend of the system (see Figure 2)
consists of the Mongo database, which is a NoSQL data structure
well suited to storing nested data like Topic Maps.</p>
      <p>For rapid server-client communication the RESTful Web service
API (Application Programming Interface) was created. With the
use of API, the client’s application can easily receive detailed
information about the Topic Maps and each individual topic. All
the data is served in a JSON format. The process starts with
retrieving a Topic Map from a database and starting a data
representation and visualization processes. In principle what it
does is check for a number of possible categories, assigning a
visual representative for each of those (a different color), setting
the opacity depending on the quality of content inside,
determining the possible size and position of each node based on
the relations they have, and writing all this information back to
the database of visualization-ready Topic Maps. At this stage a
web-service-ready Topic Map is generated. Data is “mixed and
matched” to be as easy to understand as possible, and also as
visually attractive as possible. The visualization method of
ReCredible displays all the ontology classes at once or at the
request of the user, providing their name in an intelligible
manner using a specific color (see Image 1).</p>
      <p>Image 1. A orbit view in ReCredible: pilot iPad application
As instances are the actual data associated with the ontology and
are typically what most users are actually looking for, we
represent them as connected nodes (bubbles). As showing all the
connections via visual links is not effective when there is a large
number of relations we have an overview mode (called orbit
view) which presents instances in an orbit, where more important
items are moved towards the center of the orbit (see Image 1).
The presentation of the taxonomy on which the ontology is based
is essential for understanding the inheritance relations between
classes, thus we provide a holistic view of this taxonomy. The
user can hide certain items thus creating a partial view and
focusing on a portion of the taxonomy. When a class has more
than one parent the tree view (see Image 2, Image 3) presents an
effective visualization to indicate nodes with multiple parents
and provide efficient means to view all the direct ancestors of a
node. Links (relations) are also displayed in the tree view but the
names are hidden to avoid clutter, especially on smaller screens
such as on an iPad. It’s possible to display the names on a larger
screen (e.g. recredible.com) or when the hierarchy is smaller and
more manageable, and this is always an option to consider.</p>
      <p>
        Image 2. The tree view in ReCredible: pilot iPad application
Image 3. An expanded tree view of ReCredible: pilot iPad
application
We have implemented tree-based node link diagrams as they are
considered among the most common and intuitive ways for
hierarchy representations of semantic networks. This system
offers an effective overview of semantic data structures of
different levels and features. In our analysis of different models
and methods, we concluded that methods such as cone tree
implementations [
        <xref ref-type="bibr" rid="ref26">25</xref>
        ] are most suited to helping users answer
structural and trend-related questions. Tree node – link methods
[
        <xref ref-type="bibr" rid="ref27">26</xref>
        ] have the disadvantage of requiring a lot of screen space, but
we have solved this via finger-friendly interactions.
      </p>
      <p>
        Our test users have commented on the lack of interaction and had
experienced problems with traditional navigation, such as having
to drag the scrollbars to navigate or use zoom in and out
commands, and sometimes clicking accidentally on an instance,
which resulted in wrong class or object, or even a loss of focus.
A ReCredible approach allowed us to overcome this in a much
more intuitive way, allowing sorting (instances can be
interactively sorted and color/size coded via types, categories,
groups, etc.). Most of our users thought that the ReCredible
system could be very effective for smaller ontologies or if the
user is familiar with the ontology as it seemed to them useful for
the presentation of hierarchies, even allowing them to return to a
previously visited node and quickly jumping to hierarchy
overview, because it maintains a constant positioning of the
nodes in combination. Our nodes can be controlled by expansion
of sub-trees, as expanding child up to a certain level, seemed to
be very effective. As defined in [
        <xref ref-type="bibr" rid="ref28">27</xref>
        ] a task that included finding
a specific node with the maximum number of connections to
another type of node, users preferred to browse using the orderly
tree types of knowledge rather than attempting to locate the node
with the most connections.
      </p>
      <sec id="sec-4-1">
        <title>4. CONCLUSIONS</title>
        <p>In this paper we have proposed understanding virtual study
environments as a kind of knowledge management system based
on the Topic Maps standard. The ReCredible example described
above illustrates the broad range of activities related to
knowledge finding and curating, information creating and
elearning that are possible when using Topic Maps.</p>
        <p>Graphical tools such as ReCredible Concept Maps enable
anybody to express and interpret knowledge in a form that is
easily understood.</p>
      </sec>
    </sec>
  </body>
  <back>
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