=Paper=
{{Paper
|id=Vol-358/paper-5
|storemode=property
|title=Towards Ontology Mapping for Ordinary People
|pdfUrl=https://ceur-ws.org/Vol-358/paper05.pdf
|volume=Vol-358
|authors=Colm Conroy,pages 21-25
}}
==Towards Ontology Mapping for Ordinary People==
https://ceur-ws.org/Vol-358/paper05.pdf
Towards Ontology Mapping for Ordinary People
Colm Conroy1, ,
(Co)Supervisors: Declan O’Sullivan1, David Lewis1
1
Knowledge and Data Engineering Group,
Trinity College Dublin
{coconroy,declan.osullivan,dave.lewis}@cs.tcd.ie
1 Introduction
The reasons for the lack of uptake of the semantic web amongst ordinary users can be
attributed to technology perception, comprehensibility and ease of use. It is perceived
that the creation of ontologies is a top-down and complex process, whereas in reality
ontologies can emerge bottom-up and be simple. Ontology technology is based on
formal logics that are not understandable for ordinary people. Finally there is
significant overhead for a user in the creation of metadata for information resources in
accordance with ontologies. To address these three problems, we believe that the
interfaces to ontology tools will need to be engineered in such a way as the tools
disappear into the background from the ordinary person’s perspective.
There is a common diversity between the semantic models of interest between people.
If users of the semantic web choose to model their interest with a personal ontology,
their ontology will need to be mapped to the models used in the various diverse
communities by the person himself or herself. The automatic and efficient matching
between the personal ontology and the models used by others (collaborative tags
and/or community ontologies) can be achieved through the application of a variety of
matching techniques [1]. Fully automatic derivation of mappings is considered
impossible as yet [2], and the majority of state of the art tools in the ontology
mapping area [3] and the community ontology creation area [4] rely on a classic
presentation of the class hierarchy of two ontologies side by side and some means for
the user to express the mappings. These approaches predominately assume that the
mapping is being undertaken by an expert: who does not require a personalized
interface; whose explicit task is to generate a “one size fits all” full mapping (to be
used in common by several applications); and who undertakes the task during a small
number of long sessions. The number of user trials that have taken place have also
been small [5] and those that have, have focused purely on the effectiveness and do
not address usability issues (an exception recently being that of [6]). In contrast, we
propose that the user who will benefit from mappings (through usage by their
applications), will undertake themselves partial targeted mappings, gradually and over
time, using techniques that address usability issues, support personalization and
enable control of the mapping interactions.
2 State of Art
There is an emergence of focusing on better support for users within the ontology
mapping area with cognitive support for user [7], a community-driven matching [8],
explanation of matches to users [9], and developing a formal model for ontology
mapping [10]. One of the key problems which have seen little research from a
cognitive perspective is how to display the match information in a manner that is
natural for the user. The visualization of ontology (schema) mapping can be
categorised into four different categories: tree-type, object-type, instance based
spreadsheet, and hyperbolic. Tree-type interfaces are the most common for mapping
tools and represent the semantic models side by side in a tree form, e.g. COMA++
[3], and mappings can be represented in two different ways with lines drawn between
matching terms or via a mapping table that contains all the mappings. Object type
interfaces represent the ontology in an object type or UML structure, with mappings
between the two schemas being drawn using lines (and symbols to represent the type
of mapping), e.g. SMART [11] ‘=’ is used for equals, ‘)’ for subset and so on.
Spreadsheet type interfaces, e.g. Webscripter [12], uses spreadsheet functionality to
display global mapping tables containing instance data from different users. Finally a
hyperbolic interface is one where the source and target models are represented by
hyperbolic graphs in different frames, e.g. Schema Mapper [13]. AlViz [14] is a tab
plug-in for Protege which provides visualization techniques to facilitate user
understanding of alignment results. There are other types of ontology tools which use
different types of interfaces; GINO [15] is a guided input natural language ontology
editor that allows users to edit and query ontologies in a language akin to English.
OntoViz [16] is a protégé plugin which represents ontologies via a direct graph with
concepts in boxes and relations defined with lines.
3 Research Question/Contribution
The research question we are addressing is what kind of interactions will be
acceptable, efficient and effective for an ordinary user to achieve semantic mappings
gradually and over time between information models of interest to the user. In
particular our work will provide:
• Design of a mapping framework in support of ordinary people: There is a need
to make the ontology mapping process as unintrusive and as natural as possible,
as it is important not to interrupt ordinary users during their daily life, so that they
do not see mapping as inconvenient work but more as something that will be
beneficial to them, and where they can clearly see the benefits.
• Determine the most appropriate user interaction in the process of constructing
mappings: There has been little or no research by the current state of the art
completed regarding user interaction within mapping systems. While
visualization is a key factor in this problem another key issue is determining the
most appropriate (different) way(s) for (different) people to construct mappings,
e.g. draw lines graphically, ‘yes/no’ answer on questionnaire, etc…
• Determine the appropriate ways to engage the user over time: There is a need to
engage the user in the mapping process over time rather than one long session.
This need comes from the realization that by reducing the mapping process into
piece wise comparison will make the mapping process easier to comprehend and
also will be able to give feedback to the user of the mapping choices they make
outside of the mapping sessions. Another issue will be does collaborative
knowledge sharing (via groups) assist ordinary people in the mapping task
An outcome of this research will be a process (Figure 1), methodology and tools.
Figure 1: Mapping Process
4 Evaluation
In our initial experiment undertaken early in 2007 we aimed to determine the most
practical way of visually displaying the mapping information for different groups of
users. Our hypothesis was using a Question & Answer natural language interface to
visually display ontological information helps in making mapping more familiar and
accessible and also reduces the complexity of the mapping process for users. The
intention of our experimentation was to investigate the effect and usability of a natural
language prototype tool (NL) on three groups of users and to determine whether it
made the mapping task more user friendly for one group over another. In addition we
wanted to contrast our tool against a current state of the art mapping tool. We chose
COMA++ as our State of the Art tree type graph mapping tool. The three different
groups of users were: Ontologically aware, Technology aware and Non-Technology
Aware (Casual Web User). The paper [17] goes into detail about the experiment,
some key conclusions drawn were:
• On the positive side, results suggested casual web users can map effectively and
efficiently even compared to ontology aware users. Using Natural Language
seemed to help people read and understand the information and the Q&A
approach helped in navigating through the mapping task.
• On the negative side, casual web users found it very restrictive to be limited to a
narrow range of mapping terminology, e.g. “corresponds” and “similar to” when
answering mapping questions. In addition, some users were unclear about the
benefit in engaging in the mapping task.
In our current experiment (finishing May 2008) we are focusing on whether it is
valuable to embed the mapping process within the user environment, designing a
user-centric mapping process, and addressing the negative concerns garnered from the
previous experiment by allowing the user to be more expressive by allowing them to
‘tag’ the mapping relation. Our hypothesis is the mapping task can be simplified and
become unintrusive by embedding the mapping process within the user environment
and by using a ‘tagging’ approach paradigm. By using the power of “Web 2.0”
through a Firefox extension within our new ‘tagging’ prototype, we aim to engage the
user and display matching collections at appropriate times within their own work
environment, see [18] for more details. We use online questionnaires, interviews, and
a log of each user’s actions to evaluate the impact of the ‘tagging’ prototype. In
particular through the use of our implementation over the coming months we aim to
investigate whether casual web users will be able to use tagging to turn matches into
expressive mappings in a straightforward, practical and natural manner. We will also
investigate whether embedding the mapping interface inside a browser extension will
allow the mapping process to take place over time within a casual web persons work
environment in an unobtrusive, sensible, and normal way.
Our next experiment is going to be investigating the effects of collaborative
knowledge sharing via groups (from June 2008 to October 2008). A key factor of this
experiment will be to investigate whether the knowledge shared by ontological aware
users can be beneficial to casual web users. Another issue is which users are the most
beneficial for validating each matching pair question, i.e. will users with musical
background be better than ontological aware user in relation to music based
matching’s. Another aspect is whether it is better to divide the users into different
groups and what type of characteristics determine which group(s) each user is put
into. A final feature of investigation will be if categorising the ‘user-defined’ tags
collaboratively, whether globally or within groups, is of any help to users.
In our first experiment we looked at displaying ontological information with natural
language and to analysis the difference between a graph types interfaces. The natural
language used was far from ideal and although the results showed the benefits of
using this type of interface we intend to revisit this objective to make tests with
different visual types of interfaces (from November 2008 to April 2009). We intend
to investigate different visual types of natural language, such as representing the
concepts with shallow text generation as discussed in [19], and other different visual
types. Although finding a one-size-fits-all interface for everybody may be
impossible, we believe there can be a basic interface which can be suitable to most
casual web users while also allowing these users to change the visualization to their
needs, i.e. some may rather graph based to natural language and vice versa, etc...
A key problem is reducing mapping tasks to being unintrusive to casual web user.
We intend to explore in what context and at what time should a mapping task be
performed by the user (from April 2009 to June 2009). Finally the thesis write up
will occur from July 2009 till November 2009.
References
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Semantic Integration, SIGMOD Record, Volume 33, Issue 4, pages 65-70, 2004.
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COMA++”, Proc. SIGMOD 2005 (Software Demonstration), Baltimore, June 2005.
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