=Paper=
{{Paper
|id=None
|storemode=property
|title=Visualizing Mapping of Metadata Properties
|pdfUrl=https://ceur-ws.org/Vol-680/paper_6.pdf
|volume=Vol-680
}}
==Visualizing Mapping of Metadata Properties==
<pdf width="1500px">https://ceur-ws.org/Vol-680/paper_6.pdf</pdf>
<pre>
     Visualizing Mapping of Metadata Properties

                Martin Höffernig, Wolfgang Weiss, Werner Bailer

                         JOANNEUM RESEARCH, DIGITAL –
       Institute of Information and Communication Technologies, Graz, Austria
                          {firstName.lastName}@joanneum.at


1     Introduction
Millions of hours of audiovisual content are held by collections of dedicated
broadcast, film and sound archives, institutional or corporate archives, libraries
and museums. There is a large heterogeneity between the different audiovisual
archives resulting from their history and tradition but also from cultural dif-
ferences of the countries where those archives reside. Consequently metadata
models covering the workflows and necessities in the archives differ as well. This
fact and the need for metadata for various different use cases in the archives
lead to a number of metadata models and standards. Thus mapping between
different metadata models is inevitable in practical applications.
    We are currently developing a system for automating metadata mapping by
formalizing semantics of properties in the different formats and their relations [4],
based on an intermediate ontology, namely the meon ontology [3]. In order to
enable users to validate the automatically determined mappings visualization
functionalities are required in the system. This paper describes the integration
of the ontology visualization developed in [6] into our mapping system prototype.
    Creating comprehensive, clear and intuitive visualizations of ontologies and
RDF graphs is an ongoing challenge. Different approaches can be found in ap-
plications for Semantic Web engineers. An example is Protege1 , which is an
open, platform independent environment for creating and editing ontologies and
knowledge bases. The application is extensible by its plug-in architecture and
thus provides several visualizations. IsaViz2 is a visual tool for browsing and
authoring of RDF models. Resource nodes are represented by ellipses, literals as
rectangles and properties are displayed as lines with arrows. OntoSphere 3D [1]
uses a collection of three-dimensional visualization techniques displaying ontolo-
gies. gFacet [2] combines the graph visualization with facet search in the graph.
    These applications use different kinds of visualization techniques to present
the user a possibly easy to understand and complete overview of the whole
RDF graph. Using graph visualizations of RDF data especially for end users
has a number of drawbacks. For example, these visualizations are flat and every
node is treated as a primary node. Also, displaying a graph with hundreds of
nodes and edges results in a cluttered visualization (cf. [5]). Nonetheless graph
visualizations have their place, especially for Semantic Web engineers [6].
1
    http://protege.stanford.edu/
2
    http://www.w3.org/2001/11/IsaViz/
2     Implementation

The prototype3 helps users finding, validating, and understanding metadata
mappings by automatic metadata matching and appropriately visualizing map-
ping relations. Figure 1 shows the textual part of the user interface where the
user creates a query. The first step of the user is to select an input- and output
metadata format. Via the Load button, the application lists all available con-
cepts from the selected formats. The next step is to select one or more concepts
for which the mapping relations should be found. After confirming the selected
concepts by clicking the Ask button, dependencies between the input and out-
put concepts according to the defined rules are calculated and displayed. For
each selected output format the information whether a mapping is feasible or
not is displayed: True, if the output concept can be mapped from one or more
of the selected input concepts, False otherwise. In case that there are output
concepts without corresponding selected input concepts, the Find requirements
option can be used. After selecting this option additional necessary input con-
cepts are computed in order to establish mapping relations to the selected output
concepts.
    In addition to the boolean information about the feasibility of the mapping
explained above, possible mapping relations are visualized in a graph visualiza-
tion. The RDF-like graphs include the selected input concepts as yellow nodes,
the selected output concepts as red nodes, the related meon concepts as green
nodes and potentially missing input concepts as white nodes. It focuses on the
current task of the user by displaying only necessary nodes and edges. This kind
of visualization supports the user in understanding and validating the found
mapping relations between input and output concepts of the metadata formats.
An example of the graph visualization of the selected concepts shown in Fig-
ure 1 is depicted in Figure 2. The graph representation reveals that the input
concept mpeg7:Height together with mpeg7:Width can be mapped to the se-
lected output concept ma:FrameSize via meon:Resolution, which is part of
the intermediate ontology (meon ontology). Beside this positive mapping re-
lation, no appropriate mapping relation can be established to the remaining
output concept ma:Creator from any of the selected input concepts. However,
mpeg7:UnqualifiedCreator is a possible input concept to map to ma:Creator.
    The mapping prototype is a Web application using standard Web technolo-
gies such as HTML and JavaScript for the user interface as well as Scalable
Vector Graphics (SVG) for the graph visualization. To generate the graph we
use the Java Universal Network / Graph Framework (JUNG)4 , which provides a
number of layout algorithms and mechanisms to manipulate graphs. An internal
evaluation has shown that the “self-organizing map layout for graphs” produces
the best results for our requirements. However, this layout algorithm generates
a different layout at every single run. Therefore, it is necessary to animate the
graph visualization for the user. The animation helps the user to follow how
3
    http://prestoprime.joanneum.at
4
    http://jung.sourceforge.net/
                         Fig. 1. Visualization interface.


the layout changed since the last run. For processing the RDF data the Jena
Semantic Web framework5 has been used.


3     Conclusion and Future Work
In this paper we have presented the visualization functionality of our metadata
mapping prototype6 which helps users finding, understanding and validating
metadata mappings by automatic metadata matching and appropriately visu-
alizing mapping relations. The visualization shows mapping relations between
input and output metadata formats which are determined by the system via an
intermediate ontology. It uses coloured nodes and focuses on the current user
task by displaying only nodes which are necessary for the current task. The sys-
tem is able to find direct metadata mappings as well as to suggest further input
concepts to satisfy the desired metadata mappings. In the future the system
shall support the definition of mapping rules by the user in order to improve
the results in cases where incomplete or ambiguous mappings between pairs of
formats exist.
5
    http://jena.sourceforge.net/
6
    http://prestoprime.joanneum.at
                     Fig. 2. Example of mapping visualization.


Acknowledgments
The research leading to these results has received funding from the European
Union’s Seventh Framework Programme under grant agreement nr. FP7 231161,
“PrestoPRIME” (http://www.prestoprime.eu).


References
1. Alessio Bosca, Dario Bonino, and Paolo Pellegrino. Ontosphere: more than a 3d on-
   tology visualization tool. In Proceedings of the 2nd Italian Semantic Web Workshop,
   14-15-16 December 2005, number 166, University of Trento, Trento, Italy, December
   2005.
2. Philipp Heim, Thomas Ertl, and Jürgen Ziegler. Facet graphs: Complex semantic
   querying made easy. In 7th Extended Semantic Web Conference (ESWC2010), June
   2010.
3. Martin Höffernig and Werner Bailer. Formal metadata semantics for interoperability
   in the audiovisual media production process. In Workshop on Semantic Multimedia
   Database Technologies (SeMuDaTe), Graz, Dec. 2009.
4. Martin Höffernig, Werner Bailer, Günter Nagler, and Helmut Mülner. Mapping
   audiovisual metadata formats using formal semantics. In 5th International Confer-
   ence on Semantic and Digital Media Technologies, Saarbrücken, DE, Dec. 2010. To
   appear.
5. David Karger and M.C. Schraefel. The pathetic fallacy of rdf. http://swui.
   semanticweb.org//swui06/papers/Karger/Pathetic_Fallacy.html, 2006. Re-
   trieved 06 February 2007.
6. Wolfgang Weiss, Michael Hausenblas, and Gerhard Sprung. Visual exploration,
   query, and debugging of rdf graphs. In Proceedings of the Fifth International Work-
   shop on Semantic Web User Interaction, April 2008.

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