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  <front>
    <journal-meta />
    <article-meta>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Katholieke Universiteit Leuven, Department of Computer Science Celestijnenlaan 200a</institution>
          ,
          <addr-line>3001 Leuven</addr-line>
          ,
          <country country="BE">Belgium</country>
        </aff>
      </contrib-group>
      <fpage>38</fpage>
      <lpage>46</lpage>
      <abstract>
        <p>In this paper we describe how we want to take advantage of the rapid developments in technology to assist researchers in doing research. More specifically in exploring the publication space. For this purpose we have designed and developed a prototype application to take advantage of large displays with multi touch enabled input. We describe the current state, the next steps and how we will to evaluate it. To conclude we give an outlook on further possibilities and challenges that lay ahead.</p>
      </abstract>
      <kwd-group>
        <kwd>research2</kwd>
        <kwd>0</kwd>
        <kwd>information visualization</kwd>
        <kwd>multi touch</kwd>
        <kwd>large display</kwd>
        <kwd>research</kwd>
        <kwd>fm</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>Introduction</title>
      <p>
        How great would it be to integrate the process of exploring publications, finding
them and reading them in an almost seamless way ? This sort of idea was already
described in As we may think in 1945 by Vannevar Bush [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ]. The Memex was
described as the perfect desk of a researcher, having all the knowledge of the
world readily available. At that time personal computers were not even invented,
but since then technology has advanced tremendously and become very common.
Using current state of the art technologies, we want to find out how we can ease
the process of exploring publications. This process is an important part of a
researcher’s job, as he wants to know what is going on in his field of research.
      </p>
      <p>
        To be able to get this kind of understanding, Russell et al [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ] have pointed
out that it is imperative that the right representation is found for exploring a
network of (publication) data.
      </p>
      <p>
        The idea of visualizing publication networks has been inspired by the work
of Klerkx et al, where they explore learning object repositories [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ] and social
bookmarks [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ] in a visual manner.
      </p>
      <p>In this paper we first introduce and describe the problem. We then motivate
our hardware platform, describe the origin of the data and we explain the
detailed workings of the application. In the next section we compare our work with
existing studies. Then we describe how we evaluate this and finally we propose
the next steps to be taken. To conclude we summarize our findings and discuss
further possibilities.
2</p>
    </sec>
    <sec id="sec-2">
      <title>Problem statement</title>
      <p>
        An important part of a researcher’s job is reading scientific papers. This ensures
that the researcher is up to speed of what is going on in his research field. It
is also a prerequisite for writing scientific papers, as handbooks such as the one
from Robert A. Day [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] emphasizes.
      </p>
      <p>There are three basic ways of dealing with scientific papers. There is active
search, where you search for a particular paper or a ‘good’ paper on a specific
topic you have in mind. There are dozens of websites that serve this purpose
really well, such as Google Scholar1, ISI web of Knowledge2, DBLP3 etc. There
is also what we can call passive search, where you get alerted whenever new
publication material is available. Google Scholar has recently added a feature
where you can be alerted whenever something new comes up that matches certain
keywords. Also many of the journal magazines let you subscribe to a list to send
you the table of contents when a new issue is available. Finally one can focus
on relations between papers and authors. There are existing tools where this is
possible, but we think that there is not enough technical support available for
exploring these networks.</p>
      <p>To explain the problem we want to solve, we will briefly describe the use
cases we want to tackle with this work. The use cases can be grouped into two
categories. In the first category the use cases have a mainly top down approach,
while the second category holds the use cases that typically need a bottom up
approach.
2.1</p>
      <sec id="sec-2-1">
        <title>World overview</title>
        <p>Typically, in this use case a user would like to start with a complete overview
of all nodes laid out in a graph. The user then wants to zoom in on parts of
the graph that draw her attention. This can be used to find out patterns or
clusters. In this case the user usually is already an expert in the field, trying to
understand or improve his knowledge about the field.
2.2</p>
      </sec>
      <sec id="sec-2-2">
        <title>Explore your neighbors</title>
        <p>In this case you might want to start from a view with a focus on yourself, or
the author or paper that you want to start from. Then you want to browse to
nodes in your ‘neighborhood’, which are likely to be related and/or interesting.
Here you can try to find answers to questions like : Where am I in the research
publication space ? Who should I talk or connect to ?</p>
        <sec id="sec-2-2-1">
          <title>1 http://scholar.google.com</title>
        </sec>
        <sec id="sec-2-2-2">
          <title>2 http://apps.isiknowledge.com</title>
          <p>3 http://www.informatik.uni-trier.de/∼ley/db/
3
3.1</p>
        </sec>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>The application</title>
      <sec id="sec-3-1">
        <title>The hardware</title>
        <p>The input modalities We chose for supporting a multi-touch setting, as we
want to explore direct and multi touch capabilities. This to find out whether
these relatively new input methods can help to make it easier for researchers to
interact with the fairly complex graph like structures.</p>
        <p>The display The application will entail a visualization of a deeply connected
network containing up to hundreds (maybe thousands) of nodes. This property
feeds the need for using a large display. These large displays, with increasingly
higher resolutions, are also rapidly becoming cheaper and more common, which
makes it easier to include them in our study and makes this study more relevant.</p>
        <p>A problem that sometimes arises on multi touch input devices is when one
touches the screen to give input, the finger or hand occludes information one
wants to see at that moment. This can be solved in two ways, either we make
the information appear next to the touch point, or we make the information
bigger so it is less likely to be occluded. Both solutions can benefit from a larger
display, as you have simply more space to put the information.</p>
        <p>
          Studies by Forlines et al [
          <xref ref-type="bibr" rid="ref5">5</xref>
          ] and Kin et al [
          <xref ref-type="bibr" rid="ref6">6</xref>
          ] have already shown that on
tabletop displays multi touch input has performance and spatial awareness
advantages over the traditional mouse, which reinforces our choice of hardware.
From a research perspective, we want to explore if and how a large screen estate
can influence the possibilities of this kind of visualization.
3.2
        </p>
      </sec>
      <sec id="sec-3-2">
        <title>The data</title>
        <p>EC-TEL conference Our first scope was to visualize all the publications from
all editions of one conference. We extracted metadata from papers and put them
in a database. Unfortunately this extraction process is still very error prone and
a lot of semi-manual cleaning up needed to be done. The approach took quite a
bit of effort and is not very scalable.</p>
        <p>To try and make access to these publication data easier, we propose an open
architecture for exchanging these publication metadata. This architecture is
currently being discussed and developed in the STELLAR project4, with both
suggestions for collecting these data using BuRST feeds5 and a webservice API,
called research.fm6, to make them available for tools and widgets like the one
we are describing in this paper.</p>
        <sec id="sec-3-2-1">
          <title>4 http://www.stellarnet.eu/</title>
        </sec>
        <sec id="sec-3-2-2">
          <title>5 http://stellarnet.eu/d/6/3/BuRST format adaption discussion</title>
        </sec>
        <sec id="sec-3-2-3">
          <title>6 http://www.stellarnet.eu/d/6/3/KULDocumentation</title>
          <p>3.3</p>
        </sec>
      </sec>
      <sec id="sec-3-3">
        <title>The network and the visualization</title>
        <p>The obvious relations to visualize are the paper-author relations, and also
coauthorship. To build up this network, we want to have a self-organizing and
selfdeclutering algorithm. We chose to use Traer Physics7, an implementation of a
simple particle system physics engine, which allows to combine a spring-graph
algorithm with physical forces. This combination will take care of the organizing
and declutering of the network, so we don’t have to care about where to put the
nodes. After experimenting with the parameters such as force, drag, mass of the
particles, spring length and strength, ... We could see a clear network-like graph
appearing when the network is stabilizing after a few seconds.</p>
        <p>The second use case described in section 2.2 benefits from the view as shown
in Figure 2. Here the visualization is zoomed in on a specific target. All the
author names become clearly visible, so you can find an author very relevant for
your work. One can also click on some paper nodes to get more information on
the paper itself, so to find papers that are interesting, for example because they
are closely related to your work. As you can see we are already experimenting
with varying the node size of the author, based on his number of publications,
to denote importance of this author.
4</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>Related Work</title>
      <p>There are numerous other visualizations of publication data existing already.
In this section we will highlight some visualizations that try to solve similar
problems, and we will shortly describe how each of them differ from our approach.
4.1</p>
      <sec id="sec-4-1">
        <title>Papercube</title>
        <p>
          When this web application8 first opens up, it immediately shows you a search
box. This is useful when you are looking for something more specific, but it
does not help when you want to explore the publication space and don’t have a
specific entry point in mind. There are quite some possibilities both in terms of
relations and type of visualizations, so it can take a while for someone to get used
to the interface and find what one actually wants. In our approach on the other
hand, we want to make it easy for starting the exploration phase by directly
showing the data. In this visualization the data is shown in a spring graph with
a good lay-out. When you hover over a paper, the relations to other papers are
highlighted, which is very helpful. One can also directly click through to the
paper itself, so if you have found an interesting publication you can directly
retrieve it online. Bergstr¨om et al [
          <xref ref-type="bibr" rid="ref1">1</xref>
          ] evaluated this application, and found that
the users unanimously said that this kind of visualization can usefully augment
existing digital libraries.
4.2
        </p>
      </sec>
      <sec id="sec-4-2">
        <title>Ed-Media Relation Browser</title>
        <p>
          The Ed-Media Relation Browser9 is also an interactive, browser based, author
visualization. In this approach they focus on one person and its direct relations,
assisted with a strong filtering mechanism. The visualization only starts after
you have entered a name. This emphasizes their focus on solving the problem
of getting to know closely related authors. It does not allow one to study the
field nor to discover the indirect relations between authors and papers. In our
approach we try to solve this problem by allowing to zoom in on a specific
person, but with a global navigation strategy so that the overview does not get
lost. This visualization does not allow to rearrange the graph. To help the spatial
memory we allow the user to organize the papers and authors however he likes.
The authors, Ochoa et al [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ], have also studied the complete publication space
of a conference, but only with non interactive visualizations, where we allow to
do so with a highly interactive visualization.
4.3
        </p>
      </sec>
      <sec id="sec-4-3">
        <title>Microsoft Academia Search Visual Explorer</title>
        <p>The Microsoft Academia Explorer10 is similar to the Edmedia Relation Browser.
Here you can drag the authors around to get a better view if something is not</p>
        <sec id="sec-4-3-1">
          <title>8 http://papercube.peterbergstrom.com</title>
        </sec>
        <sec id="sec-4-3-2">
          <title>9 http://ariadne.cs.kuleuven.be/edmedia/ 10 http://academic.research.microsoft.com/VisualExplorer.aspx</title>
          <p>clear. Once you click on an other author, the graph keeps the link with the
previous author but unfortunately all not directly related authors get thrown
away. Thus also this visualization only displays direct relations. This application
is also only targeted at visualizing authors. One can click through to see all the
details of an author, but it is not possible to see the publication which make
authors related. Our approach makes the transition from exploration to reading
papers easier by bringing the papers visually in the network. If a paper draws
attention, one can immediately retrieve more information from it.
5</p>
        </sec>
      </sec>
    </sec>
    <sec id="sec-5">
      <title>How to evaluate ?</title>
      <p>Due to the early stages of this work, there has not been any evaluation yet, but
we are planning to do a complete evaluation and here we outline how we will
approach this. The evaluation would be done on two levels :
Macro level We will introduce the test subjects to the application, explain
them the purpose, how it works and what are its functionalities. On this level
we want to get answers to questions like : Is this application useful ? Does it
address an actual need ? And if so, are the people aware of the existing need ?
Micro level In another evaluation, we focus more on the micro level. We want
to know if the application is usable, which functionalities and features work well
and which do not. In this evaluation the subjects would get specific tasks and
we would then record how and how fast these tasks are completed. The specific
tasks are not defined yet, but one example could be : Find the most interesting
paper written by author x.</p>
      <p>Public spaces In order to get more feedback, we also plan to deploy this
visualization at one or more conferences, where we can observe the people discovering
the tool and see what the initial thoughts are.
6</p>
    </sec>
    <sec id="sec-6">
      <title>Future work</title>
      <p>At the time of writing, a first working version of the application has been
developed with some basic functionalities. But before we can do a real evaluation
of this visualization, we need to improve the functionality of the application. In
this section we describe the next steps that will be taken to achieve this.</p>
      <p>An important feature that is missing at the moment, is being able to search
for a certain author or paper to use as a starting point for the visual exploration.
At a first stage we will add a keyboard like possibility to enter part of an author
or a paper. To show the results there are several options that can be tried out.
The found results can be highlighted in some way, or once a single result is found
the visualization can center the result and zoom in on it.</p>
      <p>At the moment it is not very visually clear yet which papers or authors are the
most important or the most relevant. We are already exploring the possibilities to
improve this by trying out filtering mechanisms and visual improvements. These
visual improvements can be highlighting certain nodes or areas, varying the size
of the nodes based on these factors, varying the strengths of the connections,
etc.
7</p>
    </sec>
    <sec id="sec-7">
      <title>Conclusion</title>
      <p>In general, the fundamental issue is to understand in a deeper way how we can
support the work of researchers with the technology that is available and how
we can evaluate that our efforts make a difference. The design based research
presented in this paper tries to move that agenda forward.</p>
      <p>A major problem we face is getting clean data. At the moment this is too
hard: we had to invest considerable effort in extracting the bibliographical data
from the PDF version of the papers and in manually cleaning up the result.
Initiatives like DBLP11, Citeseer12, bibsonomy13, citeUlike14 and others are
targeting the same issue and we need to leverage their results in the context of
our research.fm framework (see section 3.2) to create sustainable and scalable
services for basic bibliographical data provision.</p>
      <p>Assisting the user with navigation through the publication space is crucial.
It is hard to figure out the correct way to combine navigation and search for
manipulation of this information space. Currently, we only provide navigational
access and we need to augment this with search facilities to locate relevant
locations in this space: these can be papers or authors or relationships between
them. We also need to add filtering facilities to reduce the complexity and size
of this space to only that part that is relevant to the information need of an
author.</p>
      <p>We only use a fraction of the available metadata at the moment: our current
visualization focuses on (co-)authorship relations between authors and papers.
There is plenty of opportunity to also include other kinds of metadata in our
scope: this could include forward and backward citations, geospatial
information about the affiliations of the authors, textual relationships based on concept
extraction techniques, etc. Assessing which kinds of such data help to address
which kinds of problems researchers face and how we can exploit the data to
make them useful and usable to that audience is a deep design challenge.</p>
      <p>Finally, we do not exploit time information yet. However, especially as we
start adding more of the metadata to our visualization, this will become an
important concern. If we are able to integrate time information, then we can
help users understand how a domain or publication outlet (conference, journal,
11 http://www.informatik.uni-trier.de/ ley/db/
12 http://citeseer.ist.psu.edu/
13 http://www.bibsonomy.org/
14 http://www.citeulike.org/
...) evolves, how a paper gains in influence, how the collaborative relationships
between authors evolve, etc.</p>
      <p>Acknowledgements We gratefully acknowledge the financial support of the
European Commission through the STELLAR project and the STELLAR
Network of Excellence.</p>
    </sec>
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