Diagrammatic Representation and Inference: 8th International Conference, Diagrams 2014, Melbourne, VIC, Australia, July 28 – August 1, 2014. Proceedings

325 Pages·2014·11.389 MB·English

by  Tim Dwyer, Helen Purchase, Aidan Delaney (eds.)

Tim Dwyer
Helen Purchase
Aidan Delaney (Eds.)
Diagrammatic
8 Representation and
7
5
8

AI Inference
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8th International Conference, Diagrams 2014
Melbourne, VIC, Australia, July 28 – August 1, 2014
Proceedings
123
Lecture Notes in Artificial Intelligence 8578
Subseries of Lecture Notes in Computer Science
LNAISeriesEditors
RandyGoebel
UniversityofAlberta,Edmonton,Canada
YuzuruTanaka
HokkaidoUniversity,Sapporo,Japan
WolfgangWahlster
DFKIandSaarlandUniversity,Saarbrücken,Germany
LNAIFoundingSeriesEditor
JoergSiekmann
DFKIandSaarlandUniversity,Saarbrücken,Germany
Tim Dwyer Helen Purchase
Aidan Delaney (Eds.)
Diagrammatic
Representation and
Inference
8th International Conference, Diagrams 2014
Melbourne,VIC,Australia,July28–August1,2014
Proceedings
1 3
VolumeEditors
TimDwyer
MonashUniversity
POBox197,CaulfieldEast,VIC3145,Australia
E-mail:[email protected]
HelenPurchase
UniversityofGlasgow
UniversityAvenue,Glasgow,G128QQ,UK
E-mail:[email protected]
AidanDelaney
UniversityofBrighton
LewesRoad,Brighton,BN24GJ,UK
E-mail:[email protected]
ISSN0302-9743 e-ISSN1611-3349
ISBN978-3-662-44042-1 e-ISBN978-3-662-44043-8
DOI10.1007/978-3-662-44043-8
SpringerHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2014942442
LNCSSublibrary:SL7–ArtificialIntelligence
©Springer-VerlagBerlinHeidelberg2014
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Preface
The 8th International Conference on the Theory and Application of Diagrams
(Diagrams 2014) was held in Melbourne, Australia, during July and August
2014.For the second time, Diagrams was co-locatedwith the IEEE Symposium
on Visual Languages and Human-Centric Computing. Prior to Diagrams 2014,
the Diagrams 2008 co-location with the VL/HCC produced lively interaction
between the delegates of both conferences. At the 2014 conference we again
found that co-location stimulated inter-community debate.
Contributers to Diagrams 2014 continued to interpret the meaning of “dia-
gram”broadly,asbefitsanintentionallyinterdisciplinaryconference.Thisledto
the wide spectrum of papers found in this proceedings volume, covering the ar-
easofdiagramnotations,diagramlayout,diagramtools,diagramsineducation,
empirical studies of diagrams, and diagrammatic logic.
Submissions to Diagrams 2014 were soclicited under the categories of full
papers, short papers, and posters. The peer-review process entailed each paper
being reviewed by three members of the Program Committee or a nominated
sub-reviewer.For the firsttime inthis conference series,authors wereinvited to
commentonthereviewers’feedbackinarebuttalphase.Boththeoriginalreview
and the author rebuttal were considered when making acceptance decisions.
The process of selecting high-quality papers for the conference and for this
proceedings volume would have been impossible without the commitment and
efforts of the 39 members of the Program Committee and the eight additional
reviewers—we aregratefulto them. Atotalof40submissionswerereceived,of
which 15 were accepted as full papers. A further nine papers were presented at
the conference as short papers, together with six posters.
In addition to the research program, Diagrams 2014 included a graduate
symposiumandtwotutorialsessions.The two invitedtalkswerekeynote events
shared between Diagrams and VL/HCC, and reflected the Oceaniac location of
the conference — we are greatful to our invited speakers Peter Eades of the
University of Sydney and Kim Marriot of Monash University.
We acknowledge and appreciate the considerable assistance of the adminis-
tration team at Monash University for their help in organizing Diagrams 2014.
We thank the MonashImmersive Analytics project who havecontributed spon-
sorship,furthermorethegraduatesymposiumranwiththecontinuedsupportof
the US NSF to whom we are also thankful. Finally, we are immensely grateful
to John Grundy for all ofhis help in bringingDiagrams andVL/HCC together.
April 2014 Tim Dwyer
Helen C. Purchase
Aidan Delaney
Organization
Executive Commitee
General Chair
Tim Dwyer Monash University, Australia
Program Chairs
Aidan Delaney University of Brighton, UK
Helen C. Purchase University of Glasgow, UK
Workshops Chair
Karsten Klein University of Sydney, Australia
Tutorials Chair
Michael Wybrow Monash University, Australia
Graduate Symposium Chair
Stephanie Schwartz Millersville University, USA
Treasurer
Cagatay Goncu Monash University, Australia
Publicity Chair
Jim Burton University of Brighton, UK
Program Committee
Gerard Allwein US Navy Research Lab, USA
Dave Barker-Plummer Stanford University, USA
Lisa Best University of New Brunswick, Canada
Alan Blackwell Cambridge University, UK
Paolo Bottoni University of Rome, Italy
Sandra Carberry University of Delaware, USA
B. Chandrasekaran Ohio State University, USA
Peter Cheng University of Sussex, UK
Lopamudra Choudhury Jadavpur University, India
James Corter Columbia University, USA
Phil Cox Dalhousie University, Canada
VIII Organization
Richard Cox Monash University, Australia
Frithjof Dau SAP
Jim Davies Carleton University, Canada
Stephanie Elzer-Schwartz Millersville University, USA
Jacques Fleuriot University of Edinburgh, UK
Jean Flower Autodesk
Ashok Goel Georgia Institute of Technology, USA
Mary Hegarty University of California, Santa Barbara, USA
John Howse University of Brighton, UK
Mateja Jamnik University of Cambridge, UK
John Lee University of Edinburgh, UK
Emmanuel Manalo Waseda University, Japan
Kim Marriott Monash University, Australia
Nathaniel Miller University of Northern Colorado, USA
Mark Minas Universita¨t der Bundeswehr Mu¨nchen,
Germany
Ian Oliver HERE.com
Luis Pineda-Cortes Universidad Nacional Aut´onoma de M´exico,
Mexico
Beryl Plimmer University of Auckland, New Zealand
Peter Rodgers University of Kent, UK
Frank Ruskey University of Victoria, Canada
Atsushi Shimojima Doshisha University, Japan
Sun-Joo Shin Yale University, USA
Gem Stapleton University of Brighton, UK
Nik Swoboda Universidad Polit´ecnica de Madrid, Spain
Ryo Takemura Nihon University, Japan
Barbara Tversky Columbia and Stanford, USA
Yuri Uesaka The University of Tokyo, Japan
Michael Wybrow Monash University, Australia
Additional Reviewers
Andrew Blake Sonja Maier
Jim Burton Petros Papapanagiotou
Peter Chapman Sahand Saba
Veronika Irvine John Taylor
Keynote Talks (Abstracts)
What Is a Good Diagram? (Revisited)
Peter Eades
School of Information Technologies, University of Sydney
[email protected]
Graphshavebeen broadlyusedto model binaryrelationssince the beginning of
Computer Science. Nodes represent entities, and edges represent relationships
between entities. Such models become more useful when the graph model is
represented as a diagram, because visualization of a graph enables humans to
understand the underlying model.
Aqualitymetricassignsanumberq(D)toeachdiagramD suchthatq(D)is
larger than q(D(cid:2)) when D is a higher quality diagram than D(cid:2). Quality metrics
for graph visualization have been discussed since the 1970s. Sugiyama et al. [6]
wrote lists of quality metrics and his subsequent book [5] contains an extensive
discussion. The seminal paper What is a good diagram? by Batini et al.[1] pre-
sented guidelines for database diagrams. These early works were entirely based
on intuition and introspection; later Purchase et al. [4] began the scientific in-
vestigation of quality metrics with a series of experiments that validated some
of the metrics.
Of course, the quality of a diagramis “a hopeless matter to define formally”
[1]: quality depends on specific users, specific tasks, and rather informal and
subjective notions of aesthetics. Nevertheless, formal quality metrics are helpful
if not essential in the design of automatic graphvisualization methods, because
suchmethodsareoptimisationalgorithmswithqualitymetricsasobjectivefunc-
tions. As an example, it is well established that edge crossings in a diagram
inhibit human understanding, and edge crossings form the basis of so-called
“planarity-based”quality metrics. Methods that reduce the edge crossings have
received considerable attention in the literature (see, for example, [2]).
In this talk we review the history of quality metrics for graph visualization,
and suggest a new approach.
The new approachis motivated by twoobservations:(1)the size ofdata sets
is much larger now than ever before, and it is not clear that established quality
metrics are still relevant, and (2) there is a disparity between methods used in
practice and methods used in academic research.
Using a pipeline model of graph visualization, we classify quality metrics
into “readability” metrics and “faithfulness” metrics. Readability metrics mea-
sure how well the human user perceives the diagram; these metrics have been
extensivelyinvestigatedandtheyare(atleastpartially)understood.Faithfulness
metrics(see [3])measurehowwellthediagramrepresentsthedata;thesemetrics
are not well developed and they are poorly understood.
We argue that faithfulness metrics become more relevant as the data size
increases, and suggest that the commercial dominance of stress-based methods
XII P. Eades
over of planarity-based methods is somewhat due performance on faithfulness
metrics.
We introduce some specific faithfulness metrics aimed at large graphs. In
particular,wesuggestthatmetricsbasedonproximitygraphs(see[7])mayplay
a key role.
Much of this talk is basedon joint workand discussions with KarstenKlein,
SeokHee Hong, and Quan Nguyen, among others.
References
1. Batini,C.,Furlani,L.,Nardelli,E.:Whatisagooddiagram?apragmaticapproach.
In: Proceedings of the Fourth International Conference on Entity-Relationship
Approach, pp. 312–319. IEEE Computer Society, Washington, DC (1985), http:
//dl.acm.org/citation.cfm?id=647510.726382
2. Ju¨nger,M.,Mutzel,P.:Maximumplanarsubgraphsandniceembeddings:Practical
layout tools. Alogrithmica 16, 33–59 (1996)
3. Nguyen, Q.H., Eades, P., Hong, S.H.: On the faithfulness of graph visualizations.
In:2013IEEEPacificVisualizationSymposium(PacificVis),pp.209–216(February
2013)
4. Purchase, H.C., Cohen, R.F., James, M.: Validating graph drawing aesthetics.
In: Brandenburg, F.J. (ed.) GD 1995. LNCS, vol. 1027, pp. 435–446. Springer,
Heidelberg (1996), http://dx.doi.org/10.1007/BFb0021827
5. Sugiyama, K.: Graph drawing and applications for software and knowledge engi-
neers. World Scientific(2002); Japanese language version 1993
6. Sugiyama,K.,Tagawa,S.,Toda,M.:Methodsforvisualunderstandingofhierarchi-
cal system structures.IEEE Transactions on Systems,Man and Cybernetics 11(2),
109–125 (1981)
7. Toussaint,G.T.:Agraph-theoreticalprimalsketch.In:ComputationalMorphology,
pp.229–260. North-Holland (1988)