IV2012_TRACERpresentation_PhDwork

Information Visualization Application | 13 July 2012

COMPARISON OF EMERGING INFORMATION
VISUALIZATION TOOLS FOR HIGHER EDUCATION

Marta Pinto | Rui Raposo | Fernando Ramos

Montpellier, France
1

Comparison of Emerging IV Tools for Higher Education
Marta Pinto| martapinto@ua.pt Rui Raposo| raposo@ua.pt Fernando Ramos| fernando.ramos@ua.pt

Information Visualization (IV) is being used in many fields, including Education.
In a society driven by knowledge economy, information is relevant for all the stakeholders
of any field, and Higher Education is one the many fields which are gradually grasping
the advantage of the adoption of IV solutions in activities linked to:.

• Decision making
• Sharing data and information of interest to institutions, decision makers at a political or
financial level, and to a wide range of public [Anderson,2008; Powell, 2004].
• Accessing and manipulating massive data-sets, to benefit research, help to visualize
more complex systems and strengthen international communication and collaboration
in research [OECD, 2012].

2


The evolution of IV is enabling its massive use worldwide by recognized governmental and non-
governmental organizations, institutions, services, entities, which have realized the power of this
type of communication and understanding of data and information on a large scale.

3


Over the last few years IV has also gone beyond its focus on individual singled out objects with their
own sets of variables, to increasing the number of tasks of comparison of complex data. Complex
networks represented in IV [Lima, 2011]:

4


Interest in researching IV for HIGHER EDUCATION?
• Benchmarking
exercises.
Diversity • Classifying and
European ranking HEI study
Higher transparent, programs.
Education details about • Creating quality
Area profiles.
institutions • Comparable
information.

https://www.facebook.com/ProjetoTracer
5


HIGHER EDUCATION: the vast majority of data and deriving information is not available from open
databases, this means that it will need to be collected directly from institutions, a time consuming
task for whomever collects data and for institutions who may be see it as a burden [van Vught,
2012].

Open and
public
use Use for
DATASETS research
and
knowledg
e transfer

Data regarding HE is valuable to decision makers, and its visibility on the web may give institutions
prestige, helping them attract students, scholars and financial investment [Ortega, et al, 2008;
Butler, 2012].
6


METHODOLOGY | TOOL SELECTION

Search results in 4 IV tools for European Higher Education, with data regarding the Higher Education
Intitutions, propose to map diversity of HE and characterize HEI according to their autonomy,
mobility, ranking and classification.

1*. U-MAP TOOL: a classification tool
of European HE intitutions, with a
description of the profiles through 6
comparable dimensions. Decision
makers, general public.
(ongoing, demo stage, final report)

7


2*. U-MULTIRANK TOOL: derives from U-map. A global multi-ranking tool,
aiming to allow users to select HEIs performance indicators according to
their own preferences and priorities, and define the institutional profile of
their interest. Decision makers, general public. (ongoing, final report)

3*. UNIVERSITY AUTONOMY IN
EUROPE TOOL: lets the user
compare 28 HE systems regarding
their academic, organizational,
financial and staffing autonomy.
Decision makers. (finalized)

4. MAUNIMO TOOL: aiming to draw attention to various forms
and types of academic mobility.
(ongoing) 8


METHODOLOGY | COMPARISON of TOOLS
Focusing on the design and interaction patterns of the tools, sustained on the 3 tools
compared
work of the three authors, we propose 3 tables to establish a comparison:

Heer and Shneiderman (2012) : taxonomy of tools that support the fluent and flexible use of
visualizations.
Gleicher, et al. (2008): visual comparison for IV, by. Both the work of these authors focus in a
more broad analysis of IV and its design.
Behrens (2008): comparison at a deeper level of the patterns in the IV tools, according to the
compiling of visualization methods.

* U-Multirank tool is not active online, analysis according to the information in the final report.
* U-Map tool , analysis according to the online available demonstration mode and final report.

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COMPARISON 1: Heer, Shneiderman (2012) - Taxonomy of Tools that Support the Fluent and Flexible
Use of Visualizations

PROCESS & PROVENANCE VIEW MANIPULATION DATA & VIEW SPECIFICATION

Record Annotate Share views Guide Select Navigate to Coordinate Organize Visualize Filter Sort Derive
analysis patterns to and users items to examine views for multiple data by out data items to
histories document annotations through highlight, high-level linked, windows choosing to focus expose
for findings to enable analysis filter, or patterns multi- and visual on patterns
revisitation collaboration tasks or manipulat and low- dimensiona workspace encodings relevant
, review stories. e them level detail l s items
and sharing
Tools

U-Map    

University
Autonomy    
in Europe

U-
Multirank    

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COMPARISON 2: Gleicher, et al (2011) - VISUAL COMPARISON FOR INFORMATION VISUALIZATION

Explicit
Juxtaposition Superposition representation
Tools of relations

U-Map 

University
Autonomy in
Europe 

U-Multirank * 

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COMPARISON 3: Behrens (2008) - VISUALIZATION METHODS

Tools University Interaction patterns most
U-
U-Map autonomy in
Multirank
common in use are
Visualzation Methods Europe
the selection of elements by
Discrete quantities (Simple Bar Charts, interacting with the checkboxes
Display Patterns Multiset Bar Charts and Stacked Bar   
Charts).
or dropdown menus of the
interface.
Filtering (Layering, Active Objects,
Boundary Filters, Facet Browsing and  
Dynamic Query).
Behaviour Arrangement (Selective Arrangement,
U-Map and U-Multirank tools,
Patterns Sortable Columns, Custom Dimensions   allow the users to have behavior
and Isolated Comparisons). patterns such as filtering the
Exploration ("Details on Demand" and
   information to access and
DataTips).
arranging it facilitate
Boolean selection (usually done with
interface elements such as radio buttons,  
understanding and
Interaction comparison tasks, and allowing
checkboxes, and dropdown menus)
Patterns include:
Spatial navigation (Drag and Drop and
 no data for a deeper exploration of
SelectionMasks).
data and information by giving
details on demand as well as
data tips.

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DISCUSSION & CONCLUSIONS
All tools have adopted the visual presentation of data in a sunburst layout, and only offer one
type of visualization method, what makes this set of tools limited in what it concerns the
exploration of visual displays and interface interactions design.

Each sunburst line represents a unique indicator, made up by its length, or a multitude of squares.
In University Autonomy in Europe the more squares are filled, the more autonomous the HE
system. 13


Comparison by having visual
representation of 2 or more
instituions, according to specific
variables of interest to the user.

University Autonomy tool,
comparison is not allowed by
putting the sunburst graphs side by
side, visualization is not dynamic.

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U-Multirank enables the creation of the user-selected groups of sufficiently comparable
institutions.

This two-step approach is completely new in international and national rankings.

3 set of tools are very similar in the visualization , and have non hierarchical data presentation.

2 set of tools are very similar in the interactions provided.

In such a strong social web context, it is noted that none of the IV tools allow the user to
collaborate, annotate or share visualizations.

There would be advantages to allow the user to save the result of his interaction patterns, and
to be able to export the visualization, or share it with others on the social web.

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Information Visualization Application | 13 July 2012

THANK YOU!

COMPARISON OF EMERGING IV TOOLS FOR
Marta Pinto| martapinto@ua.pt Rui Raposo| raposo@ua.pt HIGHER EDUCATION
Fernando Ramos| fernando.ramos@ua.pt

This research is financed by FEDER grants under Programa Operacional Factores de Competitividade – COMPETE and by National Funds16
under FCT – Fundação para a Ciência e Tecnologia PTDC/CPECED/113368/2009COMPETE:FCOMP-01-0124-FEDER-014394

IV2012_TRACERpresentation_PhDwork

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