Automatic Layout of Structured Hierarchical Reports
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Citation
Bakke, Eirik, David R. Karger, and Robert C. Miller. “Automatic
Layout of Structured Hierarchical Reports.” IEEE Trans. Visual.
Comput. Graphics 19, no. 12 (2013): 2586–2595.
As Published
http://dx.doi.org/10.1109/tvcg.2013.137
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Institute of Electrical and Electronics Engineers (IEEE)
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Author's final manuscript
Accessed
Thu May 26 20:57:03 EDT 2016
Citable Link
http://hdl.handle.net/1721.1/87067
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Automatic Layout of Structured Hierarchical Reports
Eirik Bakke, David R. Karger, and Robert C. Miller
Fig. 1. Interactive adaptation of the layout of the data to be displayed, based on the available horizontal width of an on-screen window.
Abstract—Domain-specific database applications tend to contain a sizable number of table-, form-, and report-style views that must
each be designed and maintained by a software developer. A significant part of this job is the necessary tweaking of low-level
presentation details such as label placements, text field dimensions, list or table styles, and so on. In this paper, we present a
horizontally constrained layout management algorithm that automates the display of structured hierarchical data using the traditional
visual idioms of hand-designed database UIs: tables, multi-column forms, and outline-style indented lists. We compare our system
with pure outline and nested table layouts with respect to space efficiency and readability, the latter with an online user study on
27 subjects. Our layouts are 3.9 and 1.6 times more compact on average than outline layouts and horizontally unconstrained table
layouts, respectively, and are as readable as table layouts even for large datasets.
Index Terms—Hierarchy data, tabular data, nested relations, layout management
1
I NTRODUCTION
An important class of visualizations in everyday business use consists
of the table-, form-, and report-style views found in most graphical
relational database applications [2]. The data being displayed is typically structured, meaning that each value has an associated type and
label in a schema. Furthermore, the data frequently needs to be presented in a hierarchical manner, because of the need to visualize oneto-many relationships between entities in the database. For instance,
when users request “a list of employees, grouped by department” or
“all information about a customer, including associated support tickets and a list of open orders,” what is being displayed is a structured
hierarchical view of the underlying relational data.
Unlike other kinds of office productivity software, database applications tend to be tailored for specific target domains such as payroll,
customer relationship management (CRM), or inventory tracking, or
even more specific subdomains such as hotel reservation systems, inventory management for the offshore industry, or bug tracking systems for software developers [1]. The domain-specific nature of these
systems makes them costly to develop and maintain, and there is seldom an opportunity to hire a graphic designer every time a new form
needs to be created or an existing one updated. Yet, the software developer must invariably define the details of the view’s visual layout:
the location of labels, the dimensions of text fields, the width of table
• Eirik Bakke is at the MIT Computer Science and Artificial Intelligence
Laboratory (CSAIL). E-mail: ebakke@mit.edu.
• David R. Karger is at MIT CSAIL. E-mail: karger@mit.edu.
• Robert C. Miller is at MIT CSAIL. E-mail: rcm@mit.edu.
Manuscript received 31 March 2013; accepted 1 August 2013; posted online
13 October 2013; mailed on 4 October 2013.
For information on obtaining reprints of this article, please send
e-mail to: tvcg@computer.org.
1077-2626/13/$31.00 © 2013 IEEE
columns, the organization of form fields into columns on a page, and
so on. Since each database application can contain a sizable number of
views—say, one table view and one form view per major (non-weak)
entity type in the database schema, plus any special-purpose report
views—maintaining the detailed visual layouts of each view is a significant development burden, and can lead to poor user interfaces.
The problem we approach in this paper is as follows: How can the
visualizations required of typical domain-specific database applications be generalized in such a way as to eliminate the need for manual
tweaking of low-level visual details? A general-purpose visualization
system for nested relations data would be of direct utility to any one of
many [15, 29, 27, 28, 16, 2] previously proposed database user interfaces based on structured hierarchical views. To scope our problem,
we limit ourselves to the task of displaying simple textual data that has
been pre-organized to conform to some hierarchical but non-recursive
schema. This includes the documents of most data interchange formats
based on XML and JSON, as well as the output of any object-relational
or relational-to-XML mapping system that uses a finite number of
standard SQL queries to produce its output, e.g. SilkRoute [8]. An
equivalent data model is the nested relational model; see Levene [18]
for an extensive bibliography.
We present a layout management algorithm that automates the display of structured hierarchical data using visual idioms seen in traditional hand-designed database UIs: tables, multi-column forms, and
outline-style indented lists. The system gathers simple statistics about
fields in the input schema, and uses these to make layout decisions
which are then applied uniformly across tuples in each input subrelation. We compare our hybrid layout system with pure outline and
nested table layouts with respect to space efficiency and readability,
the latter with an online user study on 27 subjects. Our layouts are 3.9
and 1.6 times more compact on average than outline layouts and horizontally unconstrained table layouts, respectively, and are as readable
as table layouts even for large datasets.
Published by the IEEE Computer Society
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2
R ELATED W ORK
Tree Visualization. While our layout algorithm assumes the presence
of a schema along with its hierarchical input data, it is always possible
to derive a valid schema from the input data itself, and our system
supports the visualization of any tree-structured input data in XML or
JSON form, without further annotation. Our visual layouts make the
most sense in cases where the schema can correctly be assumed to be
non-recursive, which was the case for 9 out of 10 example datasets in
the XML corpus we used for our user study. Thus, our system falls into
the tree visualization category of information visualization research.
Most differences arise from our assumption of a different variation of
the tree-structured input data model than is typically seen in other tree
visualization systems. Analogous data model specialization is seen for
instance in Robertson’s polyarchies [23]. While our system does not
perform any kind of aggregation on input data, but merely displays
every piece of data in full, the same is true of many standard kinds of
tree visualizations.
Academic research on visualizations for tree-structured data has
been surveyed by Shneiderman [24] and, recently, Graham and
Kennedy [11]. In our case, we are dealing with the subproblem of
single tree visualization, with the additional constraint that we are
working with structured data only, i.e. data that conforms naturally
to some schema. In Graham’s taxonomy, the visualizations produced
by our system form a hybrid between the nested and indented list representations. While nested tables, an important base case in our layout
system, organize data in a grid of rows and columns, they do not fall
into the matrix representation category, but rather among the nested
representations, since data leaf nodes are always contained within the
visual boundaries of their parent nodes.
The study by Chimera and Shneiderman [6] compared three variations of the outline-style indented list view; two of these were interactive. Their results suggest that future versions of our system should
include collapsible nodes in indented lists. Ziemkiewicz et al.[31]
compare four different classes of tree visualizations, including three
nested variants. None of the layouts tested include tables or hybrids
between tables and indented list representations. Ghoniem et al. [10]
provide a taxonomy of readability tasks on graphs and present a study
comparing node-link and matrix representations.
Treemap [14] is maybe the most well-known nested or Venn
Diagram-style tree representation. Treemaps fit an arbitrarily sized
tree into a viewport of pre-defined dimensions, by making subsequent
levels smaller and smaller. The relative size of siblings is determined
by some semantically significant weight associated with each node in
the tree, such as disk space consumed in a map of a file system hierarchy. In contrast, our own system allocates to leaf nodes whatever
visual space is necessary to display the contained primitive text values
at a constant font size. This is a requirement from the perspective of
our target applications. Our system does, however, constrain layout
dimensions in the horizontal direction, so that only vertical scrolling
is needed if the layout can not fit in the desired viewport. In treemaps,
siblings are arbitrarily stacked vertically or horizontally at every other
step in the recursion. In our own system, tuples are always stacked
vertically. Fields are stacked either horizontally, when contained in
a nested table, or vertically, when part of an outline view. This ensures one kind of visual consistency while still allowing the widths of
layouts to be constrained.
FISH [20] is a variation of the Treemap concept. In this system,
styling attributes can be used to configure various node presentation
details, including the choice to stack siblings either vertically or horizontally. Such styling must be applied to each individual data node,
unlike in our own system, where styling is applied to schema nodes
only. Strip Treemap [3] optimizes the presentation of a treemap by
sizing rectangles such that they can be stacked in contiguous “strips”
without broken horizontal lines. Like Treemap, and unlike our own
system, both FISH and Strip Treemap assume that all data must fit
into a viewport of predetermined size both in the horizontal and vertical direction.
Elastic Hierarchies [30] and EncCon [21] both combine node-link
representations with some other representation in order to visual-
ize tree-structured data. Node-link representations are typically less
space-efficient than nested or indented representations, and seldom appear in traditional database GUIs, our target application. Thus, we did
not use them ourselves. EncCon uses node-link representations in every level of the tree, but maintains an invisible Treemap-like layout
to determine a favorable positioning for each node. In Elastic Hierarchies, subsequent levels may use either Treemaps or node-link representations, determined interactively. The Elastic Hierarchies paper
also has a relevant discussion of the design space of hybrid tree layouts, but does not consider nested tabular layouts. Neither does Graham and Kennedy’s survey. This is likely because tabular layouts apply only to structured data, where series of children in a tree all can be
expected to have the same substructure. Systems that solve the more
general problem of dealing with semi-structured (schema-free) data
will not naturally be able to take advantage of tabular layouts.
XML Visualization. VisualXML and XMLAD [7], like Elastic
Hierarchies and EncCon, use node-link representations as part of their
interface, but are geared towards XML visualization. The XMLAD
system does indeed use tabular representations as part of the output
layout, but does not support nested tables. Thus, only the bottom logical relations in the data may be displayed as tables. Similarly, the
VisualXML system uses outline or list-style representations for the
bottom relation level of each subtree. Again, both XMLAD and VisualXML use a node-link representation for all higher levels. This is
in contrast with our own system, which uses a column-enabled, indented list for a variable number of top levels in the tree, followed by
nested tables for a variable number of bottom levels. Furthermore, our
algorithm makes these layout decisions automatically, except where
manually overridden.
Tree Rewriting provides a visual language “very similar to the
lambda calculus in simplicity and expressive power” [13]. While such
systems are general enough to produce just about any layout from a set
of input data, a user must manually specify how these layouts are to
be constructed. Unlike our system, neither is able to produce a default
layout subject to a constraint such as available page width. Furthermore, no mechanism is available to help ensure the careful alignment
of column fields that is required in order to produce tabular or nested
tabular sublayouts.
A relevant class of commercial systems consists of report generator tools such as Crystal Reports1 and Altova XML-Spy/StyleVision2 .
An extensive survey is provided by Król [17]. These systems let the
user build output layouts analogous to those produced by our own system, using a variety of input data sources. The layout building process
is manual. Altova’s “Grid View” is similar to a nested table view,
but with single-level column headings repeated for every subrelation.
Navigation requires heavy use of both vertical and horizontal scrollbars as well as manual collapsing and expanding of data nodes. Altova
does combine vertical arrangements of tuple fields in an outline-style
sub-view with the use of nested tables, but is unable to render subrelations as indented lists.
UI Generation. Supple [9] generates widget-based user interfaces
for devices of various sizes and contexts using a cost optimization
algorithm, but does not deal with table layouts or other layouts that
take advantage of repeated structure in data that adheres to a schema.
The Right/Bottom strategy [4] defines heuristics for widget placement in dialog boxes, but similarly does not deal with structured relational data. Database application builder tools such as FileMaker3
and Microsoft Access4 include wizards to help with the creation of
new forms, but are only able to layout out a single level of fields automatically, and can not use statistics about the data in each field to
make structural layout decisions.
Tabular Systems. Show Me [19] is an autostyling system for
Tableau, an interactive visualization system. Since Tableau operates
on tabular input data and produces Pivot-table or cross-tab-based out1 http://crystalreports.com
2 http://www.altova.com/xml-editor
3 http://www.filemaker.com
4 http://office.microsoft.com/access
CEE 471
GEO 471
Sections
Place
History of the Earth
Days
P 01
206
13:30:00 GEO
14:20:00
GUYOT 155
15:30:00 16:20:00 GUYOT 154
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425
09:30:00 MAE
10:50:00
FRIEN 008
GEO 425
Instructors
First
Primitive Values
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Th
58
Y
Other
Middle
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Thomas
S.
Duffy
Thomas
Nicole
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Mark
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Peter
Jeffery
40 N
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30 N
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Scott
This course examines about 15 seminal events in
natural history, and how those events shaped the
modern environment. The first section covers the origin
of the Universe, chemical elements, and solar system.
After a discussion of the structure and dynamics of the
Earth, we next examine the origin of life, evolution of
eukaryotic cells and multicellularity, the evolution of
vertebrates (amphibians, dinosaurs, and mammals),
and mass extinctions. The final section discusses the
origin of man, the ice ages, and global change. 206a: 3
lectures; 206b: three lectures, 1 three-hour laboratory.
History of the Earth
This course examines about 15 seminal events in
natural history, and how those events shaped the
modern environment. The first section covers the origin
of the Universe, chemical elements, and solar system.
After a discussion of the structure and dynamics of the
Earth, we next examine the origin of life, evolution of
eukaryotic cells and multicellularity, the evolution of
vertebrates (amphibians, dinosaurs, and mammals),
and mass extinctions. The final section discusses the
origin of man, the ice ages, and global change. 206a: 3
lectures; 206b: three lectures, 1 three-hour laboratory.
The Physical Earth
An introduction to geology and geological processes.
Topics include the physical processes occurring within
the earth, including plate tectonics, formation of
minerals and rocks, earth structure, earthquakes,
faults, and mountain building, as well as the physical
processes that transform the earth's surface, including
weathering and erosion, flooding, landslides and the
development of landscape. Recommended for those
interested in majoring in the Geosciences.
Introduction to Physical Oceanography The study of the oceans as a major influence on the
atmosphere and the world environment. The contrasts
between the properties of the upper and deep oceans;
the effects of stratification; the effect of rotation; the
wind-driven gyres; the thermohaline circulation.
11:00:00 11:50:00 GUYOT 10
GEO 235
CEE 235
An introduction to the science of water quality
management and pollution control in natural systems;
fundamentals of biological and chemical
transformations in natural waters; indentification of
sources of pollution; water and wastewater treatment
methods; fundamentals of water quality modeling.
Day
Number
Format
End
Time
GEO 206
40
N
courseinfo.princeton.edu/courses/geo206ageo206b_F2000/index.html
Duffy
Gotberg
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Final
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20
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Bennett et al.
Consolmagno and
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Title
The Planetary System
The Cosmic Perspective
Worlds Apart: A Textbook in
Planetary Science
The New Solar System
33
Tchobanoglous &
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Eckenfelder
Metcalf & Eddy
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Sarah
Brian
Michael
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Water Quality
L 01
09:30:00 10:50:00 FRIEN 008
Principles of Water Quality
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Wastewater Engineering
Chemistry for Environmental
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Earth System Science
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10:00:00 10:50:00 GUYOT 220
Earth System Science
B 01
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13:30:00 16:20:00 GUYOT 178
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11:00:00 12:20:00 GUYOT 220
B 01
13:30:00 16:20:00 GUYOT 178
L 01
10:00:00 10:50:00 GUYOT 154
10
20
Lab Reports
Other Exam
Papers
Quizzes
20
50
20
10
Kump, Kasting and
Crane
Lab Reports
MidTerm
Exam
Final Exam
40
30
Press, Siever,
Grotzinger, Jordan
MidTerm
Exam
Final Exam
Problem Set
(s)
20
Pond & Pickard
40
40
Pickard & Emery
Days
11:00:00 11:50:00 GUYOT 10
Label for Primitive Field
Other Exam
Term Paper
(s)
Quizzes
Papers
Place
Understanding Earth
30
Introductory Dynamical
Oceanography, 2nd ed.
Descriptive Physical
Oceanography: An Introduction
Open University Course Ocean Circulation (2001)
Team
Open University Course Waves, tides, and Shallow-Water
Team
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Instructors
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Fig. 2. The nested table layout is the most common way to visualize a nested relation, and is supported as a special case in our algorithm. Here,
we show nested relational data generated from an academic course catalog in nested table style, with one of the nested columns enlarged to show
terminology. Nested table layouts stack tuples in the vertical direction and the fields of each tuple in the horizontal direction, with all field labels
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GEO 505
Fundamentals of the Geosciences I
GEO 540
Topics in Deformation of the Upper
Crust
A year-long survey, in sequence, of fundamental
papers in the geosciences. Topics in 505 (Fall) include
the origin and interior of the Earth, plate tectonics,
geodynamics, the history of life on Earth, the
composition of the Earth, its oceans and atmospheres,
past climate. Topics in 506 (Spring) include present
and future climate, biogeochemical processes in the
ocean, geochemical cycles, orogenies,
thermochronology, rock fracture and seismicity. A core
course for all beginning graduate students in the
geosciences.
The major deformation processes of the upper crust,
above and near the brittle-plastic transition: fault
related folding, critical-taper wedge mechanics,
detachment faulting, state of stress in crust, faulting.
Topics change from year to year. Overview lectures by
the instructor, student presentations based on readings
from scientific literature and case studies.
Current problems in environmental sciences. Element
cycles; geochemistry-biotic interactions, human
impacts on the environment. A new topic is chosen
every semester. Recent topics have included: the
global carbon cycle, alternative energies, biodiversity,
genetically modified organisms, population and the
environment, media and the environment, restoration
ecology, the humanities and the environment and
architecture, urban planning and the environment, and
world oil and the Middle East.
Covers topics including origin of elements; formation of
the Earth; evolution of the atmosphere and oceans;
atomic theory and chemical bonding; crystal chemistry
and ionic substitution in crystals; reaction equilibria and
kinetics in aqueous and biological systems; chemistry
of high temperature melts and crystallization process;
and chemistry of the atmosphere, soil, marine, and
riverine environments. The biogeochemistry of
contaminants and their influence on the environment
will also be discussed
Use of scientific arguments in concert with engineering,
economic, political, and social considerations to
develop environmental policies. Class format consists
of exercises based on actual case studies related to
international agreements, environmental regulations,
climate change, natural hazards, arms control
negotiations, and national security.
30
N
Final
S 01
09:00:00 09:50:00 GUYOT 154
14:00:00 16:50:00 GUYOT 154
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F
Jorge
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Thomas
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Samuel
30
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01:30:00 03:20:00 GUYOT 154
12:30:00 13:20:00 GUYOT 154
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This course provides a broad introduction to
atmospheric science. Topics covered include
atmospheric thermodyanmics, aerosols and clouds,
radiative transfer, surface and top-of-atmosphere
energy balances, and the hydrological cycle.
Elementary principles of atmospheric dynamics and
global circulation will be presented.
20
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F
puts, it does not fall into the tree-structured data visualization category.
Nested table layouts are used in Related Worksheets [2] and in applications produced with AppForge [28] or App2You [16]. These systems do not allow the nested table layouts to be re-styled as indented
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13:30:00 16:20:00 GUYOT 178
Michael
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lists or
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Problem Set
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Introduction to Water Pollution
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L 01
P 03
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Meetings
Beg.
Time
Final
Sample Reading List
Author Name
Day
Relation Value
This course examines the major bodies of our solar
140 Y
system, emphasizing their surface features, internal
structures, and atmospheres. Topics include the origin
of the solar system, habitability of planets, and role of
impacts in planetary evolution. Terrestrial and giant
planets will be studied as well as satellites, comets, and
asteroids. Recent discoveries from planetary missions
are emphasized. The course is aimed primarily at nonscience majors.
Final Exam Grading
Type
Title
Number
Format
A Guided Tour of the Solar System
Website
Perc.
Number
Dept.
GEO 207
AST 207
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mic Perspective
part: A Textbook in
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Solar System
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Description
May Audit?
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Enrollment
Course Listings Title
ENV 524
GEO 524
Environmental Issues Seminar: The
Food Industry and The Environment
GEO 331
CHM 331
Introduction to Environmental
Geochemistry: Chemistry of the
Natural Systems
GEO 399
ENV 399
GEO 427
GEO 418
CHM 418
GEO 420
GEO 558
GEO
CHM
EEB
AST
S 01
3
255
255
255
255
Environmental Decision Making
Introduction to Terrestrial and
Planetary Atmospheres
Y
20
Y
20
N
Y
Environmental Aqueous Geochemistry Application of quantitative chemical principles to the
20
study of natural waters. Includes equilibrium
computations, carbonate system, gas exchange,
precipitation/dissolution of minerals, coordination of
trace metals, redox reactions in water and sediments.
Topics in Earth Science
Although the Milankovitch forcing (modest variations in 20
the distribution of sunlight) has been relatively
constant over the past several million years, Earth's
response started amplifying around 3 million years ago
(Ma), culminating in dramatic oscillations between
prolonged Ice Ages and brief interglacial periods such
as the present one. Recent observational and
theoretical results, especially concerning the tropics,
provide valuable clues to this puzzle whose solution is
of direct relevance to global warming issues. This
seminar will review recent developments.
Y
Seismology Seminar: Finite Frequency A full treatment of seismic tomography with an
20
Tomography
emphasis on finite-frequency interpretations
Life in the Universe
This course introduces students to a new field,
18
Astrobiology, where scientists trained in biology,
chemistry, astronomy and geology combine their skills
to discover life's origins and to seek extraterrestrial life.
Topics include: the origin of life on Earth, the prospects
of life beneath the surfaces of Mars and Europa, a
moon of Jupiter; extra-solar planets nearby that offer
targets for NASA space telescopes searching for life.
Students will experience first hand the diverse
techniques used to study extremophiles in hot springs
and on future Mars missions during a mandatory fallbreak trip to Yellowstone Park.
Igneous and Metamorphic Geology
Interpretation of earth history based on the rock
14
record. Two-one and a half hour lectures, one threehour laboratory, several one-day field trips, and an
eight-day trip during fall break
N
09:00:00 09:50:00 GUYOT 154
314
14:00:00 GEO
16:50:00
GUYOT 154
L AYOUT A LGORITHM
GEO 499
30
Investigating Natural Hazards
M
F
Jorge
Gerta
Lincoln
Thomas
We evaluate our vulnerability to natural hazards and
the impact of disasters to the United States and the
Nadine
developing world. In particular,
we explore what
constitutes a natural disaster & predict the future
humanitarian, economic,Samuel
& political impact of such
Y
Y
www.deepbio.princeton.edu or http://blackboard.
princeton.edu
Louis
Sarmiento
Keller
Steffens Hollister
S.
Duffy
12 N
McQuarrie
George Philander
H.
N
We now describe our layout algorithm. For the purposes of exhibition,
we start by discussing basic nested table and outline layouts, then discuss hybrid table/outline layouts, and finally show the complete steps
to produce the layouts automatically.
L 01
01:30:00of
03:20:00
GUYOT 154
M to produce
John
The
purpose
the algorithm
is
a compactSuppe
but read12:30:00 13:20:00 GUYOT 154
Th
able view of tree-structured input data that conforms to a non-recursive
schema, or, more precisely, nested relational data. Whenever possible,
the regularity of the input data’s schema should be used to maximize
the readability
of the data. For instance,
tabular
dataM. should
be renS 01
18:00:00 20:50:00 GUYOT 154
Th
Francois
M.
Morel
dered as a table, with proper column headings describing the name of
fields in the schema. We may not require user input informing layout
decisions beyond what can be derived from the data itself.
3.1
AOS 527
GEO 527
Atmospheric Radiative Transfer
GEO 539
Topics in Paleoecology,
Paleoclimatology, and
Paleoceanography
events given changes in sea level, climate variations, &
demographic trends. Students will work in teams to
assess risk and to develop economically realistic &
scientifically sound policy recommendations. The
results of the class will be submitted for publication,
and the class will present their analysis to the
appropriate policy-makers and/or business leaders.
Structure and composition of terrestrial atmospheres.
10
Fundamental aspects of electromagnetic radiation.
Absorption and emission by atmospheric gases. Optical
extinction of particles. Roles of atmospheric species in
Earth's radiative energy balance. Perturbation of
climate due to natural and antropogenic causes.
Satellite observations of climate system.
The application of the fossil record to specific
5
geological problems in depositional environments and
the paleoclimatic and paleoceanographic history of the
oceans are studied.
Y
Y
Nested Relations and Nested Table Layouts
Our algorithm
operates
tree-structured
data conforming
to a nonL 01
11:00:00
12:20:00 on
GUYOT
220
M
Satish
Chandra Myneni
Babu model as the
recursive schema. We have chosenWthe nested relational
concrete data model for our implementation, since it tends to lead to
S 01
13:30:00 16:20:00 GUYOT 155
M
Gregory
E.
van der Vink
Louis
Sarmiento
Keller
Steffens Hollister
S.
Duffy
McQuarrie
George Philander
H.
Suppe
simple tree traversal code. It is equally feasible to use a different treestructured data model such as that of XML, and in connection with
the user study, we did write a routine for importing arbitrary XML
documents.
The terminology of the nested relational model is as follows: A
value is either a primitive or a relation, where a relation is defined as
a set of tuples, each containing a set of fields identified by labels, each
containing a value, recursively. The schema of a value either defines
the value to be a primitive, or defines the value to be a relation, with
schemas further specified for each of the latter’s fields, recursively.
Nested relational data is most commonly illustrated in a nested table layout. An annotated example of such a layout is shown in Figure 2; it renders data about the first few courses in an academic course
catalog. A nested table layout consists of a header area (shown in
blue) and a content area (shown in beige). The header area reflects
the schema structure of the displayed nested relation, with simple labels for columns containing primitive fields and recursive labels for
columns containing relation fields. Columns containing relation fields
may recursively contain columns for either primitive or relation subfields. In the content area, tuples in the rendered relation are stacked
vertically with row separators between them. Each tuple renders its
primitive values as simple strings and its relation values recursively as
the content area of another nested table.
Other
Final
Final
MidTerm
Exam
Problem Set
(s)
Final Exam
Quizzes
30
Oral
Presentation
(s)
Final Exam
Precept
Participation
Papers
10
30
S 01
18:00:00 20:50:00 GUYOT 154
Th
Francois
M. M.
L 01
11:00:00 12:20:00 GUYOT 220
M
W
Satish
Chandra Myneni
Babu
S 01
13:30:00 16:20:00 GUYOT 155
M
Gregory
E.
van der Vink
Atmospheric Science: An
Introductory Survey
An Introduction to Dynamic
Meteorology
Houghton
The Physics of Atmospheres
Hartmann
Global Physical Climatology
Rogers & Yau
A Short Course in Cloud Physics
Morel, F.M.M. & Hering, Principles and Applications of
J.G.
Aquatic Chemistry,
2nd Edition (1993) John
Wiley & Sons, NY
L 01
08:30:00 09:50:00 GUYOT 154
T
Th
Samuel
George
H.
Philander
C 01
08:30:00 09:50:00 GUYOT 220
T
Th
Francois
Eric
M. M.
Morel
Stephan Egleston
Trends
Rhythms&Aberrations in
Global Climate, J.
Zachos
The Pliocene Paradox,
A. Federov, P. Dekens
etc.
Obliquity Pacing of
Glacial Cycles,P.
Huybers/C. Wunsch
High Latitude Influence
on Eastern Equatorial...
Z. Liu
Role of Tropics in
Changing the Response,
S.G.Philander
Guust Nolet (preprint to
be distributed in class)
J. Lunine
S 01
13:30:00 16:20:00 GUYOT 154
T
Samuel
George
H.
S 01
09:00:00 10:30:00 GUYOT 219
15:45:00 17:15:00 GUYOT 155
13:30:00 14:50:00 GUYOT 220
W
W
T
Th
Guust
L 01
Gerard
Laura
Danielle
Tullis
Edwin
Brian
Charles
Faye
M.
C.
Lewis
B 01
B 02
L 01
13:30:00 16:20:00 GUYOT 16
13:30:00 16:20:00 GUYOT 16
19:30:00 20:50:00 GUYOT 16
W
T
T
W
Lincoln
Lincoln
Lincoln
Steffens Hollister
Steffens Hollister
Steffens Hollister
S 01
19:30:00 22:20:00 GUYOT 155
M
Peter
Gregory
John
E.
Broecker
Berner & Berner
Gunter Faure
30
10
How to build a habitable planet
Global Environment
Principles and Applications of
Inorganic Chemistry
30
20
40
Other
Wallace & Hobbs
Holton
Final
Other
Other
Take-Home
Other
3.2
Other
Final Exam
Problem Set
(s)
MidTerm
Exam
Papers
Oral
Presentation
(s)
Morel
30
30
40
50
50
Other (See
Instructor)
Problem Set
(s)
Take Home
Final Exam
Other (See
Instructor)
Oral
Presentation
(s)
100
Lab Reports
Other (See
Instructor)
Paper In Lieu
of Final
Papers
Precept
Participation
20
40
25
35
25
R.B. Smith and L.J.
Siegel
Kathy B. Sheehan
Science, 292; 686-693, (2001)
Science, 312; 1485-1489 (2006)
Nature, 434; 491-494 (2005)
Nature, 427; 720-723 (2004)
Paleoceanography, 18(2), 1045
(2003)
A Breviary for Seismic
Tomography
Astrobiology: A Multidisciplinary
Approach
Windows into the Earth
Seen and Unseen Discovering
the microbes of Yellowstone
15
Best
Smith and Pun
Igneous and Metamorphic
Petrology
How Does Earth Work
40
Outline Layouts
50
50
Philander
Nolet
Dismukes
Landweber
Schmitt
Onstott
Turner
Gertsch
DiFiore
van der Vink
Nested table layouts, like the one previously seen, can quickly become
extremely wide if many fields are to be displayed. For on-screen interfaces, the need for horizontal scrolling is undesirable, and for printing
on paper, pagination in the horizontal direction is awkward. As another basic alternative to the nested table layout, we consider the outline layout, which is common among XML editing tools. Figure 3(a)
shows the same data as before rendered using such a layout.
In an outline layout, tuples are stacked vertically in an indented
bullet list fashion; we show one bullet per tuple. Unlike the nested
table layout, which puts the fields of each tuple next to each other on a
row, the outline layout stacks the tuple fields vertically as well. Thus,
having more fields in a schema makes the layout taller, not wider. In a
tuple in an outline layout, primitive fields are rendered as strings with
their respective schema labels to the left, whereas relation fields are
rendered recursively with their schema labels above, extended to the
full width of the layout area. The color scheme is the same (blue and
beige) for labels and values in an outline layout as for the header and
Other
L 01
09:00:00 10:20:00 GUYOT 155
Th
T
Venkatachalam
Ramaswamy
Other
S 01
10:00:00 13:00:00 GUYOT 16
T
Gerta
Keller
(a) Outline layout
Title
Description
Title Final Exam
Perc. 20
•
Title Precept Participation
Perc. 10
•
Title Other Exam
Perc. 20
•
Title Problem Set(s)
Perc. 20
Sample Reading List
•
Author Name Morrow and Owen
Title
The Planetary System
•
Author Name Beatty et al.
Title
The New Solar System
Day W
•
Day F
•
Author Name Consolmagno and Schaefer
Title
Worlds Apart: A Textbook in Planetary Science
P 01
13:30:00 14:20:00 GUYOT 155
M
W
F
T
•
Author Name Beatty et al.
Title
The New Solar System
P 03
15:30:00 16:20:00 GUYOT 154
W
P 04
19:00:00 19:50:00 GUYOT 154
W
P 05
11:00:00 11:50:00 GUYOT 154
Th
L
01
Beg.
Time
End
Time
Place
Days
11:00:00 11:50:00 GUYOT 10
Instructors First
Thomas
•
Format
Number
Meetings
Middle
S.
M
W
F
•
•
Format
Number
Meetings
Last
Duffy
End
Time
Place
P
03
Beg.
Time
•
Place
Course
Listings
Max.
Enrollment
May Audit?
Website
Title Exam Type
Final
Description
Grading
Days
Day
End
Time
Sample Reading
List
Sample Reading
List
(d) Hybrid layout with justified tables
Sections
Sample Reading
List
Sample Reading
List
Sections
Sections
Course Listings
Course
Title Listings
Description
Day
•
•
(f) Schema-only hybrid layout used to partition columns in (e)
•
Title
Description
Course Listings
Sample Reading
List
Sections
•
Sample Reading
List
Course Listings
Sections
Title
Description
Perc.
Title
Description
Max. Enrollment
May Audit?
Website
Sample Reading
Final Exam Type
List
Grading
Sections
Day
Number
Format
•
Duffy
Gotberg
Miller
Duffy
Gotberg
Miller
Gotberg
Miller
Gotberg
Miller
Number
Day
•
Author Name Eckenfelder
Website
Title
Principles of Water Quality Management
FinalInstructors
Exam Type Other
•
First Nicole
Grading
Title
Perc.
•
Author Name Metcalf & Eddy
Middle KDesign Project(s)
33
Title
Wastewater Engineering
Last
Gotberg
Quizzes
66
Other (See Instructor)
1
•
Author Name Sawyer & McCarty
•
First Mark
Sample Reading Author Name
Title
Title
Chemistry for Environmental Engineers
Middle A.
List
Tchobanoglous & Schroeder
Water Quality
Last
Miller
Sections
Eckenfelder
Principles of Water
Quality Management
•
Format
L
Metcalf & Eddy
Wastewater Engineering
Number Engineers
01
•
Format
PSawyer & McCarty
Chemistry for Environmental
Meetings Beg.
End
Place
Days
Number
05
Sections
Format Number Meetings
Instructors
TimeMiddleTime
Meetings
Place
Days
Last
Beg.
End
First
•
Beg. Time 11:00:00
Time
Time
Day
09:30:00 10:50:00 FRIEN 008
T
End TimeL 11:50:00
01
09:30:00 10:50:00 FRIEN 008
T
Peter
R.
Jaffe
Th
Place
GUYOT 154
Jeffery
Scott
Paull
Th
Instructors First
Middle Last
Days
Peter
R.
Jaffe
Course Listings
Number
•
Day Dept.
Th
Jeffery
Scott
Paull
GEO 206
Title
History of the Earth
Instructors
Description
This course examines about 15 seminal events in natural history, and
those
events shaped the modern environment. The
• how
Course
Listings
•
First Nicole
first section covers the origin of the Universe, chemical elements, and solar system. After a discussion of the structure and
Middle Kdynamics of the Earth, we next examine the origin of life, evolution of eukaryotic cells and multicellularity, the evolution of
Last
Gotberg
vertebrates (amphibians, dinosaurs, and mammals), and mass extinctions. The final section discusses the origin of man, the ice
GEO 206
ages, and global change. 206a: 3 lectures; 206b: three lectures, 1 three-hour laboratory.
•
First Mark
Title
History of the Earth
Max. Enrollment 40
Middle A.
Description
This course examines about 15 seminal events
May Audit?
N
in natural history, and how those events
Last
Miller
Website
courseinfo.princeton.edu/courses/geo206a-geo206b_F2000/index.html
shaped the modern environment. The first
Final Exam Type Final
section covers the origin of the Universe,
Grading
Title
Perc.
chemical elements, and solar system.
After a
Course Listings
Other Exam
50 of the
discussion of the structure and dynamics
•
Dept.
CEE
Term Paper(s)
Earth, we next examine the origin of20
life,
Number 471
Quizzes
10
evolution of eukaryotic cells and multicellularity,
the evolution of vertebrates (amphibians,
20
•
Dept.
GEOPapers
dinosaurs, and mammals), and mass
Sample
Reading
Title
Number
471 Author Name
extinctions. The final section discusses the
List
Kump, Kasting and Crane
Earth System Science
origin of man, the ice ages, and global change.
Title
Introduction
to Water
Pollution Technology
Sections
Format
Number
Meetings
Instructors
206a:
3 lectures; Last
206b: three lectures, 1 threeDescription
An introduction to the
science End
of water quality
Beg.
Place
Days
First
Middle
hour laboratory.
management and pollution
Time control
Timein natural
Day
Max. Enrollment 40 Leslie
of biological
and GUYOT 220
Lsystems;01fundamentals
10:00:00
10:50:00
M
Michael
Bender
May Audit?
N
chemical transformations in natural waters;
W
indentification of sources of pollution; water
Website
courseinfo.princeton.edu/courses/geo206aF
and wastewater treatment methods;
geo206b_F2000/index.html
Course Listings
Max. Enrollment
May Audit?
Website
Title
Final
Exam Type
Description
Grading
Dept.
Course Listings Dept. Number
Design
33
•
Format
P
CEE 471
Project(s)
Number
04
GEO 471
Quizzes
66
Meetings
Title
Introduction to Water Pollution Technology
Other (See
1
•
Beg. Time 19:00:00
Instructor)
Description
An introduction to the science of water quality management and pollution control in natural
systems; fundamentals of biological
End Time 19:50:00
and chemical transformations in natural waters; indentification of sources
of pollution;
Sample
Readingwater
List and wastewater treatment
Place
GUYOT 154
methods; fundamentals of water quality modeling.
•
Author Name Tchobanoglous & Schroeder
Days
Max. Enrollment 58
Title
Water Quality
•
Day W
May Audit?
Y
S.
K
A.
S.
K
A.
K
A.
K
A.
Perc.
11:00:00 11:50:00 GUYOT 154
•
Number
Format
19:00:00 19:50:00 GUYOT 154
Perc.
•
15:30:00 16:20:00 GUYOT 154
Thomas
Nicole
Mark
Thomas
Nicole
Mark
Nicole
Mark
Nicole
Mark
Day
Dept.
•
P
03
First Nicole
Middle K
Last
Gotberg
P
04
First Mark
Middle A.P
05
Last
Miller
Duffy
Number
Number
Format
Course Listings
Title
Description
Day
•
13:30:00 14:20:00 GUYOT 155
Last
S.
CEE 471
GEO 471
Introduction to Water Pollution Technology
An introduction to the science of water quality management and pollution control in natural systems; fundamentals of biological
and chemical transformations in natural waters; indentification of sources of pollution; water and wastewater treatment
methods; fundamentals of water quality modeling.
Dept. Number
Max. Enrollment 140
58
GEO 207
May Audit?
Y
Y
AST 207
Website
A Guided Tour of the Solar System
Final Exam Type Final
Other
This course examines the major bodies of our solar
Grading
Title
Perc.
Title
system, emphasizing their surface features, internal
MidTerm Exam
20
structures, and 33
atmospheres. Topics include the origin
Quizzes
10
Design
of
the
solar
system,
habitability
of
planets,
and
role
of
Final
Exam
20
Project(s)
impacts in planetary evolution. Terrestrial and giant
Precept Participation
10
Quizzes
66
planets will be studied as well as satellites, comets,
Other Exam
20
Other (See
1
and asteroids. Recent discoveries from planetary
Problem Set(s)
20
Instructor)
missions are emphasized. The course is aimed
Author
Name
Title
primarily
at non-science majors.
Tchobanoglous
&
Water
Quality
Author Name
Title
Schroeder
Morrow and Owen
The Planetary System
Eckenfelder
Principles of Water Quality
Bennett et al.
The Cosmic Perspective
Management
Consolmagno and Schaefer
Worlds Apart: A Textbook in Planetary Science
Metcalf & Eddy
Wastewater Engineering
Beatty et al.
The New Solar System
Sawyer & McCarty
Chemistry for Environmental
Format Number Meetings
Instructors
Engineers
Place
Days
Last
Beg.
End
First
Middle
Meetings
Instructors
Time
Time
Day
Place
Days
Beg.
End
First
Middle Last
L
01
11:00:00
11:50:00
GUYOT
10
M
Thomas
S.
Duffy
Time
Time
W
F Peter
L 01
09:30:00 10:50:00 FRIEN 008
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Paull
Th 155
Nicole
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Gotberg
Mark
A.
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P
03
15:30:00 16:20:00 GUYOT 154
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Thomas
S.
Duffy
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Gotberg
GEO 206
Mark
A.
Miller
History
of
the
Earth
P
04
19:00:00 19:50:00 GUYOT 154
W
Nicole
K
Gotberg
This course examines about 15 seminal events in natural history, and Mark
how those events shaped
environment. The
A. the modern
Miller
first
origin of
the Universe,
chemical
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andNicole
solar system. After a discussion
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P section
05 covers the
11:00:00
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K
Gotberg
dynamics of the Earth, we next examine the origin of life, evolution ofMark
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vertebrates (amphibians, dinosaurs, and mammals), and mass extinctions. The final section discusses the origin of man, the ice
ages,
global change. 206a: 3 lectures; 206b: three lectures,
1 three-hour
Dept. and
Number
Max. Enrollment
58 laboratory.
40
CEE 471
May Audit?
Y
N
GEO 471
Website
courseinfo.princeton.edu/courses/geo206a-geo206b_F2000/index.html
Introduction to Water Pollution Technology
Final Exam Type Other
Final
An introduction to the science of water quality
Grading
Title
Perc.
Title
management and pollution control in natural systems;
Design Project(s)
33
fundamentals of biological and chemical
Quizzes
66
transformations
in
natural
waters;
indentification
of
Other Exam 50
Other (See Instructor)
1
sources
of
pollution;
water
and
wastewater
treatment
Term Paper
20
methods;
fundamentals
of
water
quality
modeling.
(s)
Author Name 10
Title
Quizzes
Tchobanoglous20
& Schroeder
Water Quality
Papers
Eckenfelder
Principles of Water Quality Management
Author
Name
Title
MetcalfKasting
& Eddy and
Wastewater Engineering
Kump,
Earth System Science
Sawyer & McCarty
Chemistry for Environmental Engineers
Crane
FormatMeetings
Number Meetings
Instructors Instructors
Place
DaysFirst
Last
Beg.
End
FirstMiddle Last
Middle
Beg.
End
Place
Days
Time
Time
Day
Time
Time
L
01
09:30:00 10:50:00 FRIEN 008
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Peter
R.
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L 01
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Leslie
Bender Scott
Jeffery
Paull
ThMichael
W
Dept. Number
Max.
Enrollment
40
F
GEO 206
May Audit?
N
History of the Earth
Website
courseinfo.princeton.edu/courses/geo206ageo206b_F2000/index.html
This course examines about 15 seminal events in
natural history, and how those events shaped the
Final Exam Type Final
modern
Grading
Title
Perc.
GEO
206environment. The first section covers the
origin ofofthe
Other Exam
50
History
theUniverse,
Earth chemical elements, and solar
system.
After
a discussion
of15
theseminal
structure
and in natural history, and howTerm
20
This
examines
about
events
events shaped the modern environment. The
Dept.course
Number
Max. Enrollment thosePaper(s)
dynamics
of covers
the Earth,
next
the origin
of elements,
first
section
the we
origin
of examine
the Universe,
chemical
and
solar
system.
After
a
discussion
of
the
structure
and
Quizzes
10
May Audit?
life, evolution
of Earth,
eukaryotic
cellsexamine
and multicellularity,
dynamics
of the
we next
the origin of life, evolution of eukaryotic
cells and multicellularity, the evolution of 20
Papers
the evolution(amphibians,
of vertebrates
(amphibians,
dinosaurs, and Website
vertebrates
dinosaurs,
and mammals),
mass extinctions. The final section discusses the origin of man, the ice
and mammals),
mass206a:
extinctions.
The final
section
Final Exam
Type
ages,
and globaland
change.
3 lectures;
206b:
three lectures,
1 three-hour
laboratory.
discusses the origin of man, the ice ages, and global
Grading
Title
Perc.
40
change. 206a: 3 lectures; 206b: three lectures, 1
N
three-hour laboratory.
courseinfo.princeton.edu/courses/GEO206a-GEO206b_F2000/index.html
Author Name
Title
Final
Kump, Kasting and Crane
Earth System Science
Title
Format Number Meetings
Instructors
End
Place
Days
First
Middle
Last
Author
Name 20 Beg.
Title
Lab
Reports
Time
Time
Day
Other Exam 50
L
01
10:00:00 10:50:00 GUYOT 220
M
Michael
Leslie
Bender
Papers
20
W
Format Number Meetings
Instructors
Quizzes
10
F
Place
Days
Last
Beg.
End
First
Middle
Author Name
Title
Time
Time
Day
Kump,
Kasting and
Earth System Science
Dept. Number
Max. Enrollment 40
Crane
GEO 206
May Audit?
N
Instructors
HistoryMeetings
of the Earth
Website
courseinfo.princeton.edu/courses/GEO206aBeg.
End
Place
Daysin
First
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GEO206b_F2000/index.html
This course
examines
about 15
seminal events
Time andTime
natural history,
how those events shaped the
Final Exam Type Final
modern environment. The first section covers the
Grading
Title
Perc.
B
01
13:30:00
16:20:00
GUYOT
178
F
Michael
Leslie
Bender
origin of the Universe, chemical elements, and solar
Lab Reports
20
Sarah
A
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system. After a discussion of the structure and
Other Exam
50
Brian
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dynamics of the Earth, we next examine the origin of
Papers
20
Llife,01evolution
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10:50:00cells
GUYOT
220
M
Michael
Leslie
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of eukaryotic
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Quizzes
10
the evolution of vertebrates (amphibians, dinosaurs,
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and mammals), and mass extinctions. The final
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Earth System Science
Format Number Meetings
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Beg.
End
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Days
First
Middle
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Time
Time
Day
GEO 235
B
01
13:30:00 16:20:00 GUYOT 178
F
Michael
Leslie
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CEE
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Sarah
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The Physical Earth
Brian
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L
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Michael faults, and mountain
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W
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Leslie
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Sarah
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Meetings Beg.
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atmospheres. Topics include the origin of the solar system, habitability of planets, and role of impacts in planetary evolution.
Time
Time
Instructors Terrestrial and giant planets will be studied as well as satellites, comets, and asteroids. Recent discoveries from planetary
missions are emphasized. The course is aimed primarily at non-science majors.
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The Cosmic Perspective
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GEO 207
AST 207
A Guided Tour of the Solar System
This course examines the major bodies of our solar system, emphasizing their surface features, internal structures, and
atmospheres. Topics include the origin of the solar system, habitability of planets, and role of impacts in planetary evolution.
Terrestrial and giant planets will be studied as well as satellites, comets, and asteroids. Recent discoveries from planetary
missions are emphasized. The course is aimed primarily at non-science majors.
Max. Enrollment 140
May Audit?
Y
Website
Final Exam Type Final
Grading
Title
GEO 207
AST 207
A Guided Tour of the Solar System
This course examines the major bodies of our
solar system, emphasizing their surface
features, internal structures, and atmospheres.
Topics include the origin of the solar system,
habitability of planets, and role of impacts in
planetary evolution. Terrestrial and giant
planets will be studied as well as satellites,
comets, and asteroids. Recent discoveries from
planetary missions are emphasized. The course
is aimed primarily at non-science majors.
Max. Enrollment 140
May Audit?
Y
Website
Final Exam Type Final
Grading
Title
Number
Format
•
Course Listings
Title
Description
Perc.
A Guided Tour of the Solar System
This course examines the major bodies of our
solar system, emphasizing their surface
features, internal structures, and atmospheres.
Topics include the origin of the solar system,
habitability of planets, and role of impacts in
planetary evolution. Terrestrial and giant
planets will be studied as well as satellites,
comets, and asteroids. Recent discoveries from
planetary missions are emphasized. The course
is aimed primarily at non-science majors.
Max. Enrollment 140
May Audit?
Y
Website
Final Exam Type Final
Grading
•
Title MidTerm Exam
Perc. 20
(c) Basic hybrid layout (wider)
•
Number
Dept.
AST
Number 207
Course Listings
Dept.
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(b) Basic hybrid layout
•
Number
Course Listings
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GEO
Number 207
Dept.
•
Number
Dept.
Dept.
Title
Description
Max. Enrollment
May Audit?
Website
Final Exam Type
Number
Fig. 3. We illustrate our algorithm by enabling its features one by one and producing successive layouts of the data from Figure 2. All layouts are at
This
is a scale.
test to(a)
see
much
space
the figure
caption
will take.
write some
here to bullets,
avoid repeating
myself.
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yes.
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ipsum
the
same
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a basic
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as indented
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dolsomething.
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howand
much
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and
puts labels Yes.
to theThis
left is
ofaprimitive
values
above
relation
values.
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show
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widths,
use the
take. (a)
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see how
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(c)
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table
fit
within
the
available
horizontal
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(d)
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Sample Reading
This
is aoftest
see how
much space
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figure caption
will take.
(d) This
is a test
to
see
how much
the figure
caption
will horizontal
take. (e) This
is a
List
•
Course
Listingscolumns
columns
thetotable
sublayouts
to fill the
available
horizontal
space.
(e)
adds
to space
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to use
space
•
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test to
see how (f)
much
figure caption
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take. (f) This
test to seetohow
much ideal
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take. in (e).
more
efficiently.
is a space
specialthe
schema-only
layout
by is
thea algorithm
calculate
pointscaption
for the will
columns
content area of nested tables, respectively.
The outline layout, unlike the nested table layout, supports the concept of a horizontally constrained width. Like the layouts produced by
our final algorithm, an outline layout can be produced for any available width (with some minimum constraints), breaking text in primitive value areas as necessary. Our system distinguishes between fixedand variable-length primitive fields; value areas for fixed-length primitive field are always rendered at their predicted width, whereas areas for variable-length primitive fields are rendered to the full available width. This ensures that the visual width of a particular primitive
field remains the same between successive tuples, even when the actual value differs. The rationale is two-fold. First, if layouts are to be
used for data entry or data editing in a database application, the width
of an input field should be commensurate with the expected size of
its values. Second, keeping the perceived overall shape (gestalt) of
successive tuples of the same relation schema similar should make it
easier for a user to visually scan for specific fields in those tuples.
3.3
Hybrid Layout
Whereas nested table layouts quickly grow wide, outline layouts tend
to be tall and narrow. Outline layouts use space inefficiently by only
starting values on the left-hand side of the page, and by repeating
schema labels once for every value. They are also harder to read than
table layouts, since they tend to put values from the same schema field
but from different tuples far apart.
In Figure 3(b), we introduce a hybrid layout that embeds nested
tables inside an outline layout. This saves vertical space compared
to the pure outline layout in Figure 3(a). Like for the outline layout,
we assume that we are given a constrained horizontal width to work
with, such as screen size or page width for printing. We then create a
layout that is guaranteed to fit within this horizontal width. This avoids
horizontal scrolling or pagination, and ensures that the layout will only
grow in the vertical direction as more tuples or fields are added.
When building a hybrid outline/table layout, the algorithm must
start at the root level of the relation schema and decide, for each relation field, whether to render that relation field using a nested table or
another level of an outline layout. If the decision is made to render a
relation field using an outline layout, the decision process is repeated
recursively for each of its fields. If the decision is made to render a
relation field using a nested table layout, all child fields are rendered
as a nested table layout as well. While our recursive layout generation algorithm technically supports embedding outline sublayouts into
nested table layouts, this makes little typographical sense, and we do
not make use of this case.
The decision to use an outline layout vs. a nested table layout for
a given relation schema could reasonably be made using a cost optimization strategy, for instance based on the total area consumed by
the layout in each case. However, because nested table layouts almost invariably consume less space than corresponding outline layouts, a simpler heuristic is possible: always use a nested table layout if
there is enough horizontal space available for it. This is the rule used
in our algorithm; it is illustrated by contrasting the narrow layout in
Figure 3(b) with the wider layout of Figure 3(c). In Figure 3(b), the
layout is constrained to a small width, and small nested tables have
been chosen by the heuristic for relation fields Course Listings, Grading,
Sections/Meetings, and Sections/Instructors. All higher-level relations are
rendered using outline sublayouts. In Figure 3(c), the same data is rendered at a larger constrained width, allowing both the Sample Reading
List relation field and the entire Sections relation field to be rendered as
a nested table. Note that a hybrid layout that is given enough horizontal space to work with will always degenerate to a pure nested table
layout.
Since the outline vs. nested table decision heuristic depends on
whether or not there is enough horizontal space for a table, the determination of table column widths is important at this stage. For relation fields, table columns are as wide as the sum of their child fields’
columns, plus separator lines and side margins, as well as any extra
space needed to accommodate the relation column’s own header label. For fixed-width primitive fields, the width of the table column
is simply the width of the field. For variable-width primitive fields,
we experimented with various heuristics, and found the average width
of values in the field to be a sensible minimum, limited upwards to a
constant value (on the order of 50 characters, a standard book column
size). Primitive columns also need to be wide enough to accommodate
their schema labels, which may often be wider than the actual values
in the fields. For the latter case, we automatically use vertical column
labels in tables if this makes the column narrower for the purposes
of the outline vs. nested table decision. Examples are the Format and
Number column header labels in Figure 3(c).
After the minimum widths of table columns have been determined
and the decisions to use outline vs. nested table sublayouts at each relation level have been made, additional horizontal space may be available to the right of nested table sublayouts. A separate table justification step uses the remaining space to first, for readability, make any
previously vertical column headers’ labels horizontal. This is done
in a greedy order to minimize the number of remaining vertical column labels. Then, any remaining horizontal space is distributed among
columns holding variable-length primitive fields, in proportion to their
fields’ average lengths. The table justification step is illustrated in the
transition from Figure 3(c) to Figure 3(d).
Note again that layout styling decisions, such as table column
widths or whether to use an outline or a table sublayout for a given
subrelation, are made once for each field in the schema of the input
data rather than once for each value in the input data. This means,
for instance, that in a given layout like Figure 3(c), every instance of
the Sections relation will be rendered in the same way (either as a table
or an outline), regardless of its actual content in each instance. The
rationale is similar to that for making primitive fields in outline mode
always the same width.
3.4
Columns in Outline Layouts
While the hybrid layouts layout shown in Figures 3(b), (c), and (d)
save a substantial amount of space compared to corresponding outline layouts, they still use horizontal space inefficiently in cases where
small primitive fields can not be made part of a table and where only
tables with narrow content can be used. In form-style database user interfaces, the traditional solution is to make use of multiple columns of
fields. Note that these are a different kind of columns than the columns
in nested tables; they allow different fields in an outline layout to be
organized in multiple adjacent stacks. We now show how our system
can automatically incorporate columns in outline sublayouts with no
manual styling required.
We considered various approaches to the problem of introducing
columns into outline layouts. Design questions include how to pick
the right number of columns to use, how to pick the width of each
column, whether to allow certain fields to span multiple columns, and
after what fields a new column should be started. We decided to make
two simplifying assumptions which seem to work reasonably in practice: (1) the number of columns to use is based solely on the available
horizontal width, and (2) every adjacent column has the same width.
So for a layout of a width corresponding to a typical letter-size page,
for instance, the algorithm would use a two-column layout in the root
level outline. However, one complicating issue must still be dealt with:
relation fields that could be rendered in a table layout need to be allowed to span multiple columns if necessary. We settled on the following rule: any relation field in an outline is excluded from participating
in a set of multiple columns if that would cause it to be rendered as
an outline. There is no requirement that the field would actually have
to be rendered as a nested table if excluded, but if the excluded field
is still rendered as an outline, that outline layout is still subject to the
usual heuristics about whether to use columns or not at that next level.
For implementation purposes, the algorithm divides the fields of a
relation displayed in an outline layout into multiple column sets, each
which contains again a list of columns, each which contains the fields
in the column. To populate column sets, the algorithm iterates over
outline fields in the order they appear in the schema, assigning each
to the current column set. If an excluded field is encountered, it is
assigned to a new column set of its own, and a new current column
•
Author Name Markus K. Brunnermeier and Lasse H. Pedersen
Title
Predatory Trading, Journal of Finance 2005
Title
Topic
Description
L 01 O 30
Max. Enrollment
May PDF?
May Audit?
Assignments
22824
Meetings
Beg.
Time
End
Time
Place
11:00:00 12:20:00 FISHH B01
Days
T
Th
N
Instructor Assignments
First
Middle Last
Markus Konrad Brunnermeier
30
Y
Y
The course involves student presentations (10-15
minutes) and most likely trading simulations that
are based on recently developed trading software.
Approximately 75 pages of reading per week.
Financial institutions play an increasingly
dominant role in modern finance. This course
studies financial institutions and focuses on the
stability of the financial system. It covers
Website
important theoretical concepts and recent
Final Exam Type Final
developments in financial intermediation, asset
Grading
Title
pricing under asymmetric information, behavioral
MidTerm Exam
finance, and market microstructure. Topics
Final Exam
include market efficiency, asset price bubbles,
Oral Presentation(s)
herding, liquidity crises, risk management, market
design, and financial regulation.
Sample Reading Author Name
Title
List
Markus K. Brunnermeier
Asset Pricing under Asymmetric Information
Maureen O'Hara
Market Microstructure Theory
Glyn A. Holton
Value-at-Risk: Theory and Practice
Markus K. Brunnermeier and Lasse H. Pedersen Predatory Trading, Journal of Finance 2005
Sections
Status
SCORE Meetings
Instructor Assignments
Number
Place
Days
TBA?
Beg.
End
First
Middle Last
Time
Time
Day
L 01 O
30
22824
11:00:00 12:20:00 FISHH B01
T
Th
N
Perc.
35
35
30
Markus Konrad Brunnermeier
Hybrid Layout
Day Th
TBA?
Code Number Subletter
ECO 467
Institutional Finance
Max.
Enrollment
•
Course Listings
Number
Format
Sections
•
Format
L
Number
01
Status
O
Max. Enrollment 30
SCORE Number 22824
Meetings
•
Beg. Time 11:00:00
End Time 12:20:00
Place
FISHH B01
Days
•
Day T
Maureen O'Hara
Glyn A. Holton
Markus K. Brunnermeier
and Lasse H. Pedersen
Asset Pricing under Asymmetric
Information
Market Microstructure Theory
Value-at-Risk: Theory and Practice
Predatory Trading, Journal of Finance
2005
Day
Author Name Glyn A. Holton
Title
Value-at-Risk: Theory and Practice
Markus K. Brunnermeier
TBA?
Author Name Maureen O'Hara
Title
Market Microstructure Theory
•
MidTerm Exam 35
Final Exam
35
Oral
30
Presentation(s)
SCORE
Number
Max.
Enrollment
Status
•
Final
Sections
Title
Table Layout
•
Outline Layout
Sample Reading List
•
Author Name Markus K. Brunnermeier
Title
Asset Pricing under Asymmetric Information
The course involves student presentations (10-15
minutes) and most likely trading simulations that are
based on recently developed trading software.
Approximately 75 pages of reading per week.
Sample Reading List
Author Name
Number
Format
Title Oral Presentation(s)
Perc. 30
Y
Grading
Title
Perc.
Title Final Exam
Perc. 35
•
Y
Assignments
Final Exam
Type
Website
Financial institutions play an increasingly dominant role 30
in modern finance. This course studies financial
institutions and focuses on the stability of the financial
system. It covers important theoretical concepts and
recent developments in financial intermediation, asset
Title
Institutional Finance
pricing under asymmetric information, behavioral
Topic
finance, and market microstructure. Topics include
Description
Financial institutions play an increasingly dominant role in modern finance. This course studies financial institutions and
market efficiency, asset price bubbles, herding, liquidity
focuses on the stability of the financial system. It covers important theoretical concepts and recent developments in
crises, risk management, market design, and financial
financial intermediation, asset pricing under asymmetric information, behavioral finance, and market microstructure.
regulation.
Topics include market efficiency, asset price bubbles, herding, liquidity crises, risk management, market design, and
financial regulation.
Max. Enrollment 30
May PDF?
Y
May Audit?
Y
Assignments
The course involves student presentations (10-15 minutes) and most likely trading simulations that are based on
recently developed trading software. Approximately 75 pages of reading per week.
Website
Final Exam Type Final
Grading
•
Title MidTerm Exam
Perc. 35
•
Institutional Finance
May Audit?
Description
May PDF?
Max.
Enrollment
ECO 467
Title
Subletter
Number
Code
Course Listings
•
Code
ECO
Number 467
Subletter
Topic
Course Listings
•
N
Instructor Assignments
•
First Markus
Middle Konrad
Last
Brunnermeier
Fig. 4. A comparison between our hybrid outline/table layout and a pure nested table layout and a pure outline layout, for the case of displaying a
single tuple with many fields, including relational fields containing other nested tuples. Each layout is showing the same data in its entirety, at the
same scale and font size. Outline layouts waste space by concentrating data to the left of the screen and by repeating labels for each value. Table
layouts waste space when different fields in the same subrelation require different amounts of vertical space. Table layouts also tend to become
very wide, requiring horizontal scrolling if viewed on a screen.
set started. No reordering of fields is done at any point, as the order
of fields in the schema is considered significant for presentation purposes. After all fields have been assigned to column sets, each column
set partitions its assigned fields into columns. Figure 3(e) shows the
final hybrid layout with column support. The example layout has a
single outline sublayout with 3 column sets; the first column set has
two columns and contains the fields Course Listings through Description
in the first column and the fields Max. Enrollment through Grading in the
second column. The second and third column sets each have only one
column with a single field in each, containing the fields Sample Reading
List and Sections, respectively.
The partitioning of columns in a column set, that is, after what fields
to start each column, requires a heuristic. Simply giving each column
the same number of fields does not work well, since some fields frequently take up more vertical space than others. A better approach is
to split the columns in such a way as to minimize the total vertical
space consumed; this can be done easily with a dynamic programming routine. However, if this is done independently for each tuple
being rendered, two tuples might end up having differently partitioned
columns, with different fields starting the columns in each case. This
is not ideal for readability. Instead, as before, we make the decision of
where to begin new columns only once for the entire layout.
To allow calculation of optimal column partitioning positions on the
basis of only aggregate information about the input, we allow our layout generation algorithm to generate schema-only versions of sublayouts. For instance, the schema-only layout for the layout in Figure 3(e)
is shown in Figure 3(f). In a schema-only layout, variable-length primitive fields are sized according to the average width of the field in the
entire dataset. Relation fields are rendered, in outline or table form,
with a single placeholder tuple only, but subsequently padded such
that the size of the subrelation layout is proportional to the average
cardinality of that relation throughout the entire dataset. Thus in Figure 3(f), the Description field is taller than the Title field, and there are
about two rows’ worth of space allocated in the Sample Reading List table. Optimal column partitioning decisions are then made using these
estimated schema-only layouts.
The final class of hybrid layouts produced is considerably more
compact than both the outline and the nested table layouts, and can
be produced automatically with no manual input. Figure 4 shows a
scale comparison between the three layout styles, each showing a single nested tuple from the course catalog example. In this case, the
hybrid layout would permit significantly more data to be fit on a single
screen without scrolling in either the vertical or the horizontal direction. We can also see that large nested table layouts often waste space
whenever two values in the same tuple take up different amounts of
vertical space.
3.5
Implementation
To produce the hybrid layouts described, our system makes two passes
over the input data while maintaining a stylesheet as the only other
common data structure. The stylesheet maps schema paths and property types to property values, that is, each node in the schema has one
value for each property. See Table 1 for the list of stylesheet properties. Before the algorithm starts, a subset of properties will already
have been set as constants, such as the choice of fonts and separator
styles. Our algorithm’s first pass over the input data is during the Measure phase, which finds the average rendered width of each primitive
value and the average cardinality of each relation value. The application of heuristics to set remaining stylesheet properties is then done in
a subsequent pass over the schema only, the Auto-Style phase. Finally,
the output layout is constructed in the Layout phase, which is the second
pass over the input value. The Auto-Style and the Layout phases execute
the same code, but with the Auto-Style phase traversing a schema-only
version of the data structure used to maintain context, and using the
aforementioned heuristics to set undefined stylesheet properties whenever they are encountered. The heuristics for setting stylesheet properties during the Layout phase are described in Table 1.
4
I NTERACTIVE F EATURES
While our evaluation focuses on the static aspects of our layout management algorithm, our implemented system includes multiple features oriented towards interactive use.5
A requirement for many kinds of interactions is to be able to make
selections among displayed elements in the layout. Our system supports a spreadsheet-like cursor which can be used to select any cell
in the layout, where a cell is defined as either a label for a primitive
field, a label for a relation field, or a primitive value. Selections can be
made either by clicking the mouse or by moving the cursor with keyboard navigation keys (arrow keys, Home/End, and Page Up/Page Down).
5 To see the interactive features described in this section in action, we recommend watching the demo video accompanying this article.
Because the aforementioned definition of a cell serves to ensure that
no two cells can ever overlap, determining the cell to be selected in
the case of a mouse click is a simple matter of determining what cell
occupies, or is closest to, the point at which the mouse was clicked.
For keyboard-based cursor movement, we found the cursor behavior
to feel the most natural when the relative motion of the cursor followed the physical location of the cells in the visual layout rather than
the logical location of the cells in the schema. To make keyboard cursor movement work well when traversing cells stacked in various nontrivial configurations, we store the cursor state as an actual point on the
layout rather than simply as a pointer to the selected cell. This generalizes the behavior seen in existing spreadsheets for instance when
moving the cursor across merged cells.
An additional feature is the ability to interactively override the
stylesheet settings made by the automatic layout manager. This has the
potential to significantly improve readability of output layouts, since
the user can use their domain knowledge to decide where labels are
superfluous and can be omitted, what fields should serve as titles and
thus be emphasized with larger fonts, and such.
Finally, our system supports “frozen” table headers which stay put
at the top of the screen for as long as a table is partially visible in the
scrolling viewport. This works both for pure table layouts and where
table layouts are contained within outline layouts.
Potential future features include multiple selection, collapsible relation fields, editing of data values, spreadsheet-style filtering, and more
general-purpose query-building.
5 E VALUATION
We evaluated three aspects of our system: runtime performance, the
amount of space consumed by generated layouts, and the readability
Mean Depth
Max. Depth
Mean Plural
Depth
Max. Plural
Depth
59 887
1 359
250
953
1 566
1 493
3 032
854
901
953
800
18 751
419
61
560
809
310
1 020
731
101
494
200
2.25
2.20
2.96
5.01
3.15
2.10
3.63
6.16
2.00
3.85
2.33
4
4
4
6
5
3
5
8
2
6
3
2.25
2.20
1.00
2.51
1.94
1.09
2.48
3.43
1.00
1.94
1.00
4
4
1
3
3
2
4
5
1
3
1
Table 3. Runtime measurements for each phase of the layout algorithm.
Standard error is within 3% in each case.
RelationalPrinceton
RelationalPrincetonHuge
Pages
12
455
Algorithm Phase Runtime (s)
Paginate
Dataset
Layout
Properties Set During Auto-Style Phase
P R StartNewOutlineColumn. True for the first field in each column of an outline
column set. The heuristic partitions columns based on schema-only layouts that
use ValueDefaultWidth and AverageCardinality to estimate field sizes.
P R StartNewOutlineColumnSet. True for the first field in each outline column set.
Column sets allow some sibling fields to be organized in multiple columns and
others not. The heuristic puts a field in its own single-column column set if it
would otherwise contain an outline sublayout.
P R UseVerticalTableHeader. Whether to display a label in a table header vertically.
The heuristic initially assumes vertical labels for primitive fields if this makes
the column narrower, but restores as many horizontal labels as possible when
the table is justified.
P R TableColumnWidth. The width of each table column. Primitive columns are
ValueDefaultWidth wide before justification; relation columns are the sum of
their children plus twice TableNestSpaceSideWidth. Columns are also extended
to accomodate their labels, as necessary.
R UseTable. Whether to use an outline or a table sublayout for this relation. A table
sublayout is used iff it its width before justification is less than or equal to the
available horizontal space.
828 463
21 811
13 679
12 360
13 559
22 012
15 046
18 218
10 607
11 236
4 858
Auto-Style
Properties Set During Measure Phase
R OutlineLabelWidth. Width of labels in outline sublayouts. Sibling fields all use the
same width, which is defined at the parent relation level.
R AverageCardinality. The average number of tuples in each subrelation.
P IsVariableLength. Whether a primitive field holds long strings of variable length.
P ValueDefaultWidth. Average width of primitive values in this field when rendered
with ValueTextStyle, or maximum width for non-variable length fields.
Dataset
RelationalPrincetonHuge
RelationalPrinceton
Auction321Gone
SigmodRecord
SwissProt
DBLP
Mondial
NASA
TPCHPart
ProteinSequence
CoursesReed
# Tuples
Constant Heuristic Parameters
R OutlineMaxLabelWidth. Maximum width of labels in outline sublayouts.
R OutlineColumnMinWidth. Minimum width of each outline column.
P OutlineMinValueWidth. Minimum width of a primitive value in an outline.
P OutlineSnapValueWidth. Multiple to round up to when setting the width of a nonvariable primitive value in an outline sublayout.
P TableMaxPrimitiveWidth. Maximum width that can be allocated to a table
sublayout column with variable-length primitive values, before table
justification.
# Primitives
Basic Styling Constants
OutlineBulletStyle. Bullet type for bulleted tuples in outline sublayouts.
OutlineIndentWidth. Indentation amount for bulleted tuples in outline sublayouts.
OutlineTupleSpaceHeight. Vertical space between tuples in outline sublayouts.
TableNestSpaceSideWidth. Horizontal margin amount for nested tables.
LabelTextStyle. Text style for outline labels or table headers.
ValueTextStyle. Text style for values in outline or table sublayouts.
# Characters in
Primitives
R
R
R
R
PR
P
Table 2. Quantitative statistics related to the size and complexity of
datasets referred to in this paper. The depth of a primitive value is the
number of enclosing relation values that must be traversed to reach the
primitive value from the root. The plural depth only counts non-singleton
enclosing relations.
Measure
Table 1. Properties defined, for each schema node, by a stylesheet.
P, R, and P R indicate properties applicable to primitive nodes, relation
nodes, or both, respectively. We have omitted color- and border-related
properties.
1.03
40.16
0.29
0.31
0.83
42.43
0.0014
0.0451
of large layouts as measured by the time taken for human subjects to
solve question tasks about the rendered data. As sample datasets, we
picked one XML file from each of the 10 categories in the XML Data
Repository at the University of Washington6 , except for the Treebank
dataset, which is the only one with a recursive schema. We used the
“preview” version of each dataset to make sure visualizations would
be of a realistic size for human perusal. We also included one dataset
from a relational database containing the complete course catalog for
a semester at Princeton University. See Table 2.
5.1
Runtime Performance
For runtime measurements, we ran all phases of the layout algorithm
in sequence, and repeated the entire sequence multiple times. The runtimes for individual phases were averaged, less initial dry runs. Resulting runtime statistics for two datasets are shown in Table 3, for 30 runs
plus 3 dry runs. The machine used had an Intel Core 2 Duo CPU and
4GB of RAM.
Our two sets of runtime measurements suggest, as expected, that
both the Measure and Layout phases run in time roughly proportional to
the size of the input data, as measured by the size of the output layouts.
Also as expected, the time consumed by the Auto-Style phase does not
depend on the size of the input data, as it depends only on the schema
and input stylesheet. For the larger RelationalPrincetonHuge dataset, the
fact that the Layout phase does not take significantly more time to run
than than the Measure phase suggests that the main bottleneck of the
Layout phrase is the line breaking code that determines the size of rectangles assigned to display primitive values. Profiling has confirmed
this to be the case. For the smaller RelationalPrinceton dataset, the time
to perform Auto-Style and Layout for a new width is interactive.
6 G.
Miklau, http://www.cs.washington.edu/research/
xmldatasets/www/repository.html
Total Layout Area
(US Letter-size pages or equivalent)
70
Unpaginated Hybrid Layout
Paginated Hybrid Layout
Unpaginated Outline Layout
Paginated Outline Layout
Unpaginated Tabular Layout
60
50
40
30
20
10
0
RelationalPrinceton
Auction321Gone
SigmodRecord
SwissProt
DBLP
Mondial
NASA
TPCHPart
ProteinSequence
CoursesReed
Fig. 5. Total area consumed by layouts of each of the three types. Outline and Hybrid layout widths are constrained to 8 inches, and are shown
both with and without pagination.
5.2
Layout Space Efficiency
To evaluate the space efficiency of our layouts, we compared, for each
dataset, the area consumed by our own hybrid layout vs. the area consumed by a pure outline layout and a pure nested tabular layout. Each
layout was produced by our layout manager, with the latter two using
hard-coded values for the stylesheet property that selects whether a
table or an outline style is used at any given level in the schema.
Figure 5 compares the total area of each kind of layout for every
dataset. The unpaginated area of a layout is that of the smallest rectangle enclosing it. The paginated area, for hybrid and outline layouts,
is the number of pages consumed by the layout times the imageable
(non-margin) area available on each page. Thus, the latter includes
space wasted at the end of each page whenever the pagination algorithm has opted to break the page at an earlier but less awkward place.
Since pure tabular views of an entire dataset are generally too wide
to fit on a regular letter-size page, the tabular layout is rendered as a
single, very large page. In cases where the tabular layout is actually
narrow enough to fit on a page, notably the the SigmodRecord, TPCHPart, and CoursesReed datasets, the hybrid layout is nearly identical to
the tabular layout, except that the pagination algorithm may be used to
break up the hybrid layouts in the vertical direction. The ratio of the
area consumed by an unpaginated outline layout to that consumed by
an unpaginated hybrid layout is 3.9:1 on average. Similarly for tabular
to hybrid layouts, it is 1.6:1 on average.
Looking at the data from Figure 5, we see that the hybrid layout
consumes less space than the corresponding outline layout for every
dataset, with or without pagination enabled. The difference is greatest, between 4 and 13 times, in the cases where the hybrid layout corresponds to a pure nested tabular layout, namely SigmodRecord, TPCHPart,
and CoursesReed. In these cases the schema of the data was flat or almost flat, and so a standard table layout would make very efficient use
of the space. In the other cases, the hybrid layouts are about half the
size of outline layouts on average. The smallest difference was for the
Auction321Gone dataset, where the outline layout was 1.3 times the size
of the hybrid layout. In this case the schema was nested in several levels, but contained only singular relations (relations only ever holding
a single tuple) beyond the top level, so there were no opportunities for
the hybrid layout algorithm to introduce tables into the lower levels
of the layout. The modest saving over the outline layout came from
the hybrid layout’s ability to display data in an outline tuple over two
columns. A more significant difference was for the Mondial dataset,
where the outline layout was 3.3 times the size of the hybrid layout.
Here the hybrid layout made good use of both tuple columns and the
ability to render subrelations as tables, and only used one level of outline bullets.
While pure nested tabular layouts cannot be constrained to a page
width like the outline and hybrid layouts, they tend to consume less
total area than the outline layouts. See again Figure 5. For Auction321Gone, NASA, ProteinSequence, SwissProt, the hybrid layout still
consumes between 30% and 80% less space than the tabular layout.
This is because nested tables waste large amounts of space whenever
a row contains cells of variable heights, such as when one empty and
one well-populated subtable are placed horizontally adjacent to each
other on the same row of a parent table.
5.3
Readability
To evaluate the readability of our layouts, we conducted a betweensubjects online user study using Amazon Mechanical Turk7 and
StudyCaster, a Java-based tool we developed to allow test subjects to
stream timestamped recordings of their computer screens to our server
with a minimum of effort. In an initial public recruiting stage of the
study, workers were offered $0.25 to launch the StudyCaster and solve
a chart-making task that required the workers to have Microsoft Excel
installed on their machines. In the second and main stage of our experiment, we gradually invited qualified Mechanical Turk workers from
the first stage directly to do a second task, worth $3.00. This task contained, for each subject, 9 different two-part questions, each two-part
question being based on a separate PDF file with a layout generated
from one of our 9 XML sources from the UW XML repository. The
questions were a mix requiring the subjects to do both scanning across
multiple similar entities (e.g. “What is the Brand number of the product sold in a Jumbo Bag container at a Retail price of less than $950?”
or “How many articles were published in Volume 12, Number 3?”)
and lookup between the attributes and related entities of a single entity
(e.g. “What is the name of the person who was responsible for digitizing the earlier work by authors X?”). To reduce potential noise from
subjects’ varying familiarity with their PDF readers’ search feature,
the PDF files were rasterized, effectively disabling the feature for everyone. All subjects were given the same questions and datasets in the
same order. However, the type of layout provided for each dataset was
randomized, with the constraint that each subject would see 3 datasets
rendered with each of the 3 kinds of layout types. The order of the
layout types was round-robined such that datasets number 1, 4, and 7
would use the same layout types, as would 2, 5, and 8, and as would
3, 6, and 9. Each of the 18 total questions (from 9 two-part questions)
would be shown in the StudyCaster pop-up window, which allowed us
to measure the exact amount of time the subjects spent viewing, and
hence presumably spent working on, each question. The StudyCaster
software also allowed us to further limit timings to when workers had
the correct PDF file in focus in their PDF reader to answer the currently shown question (sampled from the Win32 API at 5Hz), and to
exclude time idle more than 5 seconds from keyboard or mouse activity (same). The idle time rule was used to decrease noise from workers
taking a break from the computer while having a question open on the
screen.
Our user study yielded data from 27 subjects. An additional 6 subjects completed the study, but were not included in the dataset due to
7 http://www.mturk.com
270
Hybrid Layout, Subtask A
Outline Layout, Subtask A
Tabular Layout, Subtask A
Hybrid Layout, Subtask B
Outline Layout, Subtask B
Tabular Layout, Subtask B
240
Mean Time to Solve Correctly (s)
Mean Time to Solve Correctly (s)
510
480
450
420
390
360
330
300
270
240
210
180
150
120
90
60
30
0 1
-A
210
180
150
120
90
60
30
01
2-Si
3-Sw
4-D
5
6
7
8
9
BLP -Mond -NASA -TPCH -Protei -Cours
iss
on3 gmodR
ial
nSe
e
Part
21G
ecor Prot
quen sReed
one
d
ce
Task Number-Data Set Name (Subtasks A)
-Au
ucti
2-Si
3-Sw
4-D
5-M
6
7
8
9
B
g
ond -NASA -TPCH -Protei -Cours
ial
nSe
e
Part
n32 modRe issProt LP
quen sReed
1Go
cord
ce
ne
Task Number-Data Set Name (Subtasks B)
ctio
Fig. 6. The mean time to solve each task in the user study, grouped by the kind of layouts that were used to generate the PDFs subjects used to
solve the task. The error bars show the Standard Error of the Mean. Subtasks B were given to subjects directly after Subtasks A, and were in each
case identical to Subtask A except for a small emphasized change in the question text.
technical problems uploading their screen recordings and timing data.
The 18 task questions were answered correctly by 88% of subjects on
average, with too limited variation to draw conclusions about possible
impact of layout type on correctness. Figure 6 shows the average time
taken to complete each subtask for each layout type. Each subject’s
timing is included in the average for each subtask only if the subject
answered that question correctly.
To test our user study for statistical significance, we considered the
timing data from each of the 18 subtasks separately. In each case, we
thus had 3 sets of measurements of the time taken to solve the task
correctly, one for each kind of layout presented to the user. We first
ran Levene’s test to confirm that our experiment design conformed to
ANOVA’s assumption of homogeneous variances between the 3 measurement populations in each case. In only 1 of the 18 cases (Task 5B)
was Levene’s test significant (indicating non-homogeneous variances)
with p < 0.05, suggesting that this is a reasonable assumption. We
thus proceeded to use ANOVA to analyze the results, with a Tukey
Honest Significance Test (HSD) as a follow-up test in cases where
the ANOVA was significant. Since we are doing 18 tests, we should
require p < 0.05/18 for strictly significant ANOVAs, as per the Bonferroni correction. There are two significant results to this confidence
level, for tasks 2A and 8B. For the purposes of discussing results, however, we have done the Tukey HSD follow-up test for all tasks with
ANOVAs up to p < 0.05. This allows us to list all the most significantly different pairs of timings between different layout types, as
shown together with the relevant p-values in Table 4. Note that we can
expect about one (18 ∗ 0.05) of the borderline-significant ANOVAs in
this table to be due to chance.
Looking at the follow-up tests from Table 4, we can see no significant differences in the task completion times between the tabular vs.
the hybrid layouts. We do however see consistent differences both between the outline and the hybrid layouts as well as between the outline
and the tabular layouts. These differences are present in both subtasks
of several questions, suggesting that they are relevant both when users
are first learning to do a task and when they immediately after do a
second similarly structured task. In terms of relative task completion
times, it is clear that both the hybrid and the tabular layouts outperform the outline layout, in both cases being completed 2.9 times faster
on average for the tasks listed in Table 4. This is consistent with the
hypothesis that larger layouts are harder to use because more scrolling
is needed to look through the same data.
The relatively high performance of the nested tabular layouts suggests that for the kinds of large datasets we had our users work with,
the very regular structure of the tabular layout can outweigh its disadvantages of taking up more space and requiring both horizontal and
vertical scrolling. However, the tabular layout would be a poor choice
for smaller datasets, such as the common database application requirement of showing the details of a single entity with all its attributes and
Table 4. Summary of statistical tests run on the dataset from Figure 6.
Only tasks for which the ANOVA yielded p<0.05 are shown. For Tukey
HSD pairs with p<0.05, we also show the relative differences in average
task completion times.
Task Levene
ANOVA
(heteroscedasticity)
#
2A
2B
3B
5A
5B
8A
8B
9A
9B
p
0.5312
0.0627
0.2889
0.7976
0.0389
0.1099
0.3409
0.4104
0.1812
between pairs)
p
0.0012
0.0034
0.0032
0.0072
0.0174
0.0101
0.0004
0.0034
0.0107
Mean-Time-toSolve Ratio
Tabular v. Outline: Outline:
Hybrid
Hybrid Tabular
p
0.8006
2.05
2.80
0.9279
3.40
2.62
0.0962
2.81
0.8521
2.11
2.74
0.9999
4.97
0.8201
1.88
0.3129
2.00
4.16
0.9553
2.46
2.20
0.7919
4.69
Tukey HSD (follow-up to find differences
Outline v.
Hybrid
p
0.0019
0.0036
0.3047
0.0200
0.0251
0.0092
0.0048
0.0050
0.0108
Outline v.
Tabular
p
0.0169
0.0448
0.0023
0.0142
0.0532
0.0996
0.0008
0.0119
0.0530
related subentities. Future evaluation could focus on layout performance on smaller, form-size datasets.
6
C ONCLUSION
We have presented a layout management algorithm that automates the
display of structured hierarchical data using the traditional visual idioms of hand-designed database UIs: tables, multi-column forms, and
outline-style indented lists. By default, the widths of generated layouts are constrained so that only vertical scrolling may be necessary to
view the data in its entirety. Our stylesheet system is further designed
such that two input values mapping to the same schema node will always be styled in a similar way. Our hybrid layouts are 3.9 and 1.6
times more compact on average than outline layouts and horizontally
unconstrained table layouts, respectively, and are as readable as table
layouts even for large datasets. We believe that our system can function as a single output system for most of the data views commonly required in domain-specific database applications, whether they be large
tables required to display information about many entities at once or
form views that must display many details of a single entity compactly
without scrolling.
ACKNOWLEDGMENTS
We would like to thank Michael S. Bernstein, Christian Bernt
Haakonsen, Jeffrey Heer, and anonymous reviewers past and present
for their helpful input during various stages of this project.
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