4/8/10
VisTrails:
Managing Provenance for Science
Juliana Freire
http://www.cs.utah.edu/~juliana
What is Provenance?


Oxford English Dictionary: (i) the fact of coming
from some particular source or quarter; origin,
derivation. (ii) the history or pedigree of a work of
art, manuscript, rare book, etc.; concretely, a
record of the ultimate derivation and passage of an
item through its various owners.
Apple Dictionary: Origin, source, place of origin;
birthplace, fount, roots, pedigree, derivation, root,
etymology; formal radix.
Provenance in Science– Juliana Freire
Argonne National Laboratory
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1
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Provenance in Art
Rembrandt van Rijn
Self-Portrait, 1659
Andrew W. Mellon Collection
1937.1.72
Argonne National Laboratory
Provenance in Science– Juliana Freire
3
Provenance in Science
Provenance is as (or
more!) important as
the result
  Not a new issue
  Lab notebooks have
been used for a long time
  What is new?
When

–  Large volumes of data
–  Complex analyses—
computational processes

Writing notes is no
longer an option…
Annotation
Observed
data
DNA recombination
By Lederberg
Provenance in Science– Juliana Freire
Argonne National Laboratory
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2
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Digital Data and Provenance
Emp
John
Susan
Dept
D01
D02
Mgr
Mary
Ken
Argonne National Laboratory
Provenance in Science– Juliana Freire
5
Uses of Computational Provenance
anon4876_zspace_20060331.jpg
anon4877_zspace_20060331.jpg
anon4877_lesion_20060401.jpg
Reproducibility
Data quality
Attribution
Informational
How were these images created?
Was any pre-processing applied to the raw data?
What’s the difference?
Who created them?
Are they really from the
same patient?
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Vision: Provenance-Rich Data
Argonne National Laboratory
Provenance in Science– Juliana Freire
7
Provenance Management
and the Digital Data Life Cycle
Sensors
User studies
Simulations
Obtain
Data
Integrate/
Organize
Analyze/
Visualize
Web
Databases
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Provenance Management: Exploration and
Creativity Support



Reflective reasoning is key in the exploratory
processes
“Reflective reasoning requires the ability to store
temporary results, to make inferences from stored
knowledge, and to follow chains of reasoning
backward and forward, sometimes backtracking
when a promising line of thought proves to be
unfruitful. …the process is slow and laborious”
Donald A. Norman
Need external aids—tools to facilitate this process
–  Creativity support tools


[Shneiderman, CACM 2002]
Need aid from people—collaboration
Provenance can enable knowledge re-use and
collaboration
Argonne National Laboratory
Provenance in Science– Juliana Freire
9
VisTrails: Managing Provenance


Comprehensive provenance infrastructure for
computational tasks
Focus on exploratory tasks such as simulation,
visualization and data analysis
Data
Process
Data
Product
Specification
Data
Manipulation
Perception &
Cognition
Knowledge
Exploration
User
Figure modified from J. van Wijk, IEEE Vis 2005
Provenance in Science– Juliana Freire
Argonne National Laboratory
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VisTrails: Managing Provenance
Comprehensive provenance infrastructure for
computational tasks
Focus on exploratory tasks such as simulation,
visualization and data analysis
Transparently tracks provenance of the discovery
process



–  The trail followed as users generate and test hypotheses
Use provenance to streamline exploration: support
reflective reasoning
Focus on usability—build tools for scientists


–  VisTrails manages the data, metadata and the exploration
process, scientists can focus on science!
Infrastructure can be combined with and enhance
these scientific workflow and visualization systems

Provenance in Science– Juliana Freire
Argonne National Laboratory
11
VisTrails: The System






Open-source, freely downloadable system
(www.vistrails.org)
Multi-platform: users on Mac, Linux, and Windows
Python code and uses PyQt and Qt for the interface
Over 13,000 downloads since 2007
User’s guide, wiki, and mailing list
Many users in different disciplines and countries:
•  Visualizing
environmental simulations (CMOP STC)
for solid, fluid and structural mechanics (Galileo Network, UFRJ Brazil)
•  Quantum physics simulations (ALPS, ETH Switzerland)
•  Climate analysis (CDAT)Habitat modeling (USGS)
•  Open Wildland Fire Modeling (U. Colorado, NCAR)
•  High-energy physics (LEPP, Cornell)Cosmology simulations (LANL)
•  Using tms for improving memory (Pyschiatry, U. Utah)
•  eBird (Cornell, NSF DataONE)Astrophysical Systems (Tohline, LSU)
•  NIH NBCR (UCSD)
•  Pervasive Technology Labs (Heiland, Indiana University)
•  Teaching: Linköping University, University of North Carolina, Chapel Hill, UTEP
•  Simulation
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Demo



Change-based provenance model
Scalable generation of data products
Understanding exploratory process: visual workflow
difference
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Argonne National Laboratory
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Change-Based Provenance


Records user actions
Provenance = changes to
computational tasks
–  Add a module, add a connection,
change a parameter value
addModule
deleteConnection
addConnection
addConnection
setParameter
Provenance in Science– Juliana Freire
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4/8/10
Change-Based Provenance


Records user actions
Provenance = changes to
computational tasks
–  Add a module, add a connection,
change a parameter value


A vistrail node vt corresponds to
the workflow that is constructed
by the sequence of actions from
the root to vt
vt = xn ◦ xn-1 ◦ … ◦ x1 ◦ Ø
vistrail
x1
x2
x3
Extensible change algebra
[Freire et al, IPAW 2006]
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Provenance Beyond Reproducibility


Support for reflective reasoning
Ability to compare data products
[Freire et al., IPAW 2006]
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Computing Workflow Differences
No need to compute subgraph
isomorphism!
  A vistrail is a rooted tree: all
nodes have a common
ancestor—diffs are welldefined and simple to
compute
vt1 = xi ◦ xi-1 ◦ … ◦ x1 ◦ Ø
vt2 = xj ◦ xj-1 ◦ … ◦ x1 ◦ Ø
vt1-vt2 = {xi, xi-1, …, x1, Ø} –
{xj, xj-1, …,x1 , Ø}
  Different semantics:

–  Exact, based on ids
–  Approximate, based on module
signatures
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Provenance Beyond Reproducibility



Support for reflective reasoning
Ability to compare data products
Explore parameter spaces and compare results
[Freire et al., IPAW 2006]
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Exploring the Change Space


Scripting workflows: Parameter explorations are
simple to specify and apply
Exploration of parameter space for a workflow vt
(setParameter(idn,valuen) ◦ … ◦ (setParameter(id1,value1) ◦ vt )

Exploration of multiple workflow specifications
(addModule(idi,…) ◦ (deleteModule(idi) ◦ v1 )
…
(addModule(idi,…) ◦ (deleteModule(idi) ◦ vn )



Results can be conveniently compared in the
VisTrails spreadsheet
Can create animations too!
Caching to avoid redundant computations [Bavoil et
al., IEEE Vis 2005]
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Provenance Beyond Reproducibility




Support for reflective reasoning
Ability to compare data products
Explore parameter spaces and compare results
Support for collaboration
[Ellkvist et al., IPAW 2008]
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Collaborative Exploration

Collaboration is key to data exploration
–  Translational, integrative approaches to science


Store provenance information in a database
Synchronize concurrent updates through locking
–  Real-time collaboration [Ellkvist et al., IPAW 2008]

Asynchronous access: similar to version control
systems
–  Check out, work offline, synchronize
–  Users exchange patches

No need for a central repository—support for
distributed collaboration
–  For details see Callahan et al, SCI Institute Technical
Report, No. UUSCI-2006-016 2006
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Argonne National Laboratory
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Vistrail Synchronization

Version tree is monotonic
–  Actions are always added, never deleted

Merging two vistrails is simple
+
Provenance in Science– Juliana Freire
=
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Change-Based Provenance: Summary

General: Works with any system that has undo/redo!
Argonne National Laboratory
Provenance in Science– Juliana Freire
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Provenance Enabling 3rd-Party Tools
Autodesk Maya
ParaView
VisIt
ImageVis3d
[Callahan et al., IPAW 2008]
Provenance in Science– Juliana Freire
Argonne National Laboratory
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VisTrails Provenance Plugin for ParaView
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Change-Based Provenance: Summary



General: Works with any system that has undo/redo!
Concise representation
Uniformly captures data and workflow provenance
–  Data provenance: where does a specific data product come
from?
–  Workflow evolution: how has workflow structure changed over
time?



Results can be reproduced
Detailed information about the exploration process
Provenance beyond reproducibility:
–  Scientists can return to any point in the exploration space
–  Scalable exploration of the parameter space—results can be
compared side-by-side in the spreadsheet
–  Support for collaboration
–  Understand problem-solving strategies—knowledge re-use
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Re-Using Provenance
Querying Provenance by Example


Provenance is represented as graphs: hard to specify
queries using text!
Querying workflows by example [Scheidegger et al., TVCG
2007; Beeri et al., VLDB 2006; Beeri et al. VLDB 2007]
–  WYSIWYQ -- What You See Is What You Query
–  Interface to create workflow is same as to query
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Refining Analyses by Analogy

Leverage the wisdom of the crowds in shared
provenance
–  Some refinements are common, e.g., change the
rendering technique, publish image on the Web

Apply refinements by analogy, automatically
[Scheidegger et al, IEEE TVCG 2007]
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Generating Visualizations by Analogy
[Scheidegger et al, IEEE TVCG 2007]
Provenance in Science– Juliana Freire
http://www.cs.utah.edu/~juliana/videos/Analogies.m4v
Argonne National Laboratory
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The Need for Guidance in
Workflow Design
Provenance in Science– Juliana Freire
Argonne National Laboratory
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VisComplete: A Workflow
Recommendation System



Mine provenance collection: Identify graph
fragments that co-occur in a collection of workflows
Predict sets of likely workflow additions to a given
partial workflow
Similar to a Web browser suggesting URL
completions
[Koop et al., IEEE Vis 2008]
Provenance in Science– Juliana Freire
Argonne National Laboratory
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VisComplete: A Workflow
Recommendation System



Mine provenance collection: Identify graph
fragments that co-occur in a collection of workflows
Predict sets of likely workflow additions to a given
partial workflow
Similar to a Web browser suggesting URL
completions
Provenance in Science– Juliana Freire
VisComplete: Demo
Argonne National Laboratory
35
[Koop et al., IEEE Vis2008]
http://www.cs.utah.edu/~juliana/videos/viscomplete_h_264.mov
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Some Projects that Use VisTrails
Climate Data Analysis
[CDAT Project, Lawrence Livermore National Lab]
www.vistrails.org
Provenance in Science– Juliana Freire
Argonne National Laboratory
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3
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Quantum Lattice Models
[ALPS Project, ETH-Zurich]
www.vistrails.org
Provenance in Science– Juliana Freire
Argonne National Laboratory
39 39
3
Coastal Margin Observation & Prediction
[NSF Science & Technology Center for Coastal Margin Observation & Prediction]
www.vistrails.org
Provenance in Science– Juliana Freire
Argonne National Laboratory
40 40
4
19
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Comparing Cosmological Simulations
[Cosmic Code Comparison Project, Los Alamos National Lab]
www.vistrails.org
Argonne National Laboratory
Provenance in Science– Juliana Freire
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4
Wildfire Prediction
[WRF-Fire Project, University of Colorado-Denver]
www.vistrails.org
Provenance in Science– Juliana Freire
Argonne National Laboratory
42 42
4
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Studying the Effects of rtms on Memory
Psychiatry-U of Utah
Provenance in Science– Juliana Freire
Argonne National Laboratory
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Emerging Applications
21
Lactate threshold
Lactate threshold O2 uptake, l/min
Lactate threshold, % maximal O2 uptake
4.70
85
4.52
78
4.63
76
4.02
76
Gross efficiency, %
Delta efficiency, %
Power at O2 uptake of 5.0 l/min, W
21.18
21.37
374
21.61
21.75
382
22.66
22.69
399
23.05
23.12
404
4/8/10
gram” at a given percentage of V̇O2 max (e.g., 83%) increased
by 18%.
In the trained state, this individual possessed a remarkably
high V̇O2 max of !6 l/min, and his blood LT occurred at a V̇O2
of !4.6 l/min (i.e., 76 – 85% V̇O2 max). These physiological
DISCUSSION
factors remained relatively stable from age 21 to 28 yr. These
This case study has described the physiological characteris- absolute values are higher than what we have measured in
tics of a renowned world champion road racing bicyclist who bicyclists competing at the US national level (9), several of
is currently the six-time Grand Champion of the Tour de whom subsequently raced professionally in Europe during the
France. It reports that the physiological factor most relevant to period of 1989 –1995. The five-time Grand Champion of the
performance improvement as he matured over the 7-yr period Tour de France during the years 1991–1995 has been reported
"1
"1
from ages 21 to 28 yr was an 8% improvement in muscular to possess a V̇O2 max of 6.4 l/min and 79 ml !kg !min with
efficiency when cycling. This adaptation combined with rela- a body weight of 81 kg (28). Laboratory measures of the
subject
in
our
study
were
not
made
soon
after
the
Tour
de
tively large reductions in body fat and thus body weight (e.g.,
78 –72 kg) during the months before the Tour de France France; however, with the conservative assumption that
J Appl Physiol 98: 2191–2196, 2005.
O2 max was at least 6.1 l/min and given his reported body
V̇
contributed
to
an
impressive
18%
improvement
in
his
powerFirst published March 17, 2005; doi:10.1152/japplphysiol.00216.2005.
to-body weight ratio (i.e., W/kg) when cycling at a given V̇O2 weight of 72 kg, we estimate his V̇O2 max to have been at least
(e.g., 5.0 l/min or !83% V̇O2 max). Remarkably, this individual 85 ml!kg"1 !min"1 during the period of his victories in the
was able to display these achievements despite the fact that he Tour de France. Therefore, his V̇O2 max per kilogram of body
Improved muscular efficiency displayeddeveloped
as Tour
de France
matures
advanced
cancer at agechampion
25 yr and required
surgeries weight during his victories of 1999 –2004 appears to be somewhat higher than what was reported for the champion during
and chemotherapy.
1991–1995 and to be among the highest values reported in world
Edward F. Coyle
class runners and bicyclists (e.g., 80 – 85 ml!kg"1 !min"1) (6, 15,
Human Performance Laboratory, Department of Kinesiology and
16, 28, 29)
Health Education, The University of Texas at Austin, Austin, Texas
It is generally appreciated that in addition to a high V̇O2 max,
success in endurance sports also requires an ability to exercise
Submitted 22 February 2005; accepted in final form 10 March 2005
for prolonged periods at a high percentage of V̇O2 max as well
Coyle, Edward F. Improved muscular efficiency displayed as Tour ages 21 to 28 y. Description of this person is noteworthy for as the ability to efficiently convert that energy (i.e., ATP) into
de France champion matures. J Appl Physiol 98: 2191–2196, 2005. First two reasons. First, he rose to become a six-time and present muscular power and velocity (5, 7, 8, 29). Identification of the
published March 17, 2005;doi:10.1152/japplphysiol.00216.2005.— Grand Champion of the Tour de France, and thus adaptations blood LT (e.g., 1 mM increase in blood lactate above baseline)
This case describes the physiological maturation from ages 21 to 28 yr relevant to this feat were identified. Remarkably, he accom- in absolute terms or as a percentage of V̇O2 max is, by itself, a
of the bicyclist who has now become the six-time consecutive Grand
plished this after developing and receiving treatment for ad- reasonably good predictor of aerobic performance (i.e., time
Champion of the Tour de France, at ages 27–32 yr. Maximal oxygen
that aINgiven
rate ofATHLETE
ATP turnover can be maintained) (7, 8,2193
14,
IMPROVED MUSCULAR EFFICIENCY
AN ELITE
uptake (V̇O2 max) in the trained state remained at !6 l/min, lean body vanced cancer. Therefore, this report is also important because
it provides insight, although limited, regarding the recovery of 21), and prediction is strengthened even more when measureweight remained at !70 kg, and maximal heart rate declined from 207 Table
2. Physiological
characteristics
of this treatment
individualfor
from
agesofof muscle
21 to 28capillary
yr
density is combined with LT (11).
“performance
physiology”
after successful
ad-thement
to 200 beats/min. Blood lactate threshold was typical of competitive Fig.
1. Mechanical efficiency when bicycling expressed as “gross efficiency”
is thought to be an index of the working
vanced
cancer. The
of this
study
will be
to World
report Capillary density Age,
cyclists in that it occurred at 76 – 85% V̇O2 max, yet maximal blood and
“delta efficiency”
overapproach
the 7-yr period
in this
individual.
WC,
yr
results
from
standardized
laboratory
on this individual
lactate concentration was remarkably low in the trained state. It Bicycle
Road
Racing
Championships,
1st and 4thtesting
place, respectively.
Tour de muscle’s ability to clear fatiguing metabolites (e.g., acid) from
21.1
25.9
28.2
1st,time
Grand
Champion
of the Tour de
in 1999
–2004.22.0, 25.9, 21.4
muscle fibers into 22.0
the circulation, whereas
the LT is thought
appears that an 8% improvement in muscular efficiency and thus France
at five
points
corresponding
toFrance
ages 21.1,
21.5,
power production when cycling at a given oxygen uptake (V̇O2) is the Date:
andMonth-Year
28.2 yr.
Nov 1992
Jan 1993
Sept 1993
Aug 1997
Nov 1999
Scientific Publications and Provenance
maximum oxygen uptake; blood lactate concentration
Provenance
J Appl Physiol • VOL
Preseason
98 • JUNE 2005 •
Preseason
www.jap.org
Racing
Reduced
Preseason
Anthropometry
testing sequence. On reporting to the laboratory,
training, 76.5
BodyGeneral
weight, kg
78.9
Lean
bodyand
weight,
kg histories were obtained, body
70.5
racing,
medical
weight was mea- 69.8
Body
fat,("0.1
%
10.7
sured
kg), and the following tests were performed
after in- 8.8
75.1
79.5
70.2
11.7
79.7
71.6
Maximal O2 uptake, l/min
5.56
5.82
chanicalO2efficiency
blood
lactate threshold
(LT) were deter- 76.1
"1
70.5
Maximal
uptake, ml and
! kg"1the
! min
mined as
therate,
subject
bicycled a stationary ergometer
Maximal
heart
beats/min
207 for 25 min, with 206
work rate
increasing
progressively
every 5 min over7.5
a range of 50, 60, 6.3
Maximal
blood
lactic acid,
mM
6.10
81.2
202
6.5
5.29
66.6
200
9.2
5.7
71.5
200
Lactate
thresholdwas
O2 determined
uptake, l/minby hydrostatic weighing
4.70and/or analysis 4.52
composition
Lactate
threshold,
% maximal
85
78
2 uptake
of skin-fold
thickness
(34,O35).
4.63
76
4.02
76
formed consent was obtained, with procedures approved
by the
Maximal
aerobic ability
Internal Review Board of The University of Texas at Austin. Me-
70, 80, and 90% V̇O2 max. After a 10- to 20-min period ofLactate
activethreshold
recovery, V̇O2 max when cycling was measured. Thereafter, body
Mechanical
Measurement of V̇O2 max. The same Monark ergometer (model
819) efficiency
equipped
with%a racing seat and drop handlebars
Gross
efficiency,
21.18and pedals for 21.61
22.66
23.05
cycling
shoes %
was used for all cycle testing, and seat
height and saddle 21.75
Delta
efficiency,
21.37
22.69
23.12
position
held
constant.
The pedal’s crank length
was 170 mm. 382
Power
at O2were
uptake
of 5.0
l/min, W
374
399
404
V̇O2 max was measured during continuous cycling lasting between 8
and 12 min, with work rate increasing every 2 min. A leveling off of
oxygen uptake (V̇O2) always occurred, and this individual cycled until
gram”
at a given
percentage
of V̇that
O2 max
83%)
increased
In the trained state, this individual possessed a remarkably
exhaustion
at a final
power output
was(e.g.,
10 –20%
higher
than the
National
Laboratory
byminimal
18%. power output needed to elicitArgonne
l/min, and his blood LT occurred at a V̇O2
V̇O2 max. A venous blood high V̇O2 max of !645
sample was obtained 3– 4 min after exhaustion for determination of of !4.6 l/min (i.e., 76 – 85% V̇O2 max). These physiological
DISCUSSION
blood lactate concentration after maximal exercise, as described factors remained relatively stable from age 21 to 28 yr. These
below. The subject breathed through a Daniels valve; expired gases absolute values are higher than what we have measured in
This case study has described the physiological characteriswere continuously sampled from a mixing chamber and analyzed for bicyclists competing at the US national level (9), several of
tics
a renowned
world champion
road
bicyclist who
O2 of
(Applied
Electrochemistry
S3A) and
COracing
2 (Beckman LB-2). Inisspired
currently
the six-time
Grandusing
Champion
the (ParkinsonTour de whom subsequently raced professionally in Europe during the
air volumes
were measured
a dry-gasofmeter
France.
reports
thatinstruments
the physiological
factorwith
mosta computer
relevant to
Cowan It
CD4).
These
were interfaced
that period of 1989 –1995. The five-time Grand Champion of the
performance
as he
matured
overforthe
7-yr period
calculated V̇Oimprovement
same
equipment
indirect
calorim- Tour de France during the years 1991–1995 has been reported
2 every 30 s. The
"1
"1
etry ages
was used
7-yr an
period,
with gas analyzers
calibrated to possess a V̇O2 max of 6.4 l/min and 79 ml !kg !min with
from
21 toover
28 the
yr was
8% improvement
in muscular
against thewhen
samecycling.
known This
gassesadaptation
and the dry-gas
meter
calibrated
efficiency
combined
with
rela- a body weight of 81 kg (28). Laboratory measures of the
periodically
to a 350-liter
spirometer.
tively
large reductions
in Tissot
body fat
and thus body weight (e.g., subject in our study were not made soon after the Tour de
Blood
LT.during
The subject
Monark
(model
819) France; however, with the conservative assumption that
78 –72
kg)
the pedaled
monthsthe
before
theergometer
Tour de
France
J Appl
Physiol!50,
98: 2191–2196,
continuously for 25 min at work rates
eliciting
80,2005.
and V̇O
contributed
to an impressive
18%doi:10.1152/japplphysiol.00216.2005.
improvement
in60,
his70,power2 max was at least 6.1 l/min and given his reported body
published
March
17, 2005;
90% V̇First
O2 max
for each
successive
5-min stage. The calibrated ergomeweight of 72 kg, we estimate his V̇O2 max to have been at least
to-body
weight
ratio
(i.e.,
W/kg)
when
cycling
at
a
given
V̇
O2
ter was set in the constant power mode, and the subject maintained
a
85
ml!kg"1 !min"1 during the period of his victories in the
(e.g.,
5.0
l/min
or
!83%
V̇
O
).
Remarkably,
this
individual
2 max samples were obtained either from
pedaling cadence of 85 rpm. Blood
Scientific Publications and Provenance
Tour de France. Therefore, his V̇O2 max per kilogram of body
weight during his victories of 1999 –2004 appears to be somecosts of publication of this article were defrayed in part by the payment what higher than what was reported for the champion during
andThe
chemotherapy.
of page charges. The article must therefore be hereby marked “advertisement” 1991–1995 and to be among the highest values reported in world
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
class runners and bicyclists (e.g., 80 – 85 ml!kg"1 !min"1) (6, 15,
Human Performance Laboratory, Department of Kinesiology and
http://www. jap.org
8750-7587/05 $8.00 Copyright © 2005 the American Physiological Society
2191 16, 28, 29)
Health Education, The University of Texas at Austin, Austin, Texas
It is generally appreciated that in addition to a high V̇O2 max,
success in endurance sports also requires an ability to exercise
Submitted 22 February 2005; accepted in final form 10 March 2005
for prolonged periods at a high percentage of V̇O2 max as well
Coyle, Edward F. Improved muscular efficiency displayed as Tour ages 21 to 28 y. Description of this person is noteworthy for as the ability to efficiently convert that energy (i.e., ATP) into
de France champion matures. J Appl Physiol 98: 2191–2196, 2005. First two reasons. First, he rose to become a six-time and present muscular power and velocity (5, 7, 8, 29). Identification of the
published March 17, 2005;doi:10.1152/japplphysiol.00216.2005.— Grand Champion of the Tour de France, and thus adaptations blood LT (e.g., 1 mM increase in blood lactate above baseline)
This case describes the physiological maturation from ages 21 to 28 yr relevant to this feat were identified. Remarkably, he accom- in absolute terms or as a percentage of V̇O2 max is, by itself, a
of the bicyclist who has now become the six-time consecutive Grand
plished this after developing and receiving treatment for ad- reasonably good predictor of aerobic performance (i.e., time
Champion of the Tour de France, at ages 27–32 yr. Maximal oxygen
that a given rate of ATP turnover can be maintained) (7, 8, 14,
uptake (V̇O2 max) in the trained state remained at !6 l/min, lean body vanced cancer. Therefore, this report is also important because
21), and prediction is strengthened even more when measureweight remained at !70 kg, and maximal heart rate declined from 207 it provides insight, although limited, regarding the recovery of
ment of muscle capillary density is combined with LT (11).
“performance
physiology”
after
successful
treatment
for
adto 200 beats/min. Blood lactate threshold was typical of competitive Fig.
1. Mechanical efficiency when bicycling expressed as “gross efficiency”
vanced
cancer. The
of this
study
will be
to World
report Capillary density is thought to be an index of the working
cyclists in that it occurred at 76 – 85% V̇O2 max, yet maximal blood and
“delta efficiency”
overapproach
the 7-yr period
in this
individual.
WC,
results
from
standardized
laboratory
on this individual
lactate concentration was remarkably low in the trained state. It Bicycle
Road
Racing
Championships,
1st and 4thtesting
place, respectively.
Tour de muscle’s ability to clear fatiguing metabolites (e.g., acid) from
1st,time
Grand
Champion
of the Tour de
in 199921.5,
–2004.22.0, 25.9, muscle fibers into the circulation, whereas the LT is thought
appears that an 8% improvement in muscular efficiency and thus France
at five
points
corresponding
toFrance
ages 21.1,
power production when cycling at a given oxygen uptake (V̇O2) is the and 28.2 yr.
to display these achievements despite the fact that he
Improved muscular efficiency displayedwas
asableTour
de France
matures
developed
advanced
cancer at agechampion
25 yr and required
surgeries
Address for reprint requests and other correspondence: E. F. Coyle, Bellmont Hall 222, Dept. of Kinesiology and Health Education, The Univ. of
Edward
F. 78712
Coyle(E-mail: coyle@mail.utexas.edu).
Texas at Austin,
Austin, TX
characteristic that improved most as this athlete matured from ages 21
to 28 yr. It is noteworthy that at age 25 yr, this champion developed
advanced cancer, requiring surgeries and chemotherapy. During the
months leading up to each of his Tour de France victories, he reduced
body weight and body fat by 4 –7 kg (i.e., !7%). Therefore, over the
7-yr period, an improvement in muscular efficiency and reduced body
fat contributed equally to a remarkable 18% improvement in his
steady-state power per kilogram body weight when cycling at a given
V̇O2 (e.g., 5 l/min). It is hypothesized that the improved muscular
efficiency probably reflects changes in muscle myosin type stimulated
from years of training intensely for 3– 6 h on most days.
J Appl Physiol • VOL
Downloaded from jap.physiology.org on February 15, 2009
"raw data from the January 1993 test that revealed several
additional deviations from the published methodology. Coyle
used a 20-min ergometer protocol (not 25 min), including 2and 3-min stages where respiratory exchange ratios (RER)
exceeded 1.00. An RER >1.00 invalidates use of the Lusk
equations (5) to estimate energy expenditure.”
98 • JUNE 2005 •
METHODS
www.jap.org
General testing sequence.
On reporting are
to the laboratory,
training,
”…all of the published delta efficiency
values
wrong.
…
racing, and medical histories were obtained, body weight was measured ("0.1 kg), and the following tests were performed after inthere exists no credible evidence
to was
support
Coyle's
formed consent
obtained, with procedures
approved by the
Internal Review Board of The University of Texas at Austin. Mechanical efficiencyefficiency
and the blood lactate threshold
(LT) were deterconclusion that Armstrong's muscle
improved."
mined as the subject bicycled a stationary ergometer for 25 min, with
MUCH HAS BEEN LEARNED about the physiological factors that
contribute to endurance performance ability by simply describing the characteristics of elite endurance athletes in sports such
as distance running, bicycle racing, and cross-country skiing.
The numerous physiological determinants of endurance have
been organized into a model that integrates such factors as
maximal oxygen uptake (V̇O2 max), the blood lactate threshold,
muscular efficiency,
these have been found to be the
inandScience–
JulianaasFreire
most important variables (7, 8, 15, 21). A common approach
has been to measure these physiological factors in a given
athlete at one point in time during their competitive career and
to compare this individual’s profile with that of a population of
peers (4, 6, 15, 16, 21). Although this approach describes the
variations that exist within a population, it does not provide
information about the extent to which a given athlete can
improve their specific physiological determinants of endurance
with years of continued training as the athlete matures and
reaches his/her physiological potential. There are remarkably
few longitudinal reports documenting the changes in physiological factors that accompany years of continued endurance
training at the level performed by elite endurance athletes.
This case study reports the physiological changes that occur
in an individual bicycle racer during a 7-yr period spanning
work rate increasing progressively every 5 min over a range of 50, 60,
70, 80, and 90% V̇O2 max. After a 10- to 20-min period of active
recovery, V̇O2 max when cycling was measured. Thereafter, body
composition was determined by hydrostatic weighing and/or analysis
of skin-fold thickness (34, 35).
Measurement of V̇O2 max. The same Monark ergometer (model 819)
equipped with a racing seat and drop handlebars and pedals for
cycling shoes was used for all cycle testing, and seat height and saddle
position were held constant. The pedal’s crank length was 170 mm.
V̇O2 max was measured during continuous cycling lasting between 8
and 12 min, with work rate increasing every 2 min. A leveling off of
oxygen uptake (V̇O2) always occurred, and this individual cycled until
exhaustion at a final power output that was 10 –20% higher than the
Argonne National
minimal power output needed to elicit V̇O2 max. A venous blood
sample was obtained 3– 4 min after exhaustion for determination of
blood lactate concentration after maximal exercise, as described
below. The subject breathed through a Daniels valve; expired gases
were continuously sampled from a mixing chamber and analyzed for
O2 (Applied Electrochemistry S3A) and CO2 (Beckman LB-2). Inspired air volumes were measured using a dry-gas meter (ParkinsonCowan CD4). These instruments were interfaced with a computer that
calculated V̇O2 every 30 s. The same equipment for indirect calorimetry was used over the 7-yr period, with gas analyzers calibrated
against the same known gasses and the dry-gas meter calibrated
periodically to a 350-liter Tissot spirometer.
Blood LT. The subject pedaled the Monark ergometer (model 819)
continuously for 25 min at work rates eliciting !50, 60, 70, 80, and
90% V̇O2 max for each successive 5-min stage. The calibrated ergometer was set in the constant power mode, and the subject maintained a
pedaling cadence of 85 rpm. Blood samples were obtained either from
Address for reprint requests and other correspondence: E. F. Coyle, Bellmont Hall 222, Dept. of Kinesiology and Health Education, The Univ. of
Texas at Austin, Austin, TX 78712 (E-mail: coyle@mail.utexas.edu).
The costs of publication of this article were defrayed in part by the payment
of page charges. The article must therefore be hereby marked “advertisement”
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
maximum oxygen uptake; blood lactate concentration
http://jap.physiology.org/cgi/content/full/105/3/1020
Provenance
Laboratory
46
22
Downloaded from jap.physiology.org on February 15, 2009
about the physiological factors that
contribute to endurance performance ability by simply describing the characteristics of elite endurance athletes in sports such
as distance running, bicycle racing, and cross-country skiing.
The numerous physiological determinants of endurance have
been organized into a model that integrates such factors as
maximal oxygen uptake (V̇O2 max), the blood lactate threshold,
muscular efficiency,
these have been found to be the
inandScience–
JulianaasFreire
most important variables (7, 8, 15, 21). A common approach
has been to measure these physiological factors in a given
athlete at one point in time during their competitive career and
to compare this individual’s profile with that of a population of
peers (4, 6, 15, 16, 21). Although this approach describes the
variations that exist within a population, it does not provide
information about the extent to which a given athlete can
improve their specific physiological determinants of endurance
with years of continued training as the athlete matures and
reaches his/her physiological potential. There are remarkably
few longitudinal reports documenting the changes in physiological factors that accompany years of continued endurance
training at the level performed by elite endurance athletes.
This case study reports the physiological changes that occur
in an individual bicycle racer during a 7-yr period spanning
MUCH HAS BEEN LEARNED
Training stage
METHODS
Downloaded from jap.physiology.org on February 15, 2009
characteristic that improved most as this athlete matured from ages 21
to 28 yr. It is noteworthy that at age 25 yr, this champion developed
advanced cancer, requiring surgeries and chemotherapy. During the
months leading up to each of his Tour de France victories, he reduced
body weight and body fat by 4 –7 kg (i.e., !7%). Therefore, over the
7-yr period, an improvement in muscular efficiency and reduced body
fat contributed equally to a remarkable 18% improvement in his
steady-state power per kilogram body weight when cycling at a given
V̇O2 (e.g., 5 l/min). It is hypothesized that the improved muscular
efficiency probably reflects changes in muscle myosin type stimulated
from years of training intensely for 3– 6 h on most days.
Downloaded from jap.physiology.org on February 15, 2009
Mechanical efficiency
4/8/10
Provenance-Rich Publications


Bridge the gap between the scientific process and
publications
Results that can be reproduced and validated
–  Papers with deep captions
–  Encouraged by ACM SIGMOD and a number of journals


Describe more of the discovery process: people only
describe successes, can we learn from mistakes?
Dynamic (interactive) publications
–  Evolve over time
–  Blog/wiki like=> Science 2.0
–  E.g., http://project.liquidpub.org

Need tools to support this!
Provenance in Science– Juliana Freire
Argonne National Laboratory
47
Provenance and Teaching (1)

Leverage provenance to improve the way we teach
CS and Science
–  http://www.vistrails.org/index.php/SciVisFall2008
–  Also used at UNC, Linkoping, UTEP
–  Lecture provenance: student can reproduce results
Provenance in Science– Juliana Freire
Argonne National Laboratory
48
23
4/8/10
Provenance and Teaching (2)

Homework provenance provides insights regarding
–  Task complexity and nature: number of actions; structural vs.
parameter changes; task duration
–  Student confusion: large branching factor=lots of trial and error
steps

Very detailed (and honest!) feedback: instructors can
leverage this information
[Lins et al., SSDBM 2008]
Provenance in Science– Juliana Freire
Argonne National Laboratory
49
Provenance and Teaching (3)

Homework provenance helps students and instructors to
collaborate
–  Student is stuck, sends his provenance
–  Instructor understands studentʼs problem, provides hints---student
can see what instructor did!
–  They can also collaborate in real time [Ellkvist et al., IPAW 2008]
Provenance in Science– Juliana Freire
Argonne National Laboratory
50
24
4/8/10
Using Provenance to
Teach Electronic Media
[Langefeld and Kessler,
Submitted 2009]
“[...] The students have gotten to the point where
they demand the VisTrails files for every
demonstration just after I complete [it]”
“[...] students used [a vistrail instead of a reference
model] 62% of the time”
Provenance in Science– Juliana Freire
Argonne National Laboratory
51
Argonne National Laboratory
52
Using Provenance to
Teach Electronic Media
http://www.cs.utah.edu/~juliana/videos/maya_playback_slow.mov
Provenance in Science– Juliana Freire
25
4/8/10
Using Provenance to
Teach Electronic Media
[Langefeld and Kessler,
Submitted 2009]
“[...] The students have gotten to the point where
they demand the VisTrails files for every
demonstration just after I complete [it]”
“[...] students used [a vistrail instead of a reference
model] 62% of the time”
“Students who used provenance produced higherquality models”
Provenance in Science– Juliana Freire
Argonne National Laboratory
53
Science 2.0

Web 2.0 technologies has opened up new opportunities
to improve collaboration and information sharing in
science [Shneiderman, Science 2008; Waldrop, Scientific
American 2008]
Provenance in Science– Juliana Freire
Argonne National Laboratory
54
26
4/8/10
Science 2.0: Challenges





Open Science and skepticism: Can we trust that the
information is accurate? If unpublished results are posted
on a wiki, can we prevent others from stealing that work?
Need provenance: determine authorship, enforce
intellectual property rights, validate the integrity of
artifacts and assess their quality, and to reproduce the
artifact
Social Data Analysis: Share data and processes
Add to information overload!
Finding and making sense of information
–  Google is not enough!
–  Need focused search and structured queries
–  Integrate data on the fly

Preserving data
Provenance in Science– Juliana Freire
Argonne National Laboratory
55
Argonne National Laboratory
56
crowdLabs
Provenance in Science– Juliana Freire
27
4/8/10
Conclusions and Future Work

Provenance management is essential for
computational science
–  Provenance can be used to support reflective reasoning
–  Intuitive interfaces for simplifying the construction and
refinement of workflows

Science 2.0: Sharing provenance at a large scale
creates new opportunities [Freire and Silva, CHI SDA, 2008]
–  Workflow/provenance repositories; provenance-enabled
publications
–  Expose scientists to different techniques and tools
–  Scientists can learn by example; expedite their scientific
training; and potentially reduce their time to insight

Provenance + Workflows + Sharing have the
potential to revolutionize science!
Provenance in Science– Juliana Freire
Argonne National Laboratory
57
Conclusions and Future Work




Provenance management is essential for
computational science
Science 2.0: Sharing provenance at a large scale
creates new opportunities [Freire and Silva, CHI SDA, 2008]
Provenance + Workflows + Sharing have the
potential to revolutionize science
Need infrastructure and tools
–  Many challenges and several open computer science
questions
Provenance in Science– Juliana Freire
Argonne National Laboratory
58
28
4/8/10
Acknowledgments


Thanks to VisTrails group
This work is partially supported by the National
Science Foundation, the Department of Energy, an
IBM Faculty Award, and a University of Utah Seed
Grant.
Argonne National Laboratory
Provenance in Science– Juliana Freire
59
Thank you
29