&EPA
United States
Environmental Protection
Agency
Environmental Monitoring
System* Laboratory
P.O. Box 93478
Las Vegas NV 89193-3478
Research and Development
Environmental
Software From
EMSL-LV
EPA 600/8-91/044
July 1991
Environmental
Software From
EMSL-LV
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June 1991
ENVIRONMENTAL SOFTWARE FROM EMSL-LV
Prepared by
Lockheed Engineering & Sciences Company
Environmental Programs Office
1050 E. Flamingo Rd.
Las Vegas, Nevada 89119
Contract Number 68-CO-0049
Work Assignment Manager
J. Jeffrey van Ee
Exposure Assessment Research Division
Environmental Monitoring Systems Laboratory - Las Vegas
P.O. Box 93478
Las Vegas, Nevada 89193-3478
ENVIRONMENTAL MONITORING SYSTEMS LABORATORY - LAS VEGAS
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
Las Vegas, Nevada 89193-3478
-------
NOTICE
Mention of trade names or commercial products does not constitute endorsement or
recommendation for use. The information in this document has been funded wholly (or in part) by
the U.S. Environmental Protection Agency under Contract No. 68-CO-0049 to Lockheed Engineering
& Sciences Company. It has been subject to the Agency's peer and administrative review, and it
has been approved for publication as an EPA document.
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TABLE OF CONTENTS
Introduction,
Overview of Software Packages 2
ASSESS .5
CADRE,
Geo-EAS 9
Hypertext 11
SCOUT 13
Survey 15
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INTRODUCTION
The Environmental Monitoring Systems Laboratory (EMSL-LV) is committed to the development of
quality software that is critical to the monitoring and remediation efforts of the U.S. EPA Regions.
EMSL-LV has undertaken the development of expert systems, computerized information systems,
decision support systems, and "smart" advisors to provide easy access to the specialized knowledge
necessary to meet the decision-making responsibilities in the monitoring and remediation of
hazardous waste sites.
Our early work focused on the computerization of tasks that were previously manually performed
and labor intensive. These software packages, such as the widely used Computer-Aided Data
Review and Evaluation (CADRE) program, met with great success at many levels and paved the way
for further environmental software development.
The next generation of computerization included software capable of addressing specialized skills
such as geophysics, geostatistics, and sampling protocols. Our computer programmers work along
with the scientists in these areas to ensure technical accuracy as well as ease of use.
Now we are looking at the exciting applications that will be possible with emerging CD-ROM,
Hypertext, and Multimedia technology. As always, your needs guide our research. Following the
series of fact sheets and informational material in this catalog, you will find a brief survey form.
Please take a few minutes to complete it and return it to the EMSL-LV. We would like to learn of
your interests.
Expert System and Environmental Software
Development
EMSL-LV supports EPA decision-making and environmental data
processing through the development of expert system and
conventional software with environmental application. Several
systems are already in use and others are under development. The
applications targeted by EMSL-LV have a_direct positive impact on
the quality of the environmental
data obtained by the Agency and
the appropriateness of the data
analysis and interpretation. This
environmental software is
customized to the needs of the
regional user. EMSL-LV provides
follow-up support to all users.
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OVERVIEW OF SOFTWARE PACKAGES
EMSL-LV software development efforts center on computerization of waste site characterization.
Software packages can be used for the various phases of waste site evaluation. Some programs
assist in the project planning while others are used for the analysis of collected data. All of the
packages contribute to the improvement of data quality. This section presents an overview of our
software applications to different stages of environmental data collection projects.
Preliminary Evaluation:
The Geophysics Advisor Expert System assists in the
selection of geophysical monitoring methods
Field Sampling:
ASSESS assists in the planning of soil sampling
events with appropriate quality control samples to
determine sampling errors and their sources. A
computerized Hypertext version of the document,
detailing the ASSESS approach, "A Rationale for the
Assessment of Errors in the Sampling of Soils,* is
available also. The Soil Sampling Expert System
(ESES) is under development to assist in the planning
of soil sampling for metal contaminants.
Sample Analysis:
The Smart Method Index (SMI) aids in the selection of
analytical methods. SMI provides access to data
bases of chemical, physical, and radiological
methods, as well as state action limits for drinking
water quality parameters.
Data Validation:
The Computer-Aided Data Review and Evaluation
System (CADRE) performs data validation of Contract
Laboratory Program organic analysis results. A CLP
inorganic version is under development.
Data Analysis and
Interpretation:
Geo-EAS provides full geostatistical analysis
capabilities for spatially-related data. The Scout
software helps determine anomalous data points in
multivariate data (outliers). These packages work
together and provide advanced graphic capabilities.
ASSESS, CADRE, Geo-EAS, Geophysics Advisor, the Hypertext Rationale, Scout, and SMI are
currently available directly from EMSL-LV or through the Center for Environmental Research
Information (CERI). To request a software package of interest please fill out the enclosed survey
sheet.
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Expert Systems and Environmental Software
Developed by EMSL-LV
SYSTEM
T S A
GeoEas
SCOUT
ASSESS
FUNCTION AND FEATURES
Rationale (or
Assessing Errors In
the Sampling of Soils
Performs geostatistical analysis on spatially-distributed
environmental data. Includes kriging. graphics, and plotting
capabilities.
Assists in exploratory data analysis. Identifies multivariate
outliers, determines the variable(s) in which the anomaly occurred,
and displays the data set through interactive three-dimensional
graphics.
Calculates measurement errors for soil sampling based on results
from appropriate quality assurance samples.
Explains a soil sampling quality assurance approach in a
computerized document through the use of hypertext and provides
access to the ASSESS software.
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Expert Systems and Environmental Software
Developed by EMSL-LV
SYSTEM
FUNCTION AND FEATURES
Geophysics Expert
Advisor
Environmental
Sampling Expert
System (ESES)
Computer-Aided Data
Review and.
Evaluation (CADRE)
Smart Method
Index (SMI)
Provides assistance on the use of geophysical monitoring
methodology for hazardous waste site assessments. Uses expert
system techniques for method selection.
Assists in preparation of field sampling plans to measure ground-
water contamination and metal pollution in soil. Combines expert
system and hypertext techniques for decision support and help.
Performs semi-automated data validation for the Superfund
Contract Laboratory Program multi-method analytical results.
Provides natural language access to various EPA analytical method
and standard data bases.
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United States
Environmental Protection
Agency
v/EPA
INTRODUCTION
FEATURES
SCREENS AND
MENUS
Environmental Monitoring
Systems Laboratory
P.O. Box 93478
Las Vegas NV 89193-3478
TECHNOLOGY SUPPORT PROJECT
ASSESS:
A Quality
Assessment
Program
ASSESS is an interactive
program designed to assist
the user in statistically
determining the quality of
data from soil samples taken
at a hazardous waste site.
EMSL-LV scientists have
developed this public-
domain, user-friendly Fortran
program to assess precision
and bias in the sampling of
soils. The total error in a
sampling regimen is the sum
of measurement variability
and natural variability of the
contamination. It is the field
scientist's challenge to
mitigate the measurement
variability by careful sample-
taking, thoughtful sampling
design, and the use of
recommended quality as-
sessment samples. The
greatest potential for error,
both random and bias, is in
the sampling step. Field
conditions, tool contamina-
tion, operator differences, all
can affect variability and bias
in a sample before it gets to
the analytical step.
The value of ASSESS is its
ability to detect and isolate
error at critical steps in the
sampling and measurement
function. Installation is
simple and is described in the
User's Guide referenced at
the end of this text.
ASSESS plots graphics
directly on the screen to give
the user a quick look at data
or results. All graphics can
be formatted to give hard
copy via pen plotters or other
graphics printers.
ASSESS checks for missing
data and for data input errors
of sufficient magnitude to fall
outside numeric parameters
that have been previously
set.
Reports and plots can be
incorporated into
WordPerfect.
After an introduction screen,
ASSESS presents screens
and menus beginning with
the Data Quality Objectives
(DQO) Screen. The user
inputs known information
about the site and sampling
method and desired confi-
dence ranges.
Next, the user may choose
the Sampling Considerations
Screen. This screen allows
entry of further specifics
about the field sampling,
such as, number of samples
taken, number of batches
analyzed, cost, and batch
data.
The next screen is the
Historical Assessment
Screen that provides options
for entry of historical data that
may be critical to the interpre-
tation of this sampling.
A Quality Assessment Data
Screen follows that allows the
user to view and edit the
quality assessment data that
are called for in the parent
document, A Rationale tor
the Assessment of Errors in
the Sampling of Soils,
referenced at the end of this
fact sheet. These quality
assessment samples are
fundamental to the
successful use of ASSESS.
They include samples that
will check for and evaluate
error in every sampling step.
At this point, it is possible to
produce scatter plots to
visually inspect the
contribution to the total error
that is made by any particular
quality assessment sample
with the confidence in the
error estimates being a
function of the number of
data.
The Transforms Screen
follows and it gives the user a
method for applying unary or
binary operations to the
entire data set. For example,
the field scientist or data
interpreter may wish to
truncate the data, view the
plot as a log or In function, or
perform a basic mathematical
operation on all data.
The Results Screen displays
variances for sample collec-
tion, batch dissimilarity, sub-
sampling error, and handling
differences. This screen also
shows the total measurement
error. A report of the results
and a list of historical infor-
mation and the quality
assessment data may be
saved to a file or printed.
ASSESS is based on the use
of field duplicates, splits, and
performance evaluation
samples that isolate and
assess variability throughout
the measurement process.
An option is provided for the
use of duplicates and splits in
the calculation of variability
when inadequate types and
numbers of performance
evaluation samples exist.
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DATA FILES
STATUS
HARDWARE
REQUIREMENTS
ASSESS incorporates simple
ASCII text files that can be
created with any text editor.
Two output files can be
produced by ASSESS, one of
which can be read as a data
file by ASSESS and the
other, which is not ASSESS
readable, gives a report-like
document. A third type is
provided so that the user may
edit an input file without
entering all the data through
ASSESS.
ASSESS is currently avail-
able in Version 1.0. This is a
prototype environmental
software package. Further
development is planned and
input from field scientists and
EPA Regional personnel is
solicited so that the next
version may be more tailored
to user needs.
ASSESS is based on the
EPA publication, A Rationale
for the Assessment of Errors
in the Sampling of Soils, and
it is strongly recommended
that users familiarize them-
selves with the concepts in
that document before trying
to apply ASSESS.
Hardware requirements for using ASSESS are:
• IBM PC (or compatible)
• 1.2 MB floppy disk drive 5 1 /4" (or 3 112" DD or HD)
• Minimum graphics hardware is Hercules graphics card, monochrome display with graphics
capabilities, CGA and EGA
• Minimum 512 K RAM
• Math coprocessor chip is recommended but not required
REFERENCES
ASSESS User's Guide, U.S. EPA Report, EMSL-LV, in press.
van Ee, J. J., L J. Blume, and T. H. Starks, A Rationale for the Assessment of Errors in the
Sampling of Soils, EPA Report, EPA/600/4-90/013, May 1990.
FOR FURTHER INFORMATION
For copies of the ASSESS program, send preformatted floppy disks with capacity of:
2 31/2'DD,
1 3 1/2" HD, or
1 51/4-HD
to:
Mr. J. Jeffrey van Ee
U.S. Environmental Protection Agency
Environmental Monitoring Systems Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
5: For general questions regarding the use of ASSESS at a site, contact:
Technology Support Center
U.S. Environmental Protection Agency
Environmental Monitoring Systems Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2270/734-3207
FTS 545-2270
FAX/FTS 545-2637
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&EPA
INTRODUCTION
FEATURES
United States
Environmental Protection
Agency
Environmental Monitoring
Systems Laboratory
P.O. Box 93478
Las Vegas NV 89193-3478
TECHNOLOGY SUPPORT PROJECT
CADRE: A Data
Validation Program
The Environmental Monitor-
ing Systems Laboratory - Las
Vegas (EMSL-LV) has
developed a computer
software system to aid
environmental scientists and
data analysts in the evalua-
tion of data generated by the
Contract Laboratory Program
(CLP). This system, CADRE
(Computer-Aided Data
Review and Evaluation)
assists in the validation of
results from various CLP
methods.
CADRE provides data
analysts with a quick and
reliable method for examining
data that will be used tor
decision making at hazard-
ous waste sites. The pro-
gram automates the phases
of data validation that involve
electronic-format data. The
data validation process
involves comparison of
quality control (QC) indicators
used in the analysis with pre-
established data quality
criteria. Non-compliant data
are qualified with appropriate
codes to indicate the severity
of the defect. The final
assessment of the data is
made by the data reviewer,
using the information pro-
vided by CADRE.
Examples of QC parameters
that are checked by CADRE
are: holding time, blanks,
calibration, and precision.
CADRE can read data in
several CLP electronic
formats. It checks for data
completeness, and allow the
user to edit data. After the
validation is complete,
CADRE reports the results.
CADRE can be customized by
the user to validate data
collected using several
methods in the CLP. Users
can configure CADRE to
examine different compounds,
alternate quantitation limits, or
varying QC parameters.
Another customization of
CADRE involves changing
data validation criteria to
meet the needs of a modified
method. The user can
choose, for example, to allow
a longer holding time if the
compound of interest is
unlikely to volatilize or
degrade. The ability to
modify CADRE'S specific
data quality codes provides
the user with greater flexibility
and responsibility.
To protect the data from
tampering and from human
error, a layered security
system allows each user
access to the program
features he or she needs.
The program blends ease of
use with a sophisticated
screen system. Knowledge of
data validation rationale and
microcomputer operation are
recommended for the effec-
tive use of CADRE. A user's
guide, training courses, and
technical user support are
available from the EMSL-LV.
CLP ORGANIC
VERSION
The CLP ORGANIC version
of CADRE evaluates data
from CLP analysis of volatile,
semivolatile, and pesticide
compounds. Volatile and
semivolatile organic com-
pounds are analyzed by gas
chromatography/ mass
spectrometry (GC/MS).
Pesticide analysis is a GC
method.
CLP ORGANIC CADRE can
be customized to evaluate
modified versions of these
routine analyses. It can use
alternate data validation
criteria selected by the user.
Data can be read by CLP
ORGANIC CADRE from the
CLP Analytical Results
Database (CARD) or from
Agency standard format files.
Checks performed by
CADRE include:
quantitation limits
holding time
GC/MS tuning
calibration
internal standards
system performance
surrogate recovery
matrix spike recovery
precision of duplicates
contamination of blanks
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QUICK
TURNAROUND
METHOD VERSION
ADVANTAGES AND
LIMITATIONS
HARDWARE
REQUIREMENTS
The Quick Turnaround
Method (QTM) version of
CADRE reviews data ob-
tained by the QTM methods.
There are QTM methods
available for VOC, PAH,
phenols, pesticides, and
PCB. These methods are
based on the need for fast
extraction and chromato-
graphic analysis within
2 days. For speed and
simplicity, QTM CADRE
works in conjunction with
other software for electronic
data transmission from the
laboratory to the user through
the Agency communications
network.
QTM CADRE is completely
automated. The data re-
viewer needs only to set up
the system and interpret the
reports.
The use of computerized
data evaluation is changing
the workplace for many data
reviewers. The automation of
routine checks will give the
individual more time to
thoughtfully interpret the
results.
It is anticipated that in-
creased accessibility of
computer hardware to
personnel will lead to greater
demand for programs like
CADRE that will streamline
routine work. Currently,
CADRE is being developed
for inorganic methods.
Advantages
Limitations
Fast, complete, and
consistent data validation
Easy customization for
modified methods
Reduction of human error
Automated report
generation
Requires availability of
powerful computer for
efficient use
Reviewer judgement
needed for some decisions
Available for CLP organic
and QTM methods only
Needs complete data set in
electronic format
Hardware requirements for
using CADRE are:
• IBM PC (or compatible)
• MS-DOS (or equivalent)
• Hard disk drive
• 640 K RAM
A math coprocessor chip is
recommended but not
required. For easy use, a
mouse pointer is
recommended.
REFERENCE
Simon, A. W., J. A. Borsack, S. A. Paulson, B. A. Deason, and R. A. Olivero, Computer-Aided
Data Review and Evaluation: CADRE CLP Organic User's Guide, U.S. EPA, June 1991.
^Nc^IOA/
FOR FURTHER INFORMATION
For further information on CADRE,
contact:
Mr. Gary Robertson
U.S. Environmental Protection Agency
Environmental Monitoring Systems
Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2215
FTS 545-2215
For information about the Technology Support
Center at EMSL-L V, contact:
Mr. Ken Brown, Manager
Technology Support Center
U.S. Environmental Protection Agency
Environmental Monitoring Systems Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2270
FTS 545-2270
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X-/EPA
INTRODUCTION
THE METHODOLOGY
EQUIPMENT
REQUIREMENTS
United States
Environmental Protection
Agency
Environmental Monitoring
Systems Laboratory
P.O. Box 93478
Las Vegas NV 89193-3478
TECHNOLOGY SUPPORT PROJECT
Geo-EAS: Software
for Geostatistics
An EMSL-LV
f nvironmcntal
The Environmental Monitoring
Systems Laboratory-Las
Vegas (EMSL-LV) can meet
the needs of scientists who
work with spatially distributed
data. The complexity of
contaminant distribution and
migration at hazardous waste
sites requires a mathematical
method that is capable of
interpreting raw data and
converting them to useful
information. Geostatistics
began in the mining industry
and has grown to include
applications ranging from
microbiology to air monitoring.
Though the application of
geostatistics is crucial to the
delineation of buried contami-
nants, not every field scientist
can be expected to develop
customized geostatistical
algorithms for individual sites.
Geostaticians at the EMSL-
LV developed a software
package, Geo-EAS in 1988.
The current version, Geo-EAS
1.2.1, was released in 1990.
This program offers the
environmental scientist an
interactive tool for performing
two-dimensional geostatistical
analyses of spatially distrib-
uted data.
Geostatistical methods are
useful for site assessment
and monitoring where data
are collected on a spatial
network of sampling loca-
tions. Examples of environ-
mental applications include
lead and cadmium concentra-
tions in soils surrounding
smelters, and sulfate deposi-
tion in rainfall. Kriging is a
weighted moving average
method used to interpolate
values from a data set onto a
contouring grid. Thekriging
weights are computed from a
variogram, which measures
the correlation among sample
values as a function of the
distance and direction be-
tween samples.
Kriging has a number of
advantages over other inter-
polation methods:
Smoothing
Kriging regresses estimates
based on the proportion of
total sample variance ac-
counted for by random noise.
The noisier the data set, the
less representative the
sample and the more they are
smoothed.
Declustering
The kriging weight assigned
to a sample is lowered to the
degree that its information is
duplicated by highly corre-
lated samples. This helps
mitigate the impact of
oversampling hot spots.
Anlsotropy
When samples are highly
correlated in one direction,
kriging weights will be greater
for samples in that direction.
Precision
Given a variogram represen-
tative of the area to be esti-
mated, kriging will compute
the most precise estimates
from the data.
Estimation of the variogram
from sample data is a critical
part of a geostatistical study.
Geo-EAS is designed to
make it easy for the novice to
use geostatistical methods
and to leam by doing. It also
provides sufficient power and
flexibility for the experienced
user to solve practical
problems.
Geo-EAS was designed to
run under DOS on an IBM,
PC, XT, AT, PS2, or compat-
ible computer. Graphics sup-
port is provided for Hercules,
CGA. andEGA. At least 512
Kb of RAM is required, but
640 Kb is recommended. An
arithmetic co-processor chip
is strongly recommended due
to the computationally inten-
sive nature of the programs,
but is not required. Programs
may be run from floppy disk
but a fixed disk is required to
use the programs from the
system menu. The system
storage requirement is ap-
proximately three megabytes.
For hardcopy, a graphic
printer is required. Support is
provided for most plotters.
Design features such as
simple ASCII file formats and
standardized menu screens,
give Geo-EAS flexibility for
future expansion. It is antici-
pated that Geo-EAS will be-
come a significant technology
transfer mechanism for more
advanced methods resulting
from the EMSL-LV research
and development programs.
Geo-EAS software and docu-
mentation are public domain,
and may be copied and dis-
tributed freely.
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MAPS AND MENUS
The Geo-EAS programs use
an ASCII file structure for
input. The files contain a
header record, the number of
variables, a list of variable
names and units, and a nu-
meric data table.
All Geo-EAS programs are
controlled interactively
through menu screens which
permit the user to select op-
tions and enter control pa-
rameters. The programs are
structured to avoid a "black
box" approach to data analy-
sis. Several of the more
complex programs permit the
user to save and read param-
eter files, making it easy to
rerun a program.
The programs DATAPREP
and TRANS provide capabil-
ity for manipulating Geo-EAS
files. Files can be appended
or merged, and variables can
be created, transformed, or
deleted. Transformation
QpgcgjiQPg jnciucje naturai
log, square root, rank order,
indicator, and arithmetic
operations.
POSTPLOT creates a map of
a data variable in a Geo-EAS
data file. Symbols represent-
ing the quartiles of the data
values or the values them-
selves are plotted at the
sample locations.
STAT1 computes univariate
statistics, such as mean and
standard deviation, for vari-
ables in a Geo-EAS data file,
and plots histograms and
probability.
SCATTER and XYGRAPH
both create x-y plots with
optional linear regression for
any two variables in a Geo-
EAS file. SCATTER is useful
for quick exploratory data
analysis, while XYGRAPH
provides additional capabili-
ties such as multiple "y" vari-
ables, and scaling options.
PREVAR creates an interme-
diate binary file of data pairs
for use in yARIO, which com-
putesand displays plots of
variograms for specified dis-
tance and directional limits.
Variogram models can be
interactively fitted to the ex-
perimental points. The fitted
model may be the sum of up
to five independent compo-
nents, which can be any com-
bination of nugget, linear,
spherical, exponential, or
Gaussian models. XVALID is
a cross-validation program
which can test a variogram
model by estimating values at
sampled locations from sur-
rounding data and comparing
the estimates with known
values.
KRIGE provides kriged esti-
mates for a two-dimensional
grid of points. A shaded map
of estimated values is dis-
played on a Geo-EAS file of
kriged grid results.
CONREC generates contour
maps from a gridded Geo-
EAS data file, usually the
output from KRIGE. Options
are provided for contour inter-
vals and labels and degree of
contour line smoothing.
REFERENCE:
Isaaks, E. H. and R. M. Srivastava, An Introduction to Applied Geostatistics, Oxford University
Press, New York, 1989.
AVAILABILITY:
For further information about Geo-EAS, contact Dr.
Evan Englund. Government agencies and academic
or research institutions can obtain a copy of Geo-EAS
with User's Guide at no charge by sending three pre-
formatted high-density diskettes (5-1/4" or 3-1/2") to:
Dr. Evan J. Englund
U.S. Environmental Protection Agency
Environmental Monitoring Systems Laboratory-Las
Vegas
P.O. Box 93478
Las Vegas, NV 89193-3478
FAX: (702) 798-2248
FTS: 545-2248
Others can obtain a copy for a distribution charge of
approximately $45 (includes diskettes, User's Guide,
and USA shipping) from either:
ACOGS or COGS
P.O. Box 44247 P.O. Box 1317
Tucson, AZ 85733-4247 Denver, CO 80201 -1317
FAX: (602)327-7752 Phone: (303)751-8553
FOR FURTHER INFORMATION:
For information about the Technology
Support Center at EMSL-L V, contact:
Mr. Ken Brown, Manager
Technology Support Center
U.S. Environmental Protection Agency
Environmental Monitoring Systems
Laboratory-Las Vegas
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2270
10
-------
United States
Environmental Protection
Agency
INTRODUCTION
THE RATIONALE
DOCUMENT
HOW HYPERTEXT
WORKS
Environmental Monitoring
Systems Laboratory
P.O. Box 93478
Las Vegas NV 89193-3478
TECHNOLOGY SUPPORT PROJECT
Hypertext: A
Showcase for
Environmental
Documents
The amount of "required
reading* for those engaged in
hazardous waste site
remediation is overwhelming.
Documents pile up • often
leaving the scientist no option
but to briefly review the
abstract or the executive
summary. Fortunately, there
exists a computer software
tool, hypertext, that allows for
documentation on disk that
can provide all readers/users
with various layers of infor-
mation. The tiered knowl-
edge in hypertext makes it
ideal for experts in the field of
the publication who can scan
through the general informa-
tion and concentrate on a
particular section. It is also
suited to the novice in the
document's area who can
access highlighted areas for
in-depth definitions of unfa-
miliar terms, full-screen
presentations of tables and
figures, and references to
ancillary works.
Hypertext is an easy-to-use,
timesaving reading tool for
the overburdened scientist.
The ability to read an elec-
tronic book helps each reader
optimize the information-time
ratio.
Scientists at the EMSL-LV
have used hypertext on a
frequently used document, "A
Rationale for the Assessment
of Errors in the Sampling of
Soils* by J. Jeffrey van Ee,
Louis J. Blume, and
Thomas H. Starks. The
original hardcopy document
is about 60 pages long, and
contains 4 figures and 8
tables. The document also
contains several formulas
that may be unfamiliar to
many users. The hypertext
version fits on a floppy disk,
keeps general information
"hidden* unless it's requested
by a novice user, and high-
lights frequently used tables
for easy access.
Hypertext can be applied to
any document that exists in
digital form. The level of
hypertext a document needs
depends on the complexity
and length of the original
document and the anticipated
expertise of the reading
audience.
The Rationale mentioned
above addresses the com-
plexity of the sampling and
analysis of soils for inorganic
contaminants from experi-
mental design to the final
evaluation of all generated
data. Sources of error
abound but they can be
successfully mitigated by
careful planning or isolated
by intelligent error assess-
ment. Error can be either
biased or random. Biased
error is indicative of a sys-
tematic problem that can
exist in any sector of soils
analysis, from sampling to
data analysis. The first step
in analysis of variability is to
establish a plan that will
identify errors, trace them to
the step in which they
occurred, and account for
variabilities to allow direct
corrective action to eliminate
them.
Error assessment should be
understood by the field
scientist and the analyst. To
implement the ideas in the
Rationale document and aid
scientists in the estimation
and evaluation of variability,
the EMSL-LV has developed
a computer program called
ASSESS. By applying
statistical formulas to quality
assurance data entered,
ASSESS can trace errors to
their sources and help
scientists plan future studies
that avoid the pitfalls of the
past.
Scientists at the EMSL-LV
took the disk containing the
Rationale document and
extracted sections such as
the Table of Contents, tables,
figures, and certain equations
and formulas. These sec-
tions appear separately when
selected in the new hypertext
version. Then, throughout
the document, certain words
and phrases were highlighted
so definitions can be ac-
cessed by a keystroke.
When a reader receives a
hypertext document on disk,
he or she can look at the
Table of Contents and decide
which sections to read. By
selecting, for example, the
section entitled "background",
11
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HOW HYPERTEXT
WORKS (Continued)
BRIDGE TO ASSESS
ADVANTAGES AND
LIMITATIONS
HARDWARE
REQUIREMENTS
the reader can be briefed on
the scope of the document.
A term within the Background
section, e.g., "representative"
may be highlighted. Readers
wishing the definition of
•representative" as used in
this document may get an
immediate clarification. In
traditional (linear) hardcopy
documents, a reader must
either wait for the definition to
be clarified in text or seek an
external definition through
outside reference materials.
The Rationale document is
the basis for an EMSL-LV
environmental software
program called ASSESS.
The philosophy and statistical
background in the document
is exercised practically with
ASSESS, which is also
available on disk. The
hypertext version of the
Rationale document prepares
the reader to use ASSESS
and also serves as a physical
link to the program. The last
item on the Rationale docu-
ment hypertext menu is
"ASSESS". After becoming
familiar with the concepts in
the document, the user may
select "ASSESS* to begin to
use the software.
This hypertext linkage of two
or more documents or
programs can simplify and
clarify many software applica-
tions for novice users. By
providing ASSESS users with
the technical background in
its development and Ratio-
nale document readers with a
viable program, hypertext
serves all levels of users in
error-tracing in the complex
application of soil sampling.
Increased availability of
computer workstations and
the development of user-
friendly programs have made
hypertext an almost unquali-
fied bonus to busy readers/
users. Hypertext is easily
and effectively used for:
acronyms and abbreviations,
terms and phrases, tables
and figures, graphics, formu-
las and references.
Advantages
Limitations
Streamlined and non-
interruptive
Linkage to other hypertext
documents
Time-saving for expert;
instructional for novice
Availability of computer
with appropriate hardware
Some computer literacy
required
Hardware requirements for
using this hypertext package
are:
• IBM PC (or compatible)
1.2 MB floppy disk drive,
5 1/4' (or 3 1/2" DO or HD)
Minimum graphics hard-
ware card, monochrome
display with graphics
capabilities, VGA and EGA
Minimum 640 K RAM
Math coprocessor chip is
recommended but not
required
REFERENCES
Text, ConText, and Hypertext; Writing with and for the Computer, E. Barrett, ed., The MIT
Press, 1988.
van Ee, J. J., L J. Blume, and T. H. Starks, A Rationale for the Assessment of Errors in the
Sampling of Soils, EPA Report, EPA/600/4-90/013, May 1990.
FOR FURTHER INFORMATION
For more details on Hypertext and the
Rationale document, contact:
Mi-. J. Jeffrey van Ee
U.S. Environmental Protection Agency
Environmental Monitoring Systems
Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2367
For information about the Technology Support
Center at EMSL-L V, contact:
Mr. Ken Brown, Manager
Technology Support Center
U.S. Environmental Protection Agency
Environmental Monitoring Systems Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2270
12
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f/EPA
United States
Environmental Protection
Agency
Environmental Monitoring
Systems Laboratory
P.O. Box 93476
Las Vegas NV 89193-3478
TECHNOLOGY SUPPORT PROJECT
Scout: A Data
Analysis Program
INTRODUCTION
FEATURES/
SPECIFICATIONS
MENUS
The complexities of correct
data interpretation challenge
environmental scientists
everywhere. Environmental
software packages have
been developed to address
the various needs of data
analysts and decision mak-
ers. One frequent need is for
the reliable determination of
outliers in a data set. Scout
is a program developed to
identify multivariate or
univariate outliers, to test
variables for lack of normal-
ity, to graph raw data and
principal component scores,
and to provide output of the
results of principal compo-
nent analysis. Scout pro-
vides interactive graphics in
two and three dimensions.
There are many advantages
of a graphical display of data
in a multidimensional format:
it allows a quick visual
inspection of data, it accentu-
ates obvious outliers, and it
provides an easy means of
comparing one data set with
another. Scout has the
flexibility to allow viewing and
limited editing of a data set.
Scout features on-line help,
with a "built-in" users guide.
Scout is a valuable addition
to the library of environmental
software packages available
from the EMSL-LV.
Scout is a public domain,
Turbo Pascal program that is
user friendly and menu
driven. Scout reads ASCII
data files that are in Geo-
EAS format. The first line of
aQeo-EASdatafileisa
comment line, generally used
to describe the origin of the
data. The second line of the
file must contain the number
of variables • always a
number greater than or equal
to 1 and less than or equal to
48. The next lines contain
variable names in the first 10
columns and the associated
values in the next 10 col-
umns. Scout is compatible
with most IBM personal
computers that have an EGA,
VGA, or Hercules graphics
system. Scout will run with or
without a math co-processor,
but this feature is preferred
for handling floating point
calculations. A fixed disc
drive is strongly recom-
mended because Scout
performs many transfers
between memory and disc
during execution. On-line
help is available throughout
Scout and the user can
access it by selecting the
•System" option in the main
menu and then selecting
'Information'.
There are five menus in
Scout: file management,
data management, outliers,
principal components analy-
sis, and graphics.
After the introduction screen,
the user should choose the
"File Management* option on
the main menu. This option
allows the user to load the
Scout data file or read an
ASCII data file and to access
various subdirectories of
data. Scout saves data files
in two formats: binary and
the Geo-EAS ASCII format.
Scout has the ability to
search for file names, includ-
ing wild cards. The current
search string is printed at the
top of the window. Other
options in this area include
•Write ASCII Data File" for
saving the Scout file and
"Merge Two Data Files' for
combining two files into one.
The second menu is "Data
Management" which includes
options for editing data,
variables, and observations.
This menu also displays
summary statistics, such as
mean, standard deviation,
and variance. Additionally,
there is a Transform" option
which allows the user to test
each variable for lack of
normality, based on the
Kolmogorov-Smimov test at
the five percent significance
level. The critical value, test
statistic, and apparent
conclusion are displayed.
The Anderson-Darting test is
also performed and a hori-
zontal histogram is displayed
at the bottom of the screen.
Menu three is "Outliers",
which applies two powerful
tests for discordancy to the
data: the (Maha)anobis')
generalized distance, and the
(Continued)
13
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MENUS (Cont.)
Mardia's multivariate kurtosis
test. After selecting "Outli-
ers", the user can tell Scout
which variables to test, or use
the default wherein Scout
tests all variables. The user
must then decide to use the
generalized distance test or
Mardia's kurtosis. If a large
proportion of the data is
identified as discordant, the
user should be cautious that
the problem may be due to
lack of multinormality. The
outlier report may be dis-
played, sent to a file, or
printed. By selecting "Causal
Variables" the user can test
each variable for its contribu-
tion to the discordant nature
of the outlier. This option can
trace some independent
errors, such as typographical
or transcription errors.
The fourth menu is "Principal
Component Analysis" which
allows the user to select the
variables to be used and to
display covariance or correla-
tion. By choosing the "View
Components'1 option, the user
can view the eigenvectors
and eigenvalues of the PCA.
Scout will prompt the user to
specify whether or not to
include previously deter-
mined outliers. The user can
graph the component scores,
which are products of the
eigenvectors and the stan-
dardized observation vectors.
A Transform Data" option is
available to change the data
in memory from observations
to component scores.
The fifth, and final, menu is
"Graphics" which features
two graphics systems: two-
dimensional and three-
dimensional. The two-
dimensional system is used
to display scatter plots and
x-y plots. The three-dimen-
sional system is used to
display three variable plots,
which can be rotated to
illustrate the added dimen-
sion. The user can modify
graph colors and shapes.
Graphics screens may be
saved by writing to a file on
disk. The user can change
the size of the graph by
zooming in or out using the
V or"-" keys. The four
arrow keys are used to rotate
the graph. The left and right
arrows rotate the graph
around the Z axis. The up
and down arrows rotate the
graph around an imaginary
horizontal axis that passes
through the origin. Another
feature, "Search Observation
Mode", is available and
allows users to identify the
individual observations
shown on the graph.
REFERENCES
Chemometrics: A Textbook. Massart, D. L, B. G. M. Vandeginste, S. N. Deming, Y. Michotte,
and L. Kaufman, Volume 2 in the Series "Data Handling in Science and Technology",
B. G. M. Vandeginste and L. Kaufman, eds., Elsevier, Amsterdam, the Netherlands, 1988.
Gamer, F. C., M. A. Stapanian. and K. E. Fitzgerald, Finding Causes of Outliers in Multivariate
Data, J. Chemometrics, in press.
FOR FURTHER INFORMATION
For copies of the Scout program, contact:
Mr. Jack Teuschler
U.S. Environmental Protection Agency-CERI
26 King Drive
Cincinnati, OH 45268
(513) 569-7314
FTS 684-7314
For additional technical information about
Scout, contact:
Dr. George Flatman
U.S. Environmental Protection Agency
Environmental Monitoring
Systems Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2628
FTS 545-2628
For information about the EMSL-LV
Technology Support Center, contact:
Mr. Ken Brown, Manager
Technology Support Center
U.S. Environmental Protection Agency
Environmental Monitoring Systems Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2270
FTS 545-2270
14
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SURVEY
1. I am familiar with (check appropriate box):
1 ' ASSESS ' ' Geophysics Advisor
1 ' CADRE ' ' Hypertext
1 ' Geo-EAS ' ' SCOUT
2. I would be interested in receiving a copy of the software package, and
my preformatted disk(s) are enclosed.
3. My job is mainly in the area(s) of:
1 ' Geology ' ' Computer Programming
1 ' Chemistry ' ' Statistics
1 ' Biology ' ' Sampling
1 ' Other, please specify:
4. The software program that would best help me in my job would be:
5. My computer is a:
15
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SURVEY (CONT)
6. You may contact me at:
Name:
Address:
State/Zip Code:.
Phone #:_
Fax#:
E-Mail:
Please return this survey and direct any questions to:
Mr. J. Jeffrey van Ee
U.S. Environmental Protection Agency
Environmental Monitoring Systems Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702) 798-2367
16
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