Electronic Data Management and
Workflow
Imagine the result

Introduction
Jane Kennedy
Project Chemistry & Data Quality
ARCADIS U.S., Inc.
New Orleans

EDD Management and Data
Workflow Overview
• ARCADIS data management approach
• Planning & setup
• Data acquisition
• Laboratory EDD prep and submittal
• EDD receipt and review
• Data distribution
• Questions

Electronic Data Management
• Why manage data electronically?
• Consistency
• Confidence
• Efficient access to information

ARCADIS Approach to
Data Management
PLANNING ACQUISITION MANAGEMENT VALIDATION REPORTING
Plan data Acquire data Manage data Evaluate data Provide
acquisition, efficiently with tools quality streamlined
management , appropriate compliance reporting
quality, and to output with project and data
reporting
systems requirements plan accessibility
to users
Increase productivity of technical staff

ARCADIS
Data Management Systems
• EQuIS 3.2
• Desktop or server
• EQuIS 5
• Enterprise system
• Automation of EDD
management
• Internally developed system – Access platform
• Server
• Microsoft Excel
• Desktop

EQuIS 5 Deployment
• Involved variety of disciplines and stakeholders
in selection
• Data managers
• Corporate IT
• GIS personnel
• Project teams
• Senior management
• Clients
• Evaluated overall system applications

Planning
A data acquisition and
management strategy
defines:
•Coordination of
appropriate resources
•Project quality assurance
process
•Data deliverables
•Communication pathways
to ensure data usability
and accessibility

Stakeholder Participation
•Field Data •Boring Logs
Database
• Project staff
•Lab Data •Maps/Figures
• Provide information to
•3rd Party Info •Data Tables
labs and DMs
• Data managers
• Receipt, import, query and export
• Data visualization and project Team
• Communicate data export content requirements
to DMs

Project Planning Documents
• Work Plan, SAP, FSP, QAPP
• Document performance requirements
• Summarize project activities
• Define project goals
• Establish data quality objectives
• Permits
• Corrective action goals
• Risk standards (RECAP)

Data Management Plan
Data Management Plan
• Based on project planning documents
• Define personnel responsibilities
• Set up work flow
• Data acquisition strategy
• Establish project nomenclature
• Create reference values
• Detail storage and archive

Sample Collection Planning
• Establish location and sample
nomenclature
• Identify locations
• Monitoring wells
• Soil depths
• Sample matrix
• Trip blanks, equipment blanks
• Field duplicates
• Provide information to field team and data
manager prior to sampling

Database Set Up
• Prepare chemistry and geology database
• Use applicable project nomenclature
• Acquire geographic coordinates
• Provide project specific criteria to data manager
• Permit limits
• Screening standards/RECAP limits
• Corrective action goals
• Identify export requirements
• Trend plots, contours, charts
• GIS or CAD

Field Data Acquisition
• Establish field data requirements
• Well construction
• Geologic information
• Water quality parameters
• Water levels
• Identify data acquisition format
• Manual entry onto forms with transfer later
• Electronic acquisition with nightly upload
• Geographic coordinates
• Survey or GPS

Uploading Field Data
• Routes of data transfer
• Who has
responsibilities?
• What format?
• Quality Control Review
prior to submittal to
Data Manager
• Geographic coordinates
• Get them to the Data
Manager in a timely
manner

Chain Of Custody Documentation
• Complete COC
with as many EDD
expectations as
possible
• Sample ID
• Matrix
• Sample type
• Samples to be
used for site
specific QC

Communicate Project
Requirements to Laboratory
• Laboratory is a partner in the project success
• Communication prior to sample collection is
crucial
• Data quality requirements
• Performance expectations
• Deliverables
• Communication tree

What the Laboratory Needs
• List of samples and performance
criteria
• Sample nomenclature
• Select EDD Format prior to sample
submission
• DEQ format
• Consultant format
• Send project reference values
• Confirm lab has programming
completed to generate required EDD

Laboratory EDD Preparation
• Understand the requirements
• Spend the time to develop the 4-file EDD NOW
• Minimize manual entry
• Report and EDD MUST match
• Rounding routines
• Manual data entry peer review
• Data Checker (EDP) = zero defects
• EDD requires specific naming convention
• Follow the rules or it will get kicked back

Reference Values Missing
• Contact client for direction
• Don’t make anything up
• Review reference values for
other options
• Get email confirmation of
directions
• Include additions changes in
email submission of EDD

Potential EDD Pitfalls
Sample Table
• Confirm sample ID and handwriting interpretations
• Do not add any suffixes to the sample ID unless
directed by consultant
• Sample Delivery Group (report number) must be
populated
• Lab may be required to populate start and end depth
for soils
• Sample receipt date must be populated

Potential EDD Pitfalls
Sample Table (continued)
• Sample type is critical because some
samples require listing parent samples
• Field duplicates – lab may need to use
sample type of “N” to clear checker
• MB = Material Blank not method blank (LB)

Potential EDD Pitfalls
Test Table
• Subsample amounts must be populated
• Lab name must be populated
• Sample dates and times must match sample file
• Percent moisture cannot be null for solids
• Analysis type must be appropriate for dilutions,
re-analyses
• Understand the use of T, D, N for total and
dissolved field
• Caution with methods where multiple parameters
reported (e.g. Method 300 or 352.3)
• Time format can cause problems

Potential Pitfalls
Result Table
• Do not add suffixes to the CAS number
• Only 1 result is reportable = Yes (multiple dilutions)
• If the detect flag is yes, the result value cannot be
null
• Units fields cannot be null for populated fields
requiring a definition of value units
• Subsample amount must be populated
• Quality control data must be included in the
appropriate field

Additional Laboratory Challenges
• Can’t load project reference
values
• Data Checker continues to show
errors
• Do NOT try to re-write the export
every time you have samples
• Make sure to save the export to
laboratory system
• LIMS changes - CAUTION

EDD Submission
• Data checker (EDP) = zero defects
• Document problem resolution
• Follow EDD naming convention
• Email EDD to appropriate venue(s)

PDA Data Receipt:
• Variety of information received in Electronic
Data Deliverable (EDD) for import into the
Field
EDD database
Lab Lab
EDD
EDP
Submitter
Notice
Email
Web
FTP
Manager
Notice
DATABASE

Consultant EDD Management
• EDDs received by project
Data Manager data manager or via direct
upload system
• EDP confirms
•Field Data •Boring Logs completeness and
•Lab Data
Database
•Maps/Figures
compliance (3.2 v 5)
• Do not correct the EDD
•3rd Party Info •Data Tables
• If it is not compliant, return
to lab

EDD Upload to Project Database
• Manage EDD upload schedule
• Group work in batches
• Tracking is critical
• Report and EDD may not arrive
at same time
• Verification / validation of
conformance

Consultant Database Updates
• Verify sample IDs
• Laboratory data flag definitions
• Run update queries to move qualifiers
• Add location codes to link samples
• Field information
• Field parameters
• Parent samples for field dups
• Perform project specific queries

Confirmation of Content
• Export data to crosstab format
• Review a percentage of data against lab reports
• Define percentage in project plan process
• If deficiencies are identified return to lab for
correction
• Rounding Routines
• Significant Figures
• Data Flags

Track Changes to the Database
• Identify fields in the database to document
changes by data managers
• Historical data source
• Laboratory Flagging changes
• Special data qualifier definitions
• Validated, Verified, or Neither
• Validator comments/reason for qualification
• Updates of project information

Electronic Data Quality Screening
• Screening tools are available
• Critical to have appropriate QC
information
• Populate data fields appropriately
• Understand the limitations
• Qualified personnel review of
screening tool reports

‘My’ Format AND LEADMS
• Create LEADMS EDD export
from data system
• If managing 2 EDDs (client
specific and LEADMS)
• Ensure any changes in the
desktop version are
transferred to LEADMS
• Perform confirmation QC to
verify

Exports to Data Users
Tabular data,
Crosstabs
Charts,
Graphs
Email ‘Pretty’
Reports
Web
FTP
Exports for
data analysis
and
visualization
DATABASE

Data Exporting
Data Manager • Quality in = Quality out
•Field Data •Boring Logs • Exports can be automated,
scheduled or team
Database
•Lab Data •Maps/Figures coordinated
•3rd Party Info •Data Tables
• Provide information to the
DM to yield efficiency

Data Export Automation
• Database monitors incoming data and generate reports
based on arrival of:
– New data
• Anytime there is new data for facility 123, build
Report A and email it to me and all my group.
– New detections
• Anytime there is new Arsenic data greater than 15
ppb for facility 123, build Report B and email it to
just me and my client.
– Date
• Build Report C for facility 123 and email it to the
entire group on the 15th of every month.
.

Data Export to
Visualization Programs

Thank You
Jane Kennedy
ARCADIS U.S., Inc.
Phone: (504) 832-4174
Cell: (225) 205-8256
Email:
jane.kennedy@arcadis-
us.com