Data Management Data Management Data Management Data Management Best Management PracticesBest Management PracticesChris Mickle Chris Mickle CambridgeCambridgeChris Mickle Chris Mickle –– CambridgeCambridgeData Analysis and Statistics Subdiscipline LeaderData Analysis and Statistics Subdiscipline Leader

Environmental Data Management Group LeaderEnvironmental Data Management Group Leader

Today’s TopicsToday’s Topics

Importance of a QA/QC Process

Establishing database structures and policies

Protecting client confidentiality and handling COIs

Defining data deliverables and specifying EDD formats

Defining and customizing report deliverables

Managing users and reports in EQuIS Enterprise

What is Site Data Management?What is Site Data Management?

Site Data Management – The collection, processing, analyzing, and communicating project site data to assist in decision makingin decision making.

“A good system’s design will promote it’s use, and the ultimate value of data are in the data’s use rather than in the storage.”

“The real importance of a data management system is to provide the end user with a consistent data set of known quality”

Long-Term Groundwater Monitoring – The State of the Art. The Task Committee on the State of the Art in Long-Term Groundwater Monitoring Design of the Environmental and Water Resources Institute. Reston, Virginia: American Society of Engineers, 2003.

ModelingModeling GISGISEnv. Data Env. Data

ManagementManagement

gg33--D VisualD Visual

DataData

WaterWater

DataData

AdministrationAdministrationWaterWater

ResourcesResources

DataDataManagementManagement

SystemSystem

PublicPublicRelationsRelations

AssetAssetManagementManagement

DocumentDocumentManagementManagement

RemediationRemediation

CADD dataCADD dataDigitalDigital

SatelliteSatellite

Land Use &Land Use &ManagementManagement

SatelliteSatelliteDataData

Benefits of Site Data ManagementBenefits of Site Data Management

Enhances communications by providing project team access to the data

Facilitates rapid data retrieval and analysis Facilitates rapid data retrieval and analysis

Ensures data integrity and control – data security

Maximize confidence and certainty associated with dataMa e co de ce a d ce ta ty assoc ated w t data

Provides for data to be transitioned to clients/owners

Complies with contract requirements

Provide data that are of known quality for legal and technical defensibility

Consequences of Poor Site Data Consequences of Poor Site Data Consequences of Poor Site Data Consequences of Poor Site Data ManagementManagement

Garbage in and garbage out

Interpretation of bad data means bad results

Low productivity - inefficiencies

Lack of process and accountability

Limited or no access to data

Version control problems

Loss of team cohesion and cooperation

Impact of reputation as a good data provider

Quality Management DefinedQuality Management DefinedQuality Management DefinedQuality Management Defined

Quality – The totality of features and characteristics of a product Q y y por service that bears on its ability to meet the stated or implied needs and expectations of the user.

Quality Assurance – An integrated system of management activities involving planning, implementation, assessment, reporting, and quality improvement to ensure that a process, reporting, and quality improvement to ensure that a process, item, or service is of the type and quality needed and expected by the client.

Guidance for Labeling Externally Validated Laboratory Analytical Data for Superfund Use. U.S. Environmental Protection Agency Office of Solid Waste and Emergency Response. Washington, DC 20460, 13 January 2009.

Quality Management DefinedQuality Management DefinedQuality Management DefinedQuality Management Defined

Quality Control – 1) the overall system of technical activities that measures the Q y ) yattributes and performance of a process, item or service against defined standards to verify that they meet the stated requirements established by the customer.

2) Operational techniques and activities that are used to fulfill requirements for quality. quality.

3) The system of activities and checks used to ensure that measurement systems are maintained within prescribed limits, providing protection against “out of control” conditions and ensuring that the results are of acceptable quality.

Quality System – A structured and documented management system describing the policies, objectives, principles, organizational authority, responsibilities, accountability, and implementation plan of an organization for ensuring quality in its work processes, products (items), and services. The quality system provides the framework for planning, implementing, and assessing work performed by the organization and for carrying out required quality assurance (QA) and quality control (QC) activities

Guidance for Labeling Externally Validated Laboratory Analytical Data for Superfund Use. U.S. Environmental Protection Agency Office of Solid Waste and Emergency Response Washington DC 20460 13 January 2009and Emergency Response. Washington, DC 20460, 13 January 2009.

Quality Management Requirements Quality Management Requirements Q y g qQ y g qfor Successful Data Managementfor Successful Data Management Standardized Planningg

Effective Communication

Team Commitment

Integrated Quality Controls

Advanced Tools

“To manage data properly requires planning, adequate support, and a long-term commitment to a data management program.”

“A good data management system should be one that is modeled g g yaccording to how the data are collected and processed, has specifically defined data elements, and is very well documented”

Long-Term Groundwater Monitoring – The State of the Art. The Task Committee on the State of the Art in Long-Term Groundwater Monitoring Design of the Environmental and Water Resources Institute. Reston, Virginia: American Society of Engineers, 2003.g y g

Data Quality Management Process StepsData Quality Management Process StepsQC 0QC 0

Project Planning and Setup

QC 1

Sampling Data Collection

QC 2

Confirming Data Source

QC 0QC 0 QC 1QC 1

QC 2QC 2

and Setup Collection Data Source

QC 3QC 3

Collection of Analytical and Field Sample

QC 4

Validation, Qualification &

Usability Lab EDD

Database Entry InformationQC 5 – GIS Spatial Database Check

QC 6 – Well, Boring, Well Construction

QC 7 – Field Parameters

QC 8 – O&M Data

QC 3QC 3QC 4QC 4

QC 5,6,7,8QC 5,6,7,8

Field Sample InformationReview

QC 8 O&M Data

QC 9

Database Quality Control

QC 10

Data Using and Reporting

QC 9QC 9QC 10QC 10

Quality Control

Data Quality Management Process StepsData Quality Management Process StepsQC 0 Project Planning and Setup QC 0 – Project Planning and Setup

•Project scoping and definition - CSM•Identify historical information •Identify data quality objectives (DQOs)•Define roles and responsibilities with

communication and data flow process•Develop work plans (QAPP, SAP, DMP, FSP)•Develop subcontractor SOWs

QC 1 – Sampling Data Collection•Follow WP/SAP/QAPP/DQOs•Field Activity Preparation•Field Data Collection

QC 2 – Confirming Data Sources•Confirm samples shipped correctly•Confirm samples arrive at the lab in

good condition•Identify any deviations from the WP

and QAPP

QC 0QC 0 QC 1QC 1

QC 2QC 2

•Develop data validation and evaluation criteria•Define deliverables•Define data collection methods•Plan how the data is going to be managed

(EQuIS)

•Field Sample Collection•Submitting Samples for Analysis

•Confirm sample information identified correctly

QC 3 Collection of Analytical and QC 3 – Collection of Analytical and Field Sample Information•Field Sample information forwarded to

data manager – actual sample/analyses communicated (FTL)

•Database populated with sample information – from the field (DM)

•Receive EDD data packages from the lab d r th g t LC b f r g i g t

QC 4 – Validation, Qualification & Usability Lab EDD Review

•Data validation and evaluation•Data review•Evaluate data quality•Ensure EDDs are edited correctly•Technical review of Data

Database Entry InformationQC 5 – GIS Spatial Database Check

QC 6 – Well, Boring, Well Construction

QC 7 – Field Parameters

QC 8 – O&M Data

QC 3QC 3QC 4QC 4

QC 5,6,7,8QC 5,6,7,8

and ensure they go to LC before going to Data Validator (SC/LC)

•Track EDDs and data packages for lab analytical completeness (SC/LC)

•Technical review of Data Validation

QC 8 O&M Data

QC 10 D t U i g d R tQC 9 – Database Quality Control•QC data prior to making available•Review output tables for completeness•Follow-up with end user to resolve any

discrepancies•Communicate any issue resolutions to the

RPT•Track comments in the database where

QC 10 – Data Using and Report

Provide action level criteria

Request data tables

Review and evaluate data tables generated for accuracy and completeness

Provide feedback to DM on changes

QC 9QC 9QC 10QC 10

possibleProvide feedback to DM on changes needed to database

Data Management Plan ObjectivesData Management Plan Objectives

Id tifi th j t bj ti d i d d li bl Identifies the project objective and required deliverables

Describes the data quality and management objectives

Summarizes the types of data required by the project

Defines roles and responsibilities of the data management Defines roles and responsibilities of the data management

team and identifies lines of communication

Defines the workflow and data management activities Defines the workflow and data management activities

Data Management Plan Objectives Data Management Plan Objectives Data Management Plan Objectives Data Management Plan Objectives cont’cont’ Provide laboratory and electronic data deliverables (EDD) Provide laboratory and electronic data deliverables (EDD)

requirements for transfer of electronic data to a database

Standardize data deliverable processes

Define EDD formats for field, geological, survey and any other data that needs captured and how it will be delivered

Unique station/sample identifications

GIS deliverable formats

File storage and backup

Reporting needs and format

Site Data Management Project TeamSite Data Management Project TeamSite Data Management Project TeamSite Data Management Project Team Project Manager (PM)

CDM Site Data Management Administrators (SDMA)

Project Engineer (PE) & Project Geologist (PG)

Field Team Leader (FTL) & Field Team (FT) Field Team Leader (FTL) & Field Team (FT)

Sample Coordinator (SC) & Laboratory Coordinator (LC)

Project Chemist (PC) & Data Validation Coordinator (DV) Project Chemist (PC) & Data Validation Coordinator (DV)

Data Manager (DM)

GIS Leader (GIS)G S eade (G S)

Project Planning Team (PPT)

Report Preparation Team (RPT)

Unique Station Naming Unique Station Naming Unique Station Naming Unique Station Naming ConventionConvention

Primary step in data collection and warehousingPrimary step in data collection and warehousingExample Field Environmental Station Naming Scheme

First Segment Second Segment Facility Site Type Site Number Station Type Station Number Qualifier

AA A NNN AA NNN AAA A NNN AA NNN ANote: “N” = numeric, “A” = alphanumeric

Facility: AA = Facility Name

Station Type: MW = Monitoring Well SO = Soil Sample Location

Location Type: S = Site W = Solid Waste Management Unit (SWMU) A = Area of Concern (AOC) Location Number S02 = Site 2 (Former Hazardous Waste Disposal Unit)

SD = Sediment Sample LocationSW = Surface Water Sample Location Number: Sequential Station Number

S02 = Site 2 (Former Hazardous Waste Disposal Unit)S05 = Site 5 (Stormwater Drainage Canal) S09 = Site 9 (East River) W32 = SWMU 32 (Metal Shop Sump) W33 = SWMU 33 (Pesticide Shack) A11 = AOC 11 (Hydraulic Fluid Spill)

Qualifier: S = Shallow D = Deep

Laboratory EDD FormatsLaboratory EDD Formats

Client contract requirements

Regulatory agency requirements

• EPA Region 2, NYSDEC, NJDEP etc

CDM/EarthSoft customized format

• EZEDD with additional fields included for data validation

• EDD to store all lab quality control data in the database

Include EDD requirements in laboratory SOW and QAPP Include EDD requirements in laboratory SOW and QAPP

Management policy for reference values

Field EDD FormatsField EDD Formats

Client contract requirements

Regulatory agency requirements

• EPA Region 2, NYSDEC, NJDEP

If not required specify CDM format

Geology EDD include all location, well, geologic data

Import EDD from gINT

M t li f f l Management policy for reference values

Field Data TemplatesField Data Templates

Database Structures and PoliciesDatabase Structures and Policies

Policies and processes provide standards for facilitating the planning, collection, formatting, and analysis of data to support decision makingsupport decision making

Database structure requirements

• How many databases do you need?

• How many servers do you need?

• How will client facilities be organized and grouped on the server?server?

• How does the grouping of facilities impact reporting?

• Will data from multiple facilities need to be queried and p qreported?

Database Structures and Policies Database Structures and Policies Database Structures and Policies Database Structures and Policies cont’cont’

Will your database structure mitigate conflicts of interest and comply with contract confidentiality agreements?

Will b h i EQ IS f li ? Will you be hosting EQuIS for your clients?

What type of licensing will you implement with EarthSoft and your clients?y

How often will you back up your databases?

How often will you shrink your databases?

EQuIS 5 ServerEQuIS 5 ServerProposed Proposed Database Database Structure Structure

Shared Reference &

Shared Reference &

Shared Reference &

DatabaseDatabase

Reference &Business Rules

DatabaseDatabase

Reference &Business Rules

DatabaseDatabase

Reference &Business Rules

NSGNSG(Private Sector)(Private Sector)

FSGFSG(Federal Projects)(Federal Projects)

Project SpecificProject Specific

Client XFacility 1

Region 2Site 1

Facility 1Building AB ildi g BFacility 2

Client ZFacility 1

Site 2

Region 3

Building B

Facility 2Phase 1Phase 2Phase 2

Aligns with CDM Core ValuesAligns with CDM Core ValuesAligns with CDM Core ValuesAligns with CDM Core Values Excellence – superior performance as viewed through the

f li t l d h h ldeyes of our clients, employees, and shareholders.

Initiative - anticipating and taking action, focused on what counts most.

Teamwork - working together to achieve results and build positive relationships.

Sh d C i l l i hi b CDM d Shared Commitment - mutual relationship between CDM and employees based on shared goals, trust, and respect.

Integrity - dealing honestly and respectfully with clients, g y g y p y ,employees, shareholder, business associates, and the community; conducting business consistent with…laws and…standards.

Populating EQulSPopulating EQulSPopulating EQulSPopulating EQulS

Field Data Collection Analytical LabDrilling, Soil Sampling, WellInstallation, Analytical Sampling

Analytical Lab

Analytical Results, QA/QC

EDPEDP EDPEDPEQuIS—

Management of Data

Location, Sample, Result;Lithology, Water Level,

Geophysical, …

EDP = EQuIS Data Processor

Logs, Reports, Contours, Cross-Sections, Models, Statistics, …

EQuIS Data Workflow ProcessEQuIS Data Workflow Process

GISGISLabData

AutomatedData Review

(ADR)

EQuIS Data Processor (EDP)

(Standalone)

BoringsBorings

CrossCrossCrossCrossSectionsSections

e

EnterpriseEDP

PlumesPlumesSample

EQuISSample Planning EDDsEDDs

Inte

rfac

e

Field

StatisticsStatistics

TrendTrendAutomated Data

EQuIS

I

EDGE

Data

90% ofLevel 3

Validation

View and repairdata before it

enters database

PlotsPlots

R tR t

Checks & Loading

Validationenters database. ReportsReports

Define Report DeliverablesDefine Report Deliverables

Grid Report – Sample Inventory

Full summary tabley

Hits only table

Statistics tableStatistics table

CDM CARSTAT and ProUCL data tables

Reporting Detection Limit table Reporting Detection Limit table

Field Duplicate Report

Completeness Report Completeness Report

Inorganic Contaminate Summary TableInorganic Contaminate Summary Tableg yg y

GIS Used to GIS Used to GIS Used to GIS Used to Create Create Contour Contour Contour Contour MapMap

Spatial Analyst Spatial Analyst used used interactively to interactively to interactively to interactively to create figurecreate figure

Web PortalsWeb Portals

Use web portals to share information, handbooks, guides, , g ,templates, and training material and amongst your and amongst your team

Web Web Web Web PortalsPortals

Data Analysis and Statistics Data Analysis and Statistics Data Analysis and Statistics Data Analysis and Statistics Technical Resource GroupsTechnical Resource Groups

Web Web Web Web PortalsPortals

A Change Management ProcessA Change Management ProcessA Change Management ProcessA Change Management Process

John Kotter

• Harvard Business School professorp

graduated from MIT

• Best-selling author of Leading Change

• #1 Leadership Guru in America (Business Weeksurvey)

A Change Management ProcessA Change Management ProcessA Change Management ProcessA Change Management Process

Kotter’s 8-step process developed based on years of research with real organizations

Illustrated the process through a penguin fable, Our Iceberg is Melting

A Change Management ProcessA Change Management ProcessA Change Management ProcessA Change Management Process Create a Sense of Urgency – Help others see the need for immediate

action

Establish a Guiding Team – A powerful group with: Leadership skills, Bias for action, Credibility, Communication ability, Authority, Analytical skills

Develop Change Vision and Strategy - Clarify how future will be different and how you will make that future a reality

Communicate for Understanding and Buy-in – Get as many as possible to accept the vision and strategy

Empower Others to Act - Remove barriers for those who want to help

Produce Short Term Wins - Visible, unambiguous successes ASAP, g

Don’t Let Up - Press harder and faster for successes; Be relentless until vision is a reality

Create a New Culture - Hold on to the new ways of behaving Create a New Culture Hold on to the new ways of behaving and encourage, reward behavior

ConclusionConclusionConclusionConclusion Integrate Site Data Management concepts into projects at the

planning stage which include:

• Site data management process

• Identifying the quality control steps

• Assign responsibilities and hold staff accountable

Software and databases assist in achieving project goals (EQuIS, GIS, others)(EQuIS, GIS, others)

“Proper data management is important to the success of any environmental cleanup project. The value of high-quality data for making informed decisions is critical. Integrating proper data management throughout all phases of a program results in a system highly valued for its completeness and accuracy. Long-Term Groundwater Monitoring – The State of the Art. The Task Committee on the State of the Art in Long-Term Groundwater Monitoring Design of the Environmental and Water Resources Institute. Reston, Virginia: American Society of Engineers, 2003.

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