The Data User’s Guide to Producing Legally Defensible Environmental Data
Data Quality, Management and Review
Oral Presentation
Prepared by C. Hiegel
Trihydro Corporation, 1252 Commerce Dr., Laramie, WY, 82072, United States
Contact Information: [email protected]; 307-745-7474
ABSTRACT
C. Hiegel
Trihydro Corporation, 1252 Commerce Drive, Laramie, WY 82070
Contact Information: [email protected]
ABSTRACT
Key Words: Data Validation, Data Defensibility, Data Quality, Environmental Data, Legally Defensible Data
Planning for defensible data that may be used in litigation is generally not the first component of a project that we consider for a project sampling or data collection event. However, when the data are in error, data defensibility becomes the most important aspect of the project as the opposing counsel works to discredit the data. Data quality/defensibility, like safety, should not be left to luck.
Devoting significant time to plan and prepare for a complex project can be daunting and when regulatory requirements do not require specific planning documents, determining what is really important can be difficult. In addition, each project, state, and client has different defensible data planning requirements. Budget considerations do not always allow for development of Sampling and Analysis Plans (SAPs), Quality Assurance Project Plans (QAPPs), Data Management Plans (DMPs), Standard Operating Procedures (SOPs), and other plans. The following steps will be discussed in determining what is important when producing defensible data:
DEFINE DEFENSIBILITY: The first step in planning for legally defensible data is determining how the project success will be defined.
PLANNING: Once the project goals are defined, the second step is to choose the tools (planning documents, equipment, personnel, etc…) the project will need to be successful.
PREPARATION: When planning is complete, preparations of the tools that will be used to measure the defensibility are initiated. The most important aspect of planning will be effectively communicating project success requirements to the laboratory, managers, and sample crew.
EXECUTE: Project execution should result in the samples being collected in accordance with the planning documents; chain-of-custody should be properly maintained; and the laboratory should analyze the samples in accordance with the methods.
REVIEW: The review process ensures that the project planning and execution was effective.
MANAGE: Finally, once the data are reviewed and approved or rejected, the data should be maintained with any data validation qualifiers, laboratory data qualifiers, and notes.
The concern of environmental risk factors affecting human and ecological receptors, the quality of the procedures involved in the defining, planning, preparation, execution, review, and management of data is under heavier scrutiny than ever before. Therefore, the goal of this user’s guide is to provide guidance in understanding what critical steps are necessary to produce defensible data, improve the quality of the data results, and assist data users in defending their data in court.
Data Quality, Management and Review
Oral Presentation
Prepared by C. Hiegel
Trihydro Corporation, 1252 Commerce Dr., Laramie, WY, 82072, United States
Contact Information: [email protected]; 307-745-7474
ABSTRACT
C. Hiegel
Trihydro Corporation, 1252 Commerce Drive, Laramie, WY 82070
Contact Information: [email protected]
ABSTRACT
Key Words: Data Validation, Data Defensibility, Data Quality, Environmental Data, Legally Defensible Data
Planning for defensible data that may be used in litigation is generally not the first component of a project that we consider for a project sampling or data collection event. However, when the data are in error, data defensibility becomes the most important aspect of the project as the opposing counsel works to discredit the data. Data quality/defensibility, like safety, should not be left to luck.
Devoting significant time to plan and prepare for a complex project can be daunting and when regulatory requirements do not require specific planning documents, determining what is really important can be difficult. In addition, each project, state, and client has different defensible data planning requirements. Budget considerations do not always allow for development of Sampling and Analysis Plans (SAPs), Quality Assurance Project Plans (QAPPs), Data Management Plans (DMPs), Standard Operating Procedures (SOPs), and other plans. The following steps will be discussed in determining what is important when producing defensible data:
DEFINE DEFENSIBILITY: The first step in planning for legally defensible data is determining how the project success will be defined.
PLANNING: Once the project goals are defined, the second step is to choose the tools (planning documents, equipment, personnel, etc…) the project will need to be successful.
PREPARATION: When planning is complete, preparations of the tools that will be used to measure the defensibility are initiated. The most important aspect of planning will be effectively communicating project success requirements to the laboratory, managers, and sample crew.
EXECUTE: Project execution should result in the samples being collected in accordance with the planning documents; chain-of-custody should be properly maintained; and the laboratory should analyze the samples in accordance with the methods.
REVIEW: The review process ensures that the project planning and execution was effective.
MANAGE: Finally, once the data are reviewed and approved or rejected, the data should be maintained with any data validation qualifiers, laboratory data qualifiers, and notes.
The concern of environmental risk factors affecting human and ecological receptors, the quality of the procedures involved in the defining, planning, preparation, execution, review, and management of data is under heavier scrutiny than ever before. Therefore, the goal of this user’s guide is to provide guidance in understanding what critical steps are necessary to produce defensible data, improve the quality of the data results, and assist data users in defending their data in court.
