Biomedical subjects

J C Worthington

Publications and source records attributed to J C Worthington.

3 recordsLinked to original sources

PubMedDate not supplied

Data standards are back seat drivers! Methodology for incorporating information quality into quality assurance project plans.

Quality assurance project plans for environmental data collections consider user requirements for the measurements and express these in the form of data quality objectives. User requirements now may include capture of measurements and associated information in prescribed formats to facilitate entry into computerized information systems. Establishing ahead of time that the data requirements may be an important "back seat driver" for an environmental collection effort can save considerable resources for an organization. Also, the planning may need to accommodate unique requirements associated with the entry of data into data collection systems.

Data Collection↗

PubMedDate not supplied

Two data bases in every garage: information quality systems.

Enterprises, including Federal agencies such as the U.S. Environmental Protection Agency (EPA), are now identifying their information as a strategic resource. As part of a new strategy, enterprises address quality system planning. This technical paper presents some of EPA's approaches and techniques for reconciling quality system considerations for science and technical activities with quality system considerations for information technology and resources. Identification of key information quality indicators, management processes, and assessment processes are addressed.

Environmental Monitoring↗

PubMedDate not supplied

How good are my data?: Information quality assessment methodology.

Quality assurance techniques used in software development and hardware maintenance/reliability help ensure that data in a computerized information management system are maintained well. However, information workers may not know the quality of data resident in their information systems. Knowledge of the quality of information and data in an enterprise provides managers with important facts for managing and improving the processes that impact information quality. This paper presents quality assessment methodology to assist information workers in planning and implementing an effective assessment of their information data and quality. The areas covered include: identifying appropriate information quality indicators; developing assessment procedures; conducting information quality assessments; reporting information assessment results; tracking improvements in information quality.

Computers↗