Data collection design approach

To facilitate systematic planning, EPA developed the DQO process, a seven-step planning approach for data collection designs, which enables us to collect relevant and valid data for project decision-making. 

In Step 7, the planning team evaluates the data collection design alternatives and selects the most cost-effective approach that most closely meets the DQOs. Budget... 

A stepwise approach to DQA identifies different tasks that may be performed by individuals with different expertise. For example, a less experienced chemist may verify the data package content (Step 2), whereas a more experienced chemist may perform data evaluation (Step 3). For a statistical data collection design, a statistician may be involved in the assessment of data relevancy (Step 6). A database manager may be involved at several steps if the EDDs are part of laboratory deliverables and if completeness is calculated. 

The traditional approach, because it sees the major causes of errors and accidents as being attributable to individual factors, does not encourage a consideration of the underlying causes or mechanisms of error. Thus, accident data-collection systems focus on the characteristics of the individual who has the accident rather than other potential contributory system causes such as inadequate procedures, inadequate task design, and communication failures. 

Contextual design is a flexible software design approach that collects multiple customer-centered techniques into an integrated design process [7]. The approach is centered around contextual inquiry sessions in which detailed information is gathered about the way individual people work and use systems and the associated information flow. The data from each contextual inquiry session are used to create sequence models that map the exact workflow in a session along with any information breakdowns, flow models that detail the flow of information between parties and systems (much akin to but less formal... 

This paper describes a package of computer programs that we have written to provide menu-driven operation of our facility for x-ray orientation studies. This paper describes the overall structure of the package in the hope that our design approach will be useful to future designers of laboratory data collection systems. Persons who are interested in implementing similar systems can obtain copies of the software described herein from the authors. 

In the next section of this chapter, we will review a variety of instrumentation approaches to the FLIM experiment. In particular, we describe conventional systems as well as those designed to observe variation in a, and systems designed for the collection of multifrequency data. In this context, we will also look at data collection strategies and the subsequent first pass analysis of the acquired... 

This paper outlines a novel approach to maximising the value of kinetic data by combining mineralogy, aqueous geochemistry and kinetic test data to design ground and surface water exploration programs. The approach is tested on environmental data collected by Adanac Molybdenum Corporation at the Ruby Creek Molybdenum project, Atlin, BC, Canada. 

It is important to point out that there is often considerable discussion about the merits of rational approaches where systems are designed, synthesized, and then studied relative to what is sometimes described as the random approach taken with combinatorial chemistry. It is important to view parallel approaches not as a replacement for rational science but as a tool that allows for faster data collection. This data can then be used for the design of better catalysts. 

The previous chapter discussed the (currently) relatively loosely defined statistical approaches to safety data collected in clinical trials. In contrast, there are widely accepted statistical methods for demonstrating efficacy in clinical trials. As has been noted several times in this book, if the study design and methodology have been appropriate and have led to the collection of optimum quality data, the statistical analysis and interpretation of efficacy data are relatively straightforward. The clinical (biological) interpretation of efficacy data is typically not quite as clear-cut, but there are widely accepted methodologies that are very useful in this realm too. Of particular importance here is the expert judgment of the clinicians who will review the statistical results with the statisticians and the rest of the study team. 

The process of characterization of impurities described in this chapter uses a designed approach for the isolation of unknown impurities and degradants in pharmaceutical drug substances. This approach focuses on efficiency, so that the success of data collection is maximized. The isolation of pure material is crucial when trying to identify the structure of an unknown impurity/degradant. Once the unknown has been isolated, it can be submitted for structure elucidation using mass spectrometry and NMR spectroscopy. 

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