Quality assurance and quality control in monitoring programs

Shampine, William J.

doi:10.1007/bf00547492

Cited by 25 publications

(9 citation statements)

References 1 publication

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“…Biological surveys often address longterm and large-scale questions, necessitating a degree of temporal and spatial replication sufficient to represent the heterogeneity of the target population (Legg & Nagy 2006). Finally, the quantity of samples determines the capacity of a data set to reveal environmental patterns and relationships (Shampine 1993).…”

Section: Introductionmentioning

confidence: 99%

Influence of volunteer and project characteristics on data quality of biological surveys

Lewandowski

Specht

2015

Conservation Biology

169

170

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Volunteer involvement in biological surveys is becoming common in conservation and ecology, prompting questions on the quality of data collected in such surveys. In a systematic review of the peer-reviewed literature on the quality of data collected by volunteers, we examined the characteristics of volunteers (e.g., age, prior knowledge) and projects (e.g., systematic vs. opportunistic monitoring schemes) that affect data quality with regards to standardization of sampling, accuracy and precision of data collection, spatial and temporal representation of data, and sample size. Most studies (70%, n = 71) focused on the act of data collection. The majority of assessments of volunteer characteristics (58%, n = 93) examined the effect of prior knowledge and experience on quality of the data collected, often by comparing volunteers with experts or professionals, who were usually assumed to collect higher quality data. However, when both groups' data were compared with the same accuracy standard, professional data were more accurate in only 4 of 7 cases. The few studies that measured precision of volunteer and professional data did not conclusively show that professional data were less variable than volunteer data. To improve data quality, studies recommended changes to survey protocols, volunteer training, statistical analyses, and project structure (e.g., volunteer recruitment and retention).

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Section: Introductionmentioning

confidence: 99%

Influence of volunteer and project characteristics on data quality of biological surveys

Lewandowski

Specht

2015

Conservation Biology

169

170

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“…At the same time, considerable concern exists in the scientific community about the ability of monitoring programmes to provide the desired information (Legg and Nagy, 2006;Vos et al, 2000). The main reason for this is the poor confidence about the quality of the data, with most typical questions concerning the statistical basis of sampling design, the reliability and comparability of data, and data management (Elzinga et al, 2001;Ferretti, 2009;Legg and Nagy, 2006;Shampine, 1993;Vos et al, 2000;Wagner, 1995). This concern is justified especially for terrestrial monitoring with a large-scale coverage and a long-term nature, such as the international monitoring programmes.…”

Section: The Need For Quality Assurancementioning

confidence: 99%

“…While this kind of problem may always occur with terrestrial monitoring over large areas (remote sensing techniques may be less influenced), they are exacerbated in international programmes when a joint effort of experienced institutions over several countries is necessary. On the other hand, the time "impacts how the work is viewed by the people collecting data, as well as the people who ultimately will use the data" (Shampine, 1993). In addition, change in personnel (in particular under the current labour market conditions) and change in methods (due to conceptual and technical improvement of methods, techniques and instruments) may lead to comparability problems at times of personnel/method changes.…”

Section: The Need For Quality Assurancementioning

confidence: 99%

Quality assurance (QA) in international forest monitoring programmes: activity, problems and perspectives from East Asia and Europe

Ferretti

König

Rautio³

et al. 2009

Ann. For. Sci.

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Abstract• The quality of monitoring is defined by its ability to provide data that (i) allow estimates of the status of the target resource with defined precision level, (ii) permit change detection with defined power, and (iii) are comparable through space and time. To achieve these requirements a Quality Assurance (QA) perspective is essential.• To what extent QA was considered and data quality achieved in international forest monitoring programmes in East Asia and Europe? What is missing?• Past and present QA activity in forest monitoring in East Asia and Europe revealed that most attention was given to evaluate and promote comparability of measurements, with special emphasis on analytical chemistry. Much less attention was given to field sampling and to the overall monitoring design. QA approaches were unbalanced among the various investigations, and several problems with data comparability remained over years.• Despite considerable work on data quality control, parts of the monitoring process are still poorly covered by QA and revealed weaknesses in design and implementation. More comprehensive, formal and stringent QA procedures are necessary in international monitoring initiatives. Steps currently being undertaken for a more comprehensive QA approach are presented. Mots-clés :Asie de l'Est / Europe / surveillance des forêts / assurance qualité Résumé -L'assurance qualité (AQ) dans les programmes de surveillance des forêts : activités, problèmes et perspectives pour l'Asie de l'Est et l'Europe.• La qualité de la surveillance est définie par sa capacité à fournir des données qui (i) permettent des estimations de l'état de la ressource cible, définie à un niveau de précision, (ii) permettent la détection des changements de puissance définie et (iii) sont comparables à travers l'espace et le temps. Pour satisfaire à ces exigences d'assurance qualité (QA) la perspective est essentielle.• Dans quelle mesure l'assurance qualité a été examinée de même que la qualité des données obtenues dans les programmes internationaux de surveillance des forêts en Asie de l'Est et l'Europe ? Qu'est-ce qui manque ?• L'activité passée et présente dans l'assurance qualité de surveillance des forêts en Asie de l'Est et Europe a révélé que la plus grande attention a consisté à évaluer et promouvoir la comparabilité des mesures, avec un accent particulier sur la chimie analytique. Beaucoup moins d'attention a été accordée à l'échantillonnage sur le terrain et au modèle de surveillance globale. Les approches de QA ont été déséquilibrées entre les différentes enquêtes, et plusieurs problèmes avec la comparabilité des données sont restés au fil des années.• Malgré un travail considérable sur la qualité des données de contrôle, des parties du processus de suivi sont encore mal couvertes par l'assurance qualité et des lacunes de conception et de mise en oeuvre ont été révélées. Des procédures d'assurance qualité plus complètes, structurées et rigoureuses sont nécessaires dans les initiatives internationales de surveillance. Les étapes ac...

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“…Quality assurance (QA) protocols for all aspects of environmental studies including design, plan, preparation, sample collection, field liaison communication and records, sample handling, laboratory analysis, data transmission, data validation, data approval, data distribution, statistical analysis, and reporting. A QA plan should enable the quantification of data quality (precision and accuracy), consistency and comparability of data over time even through sampling and analysis techniques change, and accessibility of data (Shampine, 1993). Concepts of quality assurance as related to the precision of estimating microbiological counts should be incorporated in the data interpretations and include variation between replicates, within samples, between operators, and between laboratories (Havelaar et al, 1993).…”

Section: Nps Modeling and Monitoringmentioning

confidence: 99%