Full metadata record
DC FieldValueLanguage
dc.contributor.authorDURRANT Tracyen_GB
dc.contributor.authorHIEDERER Rolanden_GB
dc.date.accessioned2010-02-25T16:24:56Z-
dc.date.available2009-04-15en_GB
dc.date.available2010-02-25T16:24:56Z-
dc.date.created2009-03-09en_GB
dc.date.issued2009en_GB
dc.date.submitted2008-12-03en_GB
dc.identifier.citationJOURNAL OF ENVIRONMENTAL MONITORING vol. 11 no. 4 p. 774-781en_GB
dc.identifier.issn1464-0325en_GB
dc.identifier.urihttp://www.rsc.org/Publishing/Journals/EM/article.asp?doi=b818274ben_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC49124-
dc.description.abstractManaging data in the context of environmental monitoring is associated with a number of particular difficulties. These can be broadly split into issues originating from the inherent heterogeneity the parameters sampled, problems related to the long time scale of most monitoring programmes and situations that arise when attempting to maximise cost-effectiveness. The complexity of environmental systems is reflected in the considerable effort and cost required to collect good quality data describing the influencing factors that can improve our understanding of the interrelationships and allow us to draw conclusions about how changes will affect the systems. The resulting information is also frequently elaborate, costly and irreplaceable. Since the quality of the results obtained from analysing the data can only be as good as the data, proper management practices should be considered at all stages of the monitoring activity, if the value of the information is to be properly exploited. Using a QA system can aid considerably in improving the overall quality of database, and good metadata will help in the interpretation of the results. The benefits of implementing QA principals to project management and data validation are demonstrated for the information collected for the long-term monitoring of the effects of air pollution on the forest environment under Forest Focus. However, there are limits in the ability of any computer system to detect erroneous or poor quality data, and the best approach is to minimise errors at the collection phase of the project as far as possible.en_GB
dc.description.sponsorshipJRC.H.7-Land management and natural hazardsen_GB
dc.format.mediumPrinteden_GB
dc.languageENGen_GB
dc.publisherROYAL SOC CHEMISTRYen_GB
dc.relation.ispartofseriesJRC49124en_GB
dc.titleApplying Quality Assurance Procedures to Environmental Monitoring Data: A Case Studyen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1039/b818274ben_GB
JRC Directorate:Sustainable Resources

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.