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Version 0.9 2004-11-10. * * * Quality assurance of Eurowaternet data Presentation for the EIONET Water Workshop Budapest, 11-12 November 2004. EIONET European Environment Information and Observation Network http://www.eionet.eu.int/. Hermann Peifer, Project Manager EIONET Data Flow
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Version 0.9 2004-11-10 * * * Quality assurance of Eurowaternet data Presentation for the EIONET Water WorkshopBudapest, 11-12 November 2004 EIONETEuropean Environment Information and Observation Networkhttp://www.eionet.eu.int/ Hermann Peifer, Project Manager EIONET Data Flow <hermann.peifer@eea.eu.int>
Quality: Models, concepts and frameworks Concerning quality in a broader sense: ISO 9000: A family of International Standards for quality management http://www.iso.ch/ TQM: Total Quality Managementsearch on google.com: 472.000 hitssearch on amazon.com: 5.485 books EFQM: Excellence Model of the European Foundation for Quality Management http://www.efqm.org The word quality might have been overused in the past years. A too generic definition bears the risk of loosing focus.
Data quality frameworks Concerning data quality in the in sensu strictu: • ESS: Quality Declaration of the European Statistical System:http://amrads.jrc.it/WPs%20pages/Quality/Documents/LEGsummary.pdf • IMF: Data Quality Reference Site of the International Monetary Fund (IMF) http://dsbb.imf.org/Applications/web/dqrs/dqrshome/ • MIT: Total Data Quality Management Program (TDQM) http://web.mit.edu/tdqm/www/index.shtml/ • FAO‘s approach to data quality evaluation and monitoringhttp://www.fao.org/faostat/quality_en.asp • OECD initiative on environmental data qualityhttp://www.oecd.org/
What is data quality? Data quality is a measure of the degree of usefulness of the data for a specific purpose. Data quality indicators are qualitative or quantitative descriptors of data quality.
Data quality management in EIONET:Too little, too late? Data quality management is happening in EIONET. Much of the QA/QC work is carried out by Topic Centres. The level of available QA/QC documentation is improving. There is a clearly a lack of visibility for this area of work. An overarching framework for EEA/EIONET is missing. Annual Management Plan 2005 1.4.2 Maintaining and quality assuring priority data flows“To provide an overview of the quality of the data provided by the member countries by documenting QA/QC processes countryby country, in order to improve the overall quality of data.”
EEA/EIONET data and information flow Presentation Dissemination Data collection Reportnet EEA/EIONET EEA/Users Flow Tools to serveEEA, MS, others Assessmentprocesses Information processes Aggregation Assessment
Data quality: Where it matters most Reports NFP ETC ETC EEA ReportnetData collection EEA/EIONETData processing EEA/UsersData dissemination NRC NRC NRC NRC Q1 Q2
Data quality dimensions Representativeness Accuracy Punctuality
Which dimension is most important? Many say: Relevance Another popular choice:Timeliness The classical one:Accuracy A smart answer is:All My personal preference:... Comparability Accessibility Accuracy Completeness Timeliness Relevance
Guiding thoughts on measuring data quality You can not measure what is not defined. You can not improve what can't be measured. Focus on understandable data quality dimensions. Easy to measure, preferably via simple automated analysis. Providing the right level of information to data providers (Q1) and end-users (Q2) The aim: simple, regular, quantitative and user-oriented data quality reporting
The aim: regular data quality reporting Eurowaternet-Rivers Data Quality for Country X 1995 2000 2005 Punctuality Completeness Timeliness 0 Accuracy Representativeness Comparability
EIONETPriority Data Flows:Annual Progress Reports 1999-2003 Annual monitoring of data deliveries and benchmarking of countries covering: • Relevance • Punctuality • Timeliness • Completeness
Scoring criteriafor Eurowaternet data collection 2005 Response to data quality questionnaire
Data quality in EIONET: Summary Data quality in EIONET needs: More documentation Continuous improvement More visibility Topic-specific QA/QC procedureshave to be embedded into a data quality management framework. The overall aim is (preferably) quantitative data quality reporting which is regularly updated in order to show trends over time. EIONET data quality reporting (mainly targeted at data providers, i.e. Countries) has to be complemented by data quality information targeted at end-users of the data. EEA Data Quality Framework QA/QCEurowater net