GENASIS EU RECETOX Masaryk University Brno Czech Republic

GENASIS. EU RECETOX, Masaryk University, Brno, Czech Republic http: //www. recetox. cz NORMAN meeting, Berlin 20 -21. 4. 2011

Overview 1) Functions: Database + Visualization + Analytical tools + Data sharing 2) Structure: Modular, flexible, expandable - all matrices including biota, human (2010 – air, 2011 – soils) - any analyte / bioassay-endpoint / additional parameters (flow, meteorology …) - own data + data from partners - primary as well as aggregated data (per year, per country …) 3) Clients-users: - data providers (analyses, visualisation, link to other data) - stakeholders (Ministries – Envi, Agri + Regional/Local authorities) - scientists (? Trends, ? Relationships … datamining) - public (easy access, visualization) 4) Current status and visions – included in the National Integrated Information System on the Environment – link to health (e. g. svod. cz) and bioindication (arrow. cz) systems – integrating Czech environmental system

System architecture and functions

Simplified database model Data provider, projects, security … 1. Institution 2. Locality 3. Matrix 4. Sample 5. Parameters 6. Measured value … measuring at various sites (GIS data) (or agregated – e. g. „Germany“) … various matrices (fractions, tissues…) … samples are collected (time, type …) QA – sampling methods, integrated, changing status (e. g. grassland vs. field) -Dictionary of parameters and QAmethods (e. g. Cd, fluoranthene + e. g. TOC, meteorology) … measured values (value, unit, LOQ/D, weight)

Providers Projects SAMPLES Values Parameters Locality

Discussion to NORMAN workshop 1) Harmonize towards multipurpose use (no isolated single-purpose databases …) 2) Respect existing activities and recommendations (EU – data close to source, linking datasources …) 3) Approach 1: future data - establish minimum data record (harmonized template) - plan and discuss with data providers 4) Aproach 2: retrospective data collection - use whatever data are available - current NORMAN approach is good … but needs a lot of manual manpower 5) Store also „poor-quality“ data (… not necessarily use them for your purpose) (e. g. bioassays: all results of poor quality ? improve ? do not use ? ) (? ) project (EU FP, DG …) – retrospective + prospective approaches future