1. GENASIS.EU RECETOX, Masaryk University, Brno, Czech Republic http://www.recetox.cz NORMAN meeting, Berlin 20-21.4.2011

2. Overview • 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

3. Systemarchitectureandfunctions

4. Simplifieddatabase model • Data provider, projects, security … • … 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 QA-methods (e.g. Cd, fluoranthene + e.g. TOC, meteorology) • … measured values (value, unit, LOQ/D, weight) 1. Institution 2. Locality 3. Matrix 4. Sample 5. Parameters 6. Measuredvalue

5. Providers Projects SAMPLES Values Parameters Locality

6. Discussion to NORMAN workshop • Harmonize towards multipurpose use (no isolated single-purpose databases …) • Respect existing activities and recommendations (EU – data close to source, linking datasources …) • 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