Part #2 of 3. WISE SoE data flows River water quality Lake water quality Groundwater quality Water quantity * Emissions to water * + biology.

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Presentation transcript:

Part #2 of 3

WISE SoE data flows River water quality Lake water quality Groundwater quality Water quantity * Emissions to water * + biology

Plan Adjust Iterate no WISE SoE data flows in ?

WISE SoE review and upgrade towards WISE 2.0 Content Review of the WISE SoE data flows against upcoming WFD reporting in 2016 Technical Review of QA/QC of data flows to develop more efficient processes between EEA and Member Countries, including feedback mechanisms

Why ? Plan Execute Adjust Evaluate Iterate

Timeliness & completeness

WISE SoE data flows 1.7  1.8 here in 2012there in 2013

River water quality 1.7  2.1 Delays… No Biology data No Hazardous Substances data

Lakes water quality 1.8  2.1 No reply to critical QC issues...

Groundwater quality 2.4  2.1 No delivery...

Water quantity * 1.1  1.2 Only EUROSTAT/OECD JQ 2012 Incomplete spatial coverage Issues with spatial units / aggregation Issues with temporal aggregation

from ground truth to Waterbases… Setup collectionRun collectionFinalise collectionProcess + AnalyseDisseminate publication

Emissions to water * 1.5  1.3 Only point emissions Only E-PRTR

E-PRTR 2.7 Smaller set of countries

from ground truth to Waterbases… End of E-PRTR Setup collectionRun collectionFinalise collectionProcess + AnalyseDisseminate End reporting Last delivery Publication

On average… Setup collectionRun collectionFinalise collectionProcess + AnalyseDisseminate + 5 weeks

On target ? Setup collectionRun collectionFinalise collectionProcess + AnalyseDisseminate

Adjust Iterate How ?

Design Principles 1.Start with needs 2.Do less 3.Design with data 4.Do the hard work to make it simple 5.Build digital services, not websites 6.Iterate. Then iterate again. 7.Don't do everything yourself (you can't) 8.Build a network of trust 0. Adapted from:

Prioritise Must Must describes a requirement that must be satisfied in the final solution for the solution to be considered a success. Should Should represents a high-priority item that should be included if possible. This is often a critical requirement but one which can be satisfied in other ways if strictly necessary. Could Could describes a requirement which is considered desirable but not necessary. This will be included if time and resources permit. Won’t Won’t represents a requirement that stakeholders have agreed will not be implemented in a given release, but may be considered for the future. MoSCoW analysis MoSCoW analysis [BABoK 2009:192]

Prioritise data collection Must have… Data needed for core indicators, planned assessments, existing and planned data products. Data needed as input to other reporting obligations (e.g. WFD, the Eurostat/OECD Joint Questionnaire)… Should have… Data to improve the thematic | spatial | temporal coverage and resolution of data obtained through other data flows (e.g. EU directives reporting). Could have… Won’t Input data not directly traceable to an existing or planned data product or need. Or redundant data in different data flows… …same as before, if and only if it doesn’t prevent us from collecting the data we really need. i.e. reduce reporting burden

An example with WFD reporting Must ! Section 9.2 and 9.3 introduce the possible use of WISE SoE information for emissions and water abstraction to replace WFD requirements when the data is reported under WISE SoE

An example with emissions… ? Should ? ? Could ? ? Must ?

Prioritise data processing Must do… Upon delivery, process the available data for the update of indicators, Waterbases, map services and interactive data and map viewers. Also applies data consumed by other entities (e.g. Eurostat, ENV). Should do… Could Won’t Do not process data with severe Quality Issues that where flagged upon delivery by the automated QC routines … … but provide “human” interaction and feedback to improve the data deliveries. As soon as required, process data for planned assessments (which typically needs to be tailored or post-processed). As soon as possible, process ad-hoc data requests. But, preferably, make all data available for download. And/or through well-documented APIs.

Waterbases Groundwater Water Quantity Emissions Rivers + biology Lakes + biology BWD DWD UWWTD WFD Floods

Standardise, document and reuse: Concepts and vocabularies Data models Code lists Spatial units Processes Formats Services Waterbases Groundwater Water Quantity Emissions Rivers + biology Lakes + biology BWD DWD UWWTD WFD Floods

Small steps towards services… time WFDWFD alignment… WISE SoE 2020 …compliance

Monitoring stations Nutrients Hazardous substances Biology Pressures Characterisation of the spatial unit RiversLakesGW Emissions INSPIRE Environmental Monitoring Facilities ISO 19156:2011 Observations and Measurements

Questions?Feedback?

Part #3 of 3 Fernanda Nery

2.0

HP DevOps Maturity Model

Build digital services, not websites 5.

time 2020

Build digital services, not websites Our service doesn’t begin and end at our website. We need to design for that, even if we can’t control it. And we need to recognise that some day, before we know it, it’ll be about different digital services again. 5.

Questions?Feedback?