1 Ecoinformatics April 2008

2 Exercise Turn to the person sitting next to you Decide who will present and who will question Presenter: present the indicator to the person sitting next to you Questioner: ask questions to clarify anything that is unclear Time: 45 seconds

3 Total energy intensity in the EU-25 during , Nb. Energy intensity is a measure of total energy consumption in relation to economic activity

4 Important not to have unrealistic expectations of what indicators can do… Think back to DAS presentation yesterday…

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6 River Thames 2007

7 Oil spill from tanker Prestige off Spanish coast (ESA Envisat satellite)

8 Global NO2 pollution map for 2006 (ESA Envisat)

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10 Outline 1.(Exercise) 2.Knowledge for action 3.Uncertainty

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12 How: Building the scene Polity Take actions Explore responses Create knowledge Framework Signals and facts

13 Why and whom: developing processes, working with the actors Steps Stages Political understanding Scientific analysis Action identification Measure effectiveness

14 Tools When and where: The changing scene before/after, above/below... Past implementation National condition Regional future options Actual evaluation Instruments

15 Managing the scene: Uncertainty and complexity Signals in Actual actions out Quantitative data in Knowledge out Future actions out Knowledge out Qualitative data in Signals in

16 Knowledge for action

17 Evidence based policy: linking uncertainty and action Willingness to act is a political quantity – we cannot really influence it, but we can take advantage of it and play to it…

18 Purpose of uncertainty assessment for indicators Minimise risk of misleading policy makers 1)Uncertainty in datasets: e.g. Inexactness or non- comparability in underlying data from monitoring, collection etc. 2)Uncertainty in methodology: e.g. Systematic errors arising during manipulation of data, use of unreliable or subjective methods for dealing with missing data, lack of scientific /societal robustness or legitimacy in the choices made in the methods or indicators 3)Uncertainty in rationale: e.g. perceptions of the problem, causes and solutions. This includes issues to do with ignorance of other possible explanatory variables or lack of scientific /societal robustness or legitimacy in the choices made in framing of the problem or the assessments.

19 Integral to e- indicator management system: CSI, TERM, EERM, Irena; CCm, ?CCA, AQ, we struggle with: water, soil, biodiversity, waste

20 Some Generic Levels of Evidence….. Beyond all reasonable doubt Reasonable certainty Balance of probabilities/evidence Strong possibility Scientific suspicion of risk Negligible/insignificant That are appropriate for different purposes - language issues!!

21 Indicators

22 Knowledge for action

23 Assessments for action… ….Means understanding the policy cycle

Most information EEA core set of indicators

25 Assessments for knowledge… ….Means understanding the knowledge we have

26 Build a structure or pattern from diverse elements. Put parts together to form a whole, with emphasis on creating a new meaning or structure. X Make judgements about the value of ideas or materials. X Data description.  Separate material or concepts into component parts so that its organizational structure may be understood. Distinguish between facts and inference. X Apply concept - conceptualise problem or issue..  ? Understand the meaning, translation, interpolation and interpretation of the problem. Redefine the problem.  Blooms typology of knowledge

27 Knowledge for action 1 st aim: To further action 2 nd aim: To further understanding of the system- is the policy working? See policy as test of hypothesis of the mechanism… Closing the loop:- create real life experiments! And engage back with science…

28 Assessments Acuity The clarity or clearness To further action

29 …What policy makers need to know vs. what it would be nice if they knew…. What ministers like is Alliteration! E.g. 4Fs What civil servants like… ….“To reduce the political risk of doing the right thing”

30 Future actions Uncertainty w/s for thematics: very practical approach

31 Thank you! Any Questions?