12. Executive summary

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MIDAS - An example of an environmental data strategy

12. Executive summary

This chapter provides a quick overview of main points from the whole report. The figures in the left column refer to chapters, pages and figures in the report where the relevant information is elaborated and explained in more detail.

Chapter1,p.1 Chapter2,p.5	What is MIDAS ? The name 'MIDAS' is used by the Danish EPA as an acronym for its environmental data strategy. This strategy was initiated in 1991 and is now under continual implementation. A data strategy in the MIDAS concept of the word requires a problem analysis; an analysis of valuable experience made elsewhere; the set-up of a range of objectives; a tool-box with a set of tools for achieving these objectives; and a strategy combining the tools and the objectives in an action plan.
	Objectives of the report.
Chapter1,p.1	The present report is part of a package of project launched by the Danish Ministry of Environment and Energy for the support of the European Environment Agency (EEA). The main objective is to transfer knowledge and experience of the MIDAS project to the EEA. The idea is not the adoption of the MIDAS strategy by the EEA, but to enable the EEA to use the MIDAS project as an inspiration in its data strategic work.
	The starting point. The starting point of the MIDAS project was a problem analysis - an attempt to pinpoint not just the immediate problems, but the reasons behind them. Five major problem areas were identified:
Chapter3,p.10f	Problems related to internal organisation of data work in the Danish EPA - there was decentralisation without co-ordination where it should be co-ordinated decentralisation Problems in relation to the co-operation with other bodies outside the EPA mainly in the collection of environmental data There was not enough demand for data and focus on data from the top level of the organisation and from the outside world There was a lack of practical training - not in the use of specific software tools but in the general production and use of environmental data Resources for environmental data work were scarce.
Figure 3.1, chapter3,p.9	In establishing objectives, tool-box and strategy focus was on four aspects of environmental data work: organisation, data content, human resources and database aspects.
Chapter4	The tool-box. After describing the background and problem analysis of the original MIDAS report, the present report looks into the tool-box of the MIDAS project. Some of the most important tools are presented in more detail, among them: The conceptual framework - which is a tool for defining the main categories of data relevant when describing and analysing any field of environmental work. The objective is to ensure that the available data are comprehensive. The conceptual framework can be put into a form and in this way work as a kind of checklist (see table below). Data on environmental problems are of course relevant, and sectors in society are important, as they are the target groups for most environmental policy. Other important aspects are data on the state of the environment; data on regulation; and data on environmental economy.

State of the Environment Env. Problem Sources of pollution Regulation

State Pressure Location and extent Structural/ behavioural aspects Contribution to environmental problem Objec-tives Measures to be taken Time limits/ expenditure

Chapter5	Thematic analyses - which is a way of dealing with a large subject area by dividing it into smaller bits. In the original MIDAS report it was not possible to go into any detail with the problems and data needs related to the many different areas of work of the Danish EPA. Therefore it was decided to go through the different areas one by one with the double aim of pinpointing problems and providing strategies for improvement. A set of rules for this work was defined, and the conceptual framework was used for the definition of data gaps and data needs.
Chapter6	Organisation of data - another idea of the original MIDAS report was to have data in different levels to make it easier to combine data and use them in more than one context. This involved a hierarchy of data according to their level of detail and to the way they were to be presented. The levels were expert data (the most detailed level); thematic data combining data from the different expert databases that were relevant to the theme in question (presented in a GIS-system); and keydata. This was completed by the idea of having a computer based catalogue of data to supply overview and the idea of having a database of common data (data used in more than one database).
Chapter7	The key data system - the idea of the key data system was to have a tool for structuring, combining and presenting environmental data at the highest level of aggregation to decision makers. The system was supposed to combine graphic presentations and map-based presentations, and a special tool was later developed for this purpose. In the actual implementation process the distinction between key data, thematic data and expert data was dissolved so that the key data system ended up including data down to a fairly high level of detail.
Chapter4,p.14 ff.	Some of the other tools recommended in the original MIDAS strategy are: Guidelines and procedures for environmental data projects; clear definitions of responsibilities related to data work; standard agreement with data suppliers; specialised training courses; strengthening of the data co-ordinating group in the Danish Ministry of Environment and Energy.
Chapter8	The implementation of the MIDAS strategy. In the implementation process pilot projects and proto-typing were important methods. At the overall level, the whole MIDAS strategy was subject to an evaluation and reformulating after a period of a year. This was done to make sure that the strategy was up-dated and experience made useful.
Chapter9	Using experience from other countries and agencies. To broaden the perspective of the report a little, experience from the United States is discussed. Main points are summed up in table 9.1.
Preconditions etc. are summed up in table 9.2,p.53	An important point when discussing experience is the preconditions for initiating data strategic projects and carrying them out. Important is also the discussion of counter-productive conditions. When starting and implementing data strategies it is vital to be aware of these conditions and to try to neutralise them.
Chapter10	Conclusions and recommendations. Another way of summing up your experience is by discussing what you would change in your approach if you had the chance. In the MIDAS context, more focus would have been put on visibility and user-oriented intermediary products to ensure continuous involvement by the whole organisation. Also more focus would be put on the range of software tools available and on aspects concerning the outside world, e.g. making data available to the public. When your data work is very closely tied to the production of specific reports there is a span of approaches to collection, storage and retrieval of data ranging from an ad-hoc-model approach to a global data model approach.
Chapter11	When you are going to decide whether data strategic work is relevant for your organisation, there are some questions that can be used as guidelines, e.g. are all the necessary data available to the organisation ? Are data easily accessible to all users ? Is the out-put of the data work of the organisation satisfactory ? Is the organisation of data work adequate, i.e. are there no organisational barriers to data work ? If the answer to one or more of these questions is 'no', it is worthwhile to take a closer look at the data work of the organisation.
The MIDAS method is summarised in the table at the very end of chapter11. A suggestion for a method for initiating a more ad-hoc set of projects is presented at the very end of chapter 11.	If a need for data strategic work is recognised there are basically two ways of doing it: the MIDAS method, comprising a comprehensive data strategy, or a more ad-hoc way. Basically it is a question of resources and time that decides which approach is most adequate. In the report it is recommended that the EEA considers its need for data strategic work. If it is agreed that there is such a need the EEA could either define a project that will lead to an environmental data strategy or define a range of individual projects based on a quick assessment of problem areas. These projects should all be able to contribute to data strategic objectives. The range of projects would of course depend on the resources that the organisation is willing to use, but at least these aspects should be taken into consideration: presentation of data for management (and general public) purposes in an integrated system common standards, guidelines and procedures for data work, including a common view of the world (cf. the ongoing thesaurus work) and a model for all data related to the work of the EEA organisational aspects including strengthening of co-ordinating procedures
	Other recommendations concern: development of a system for structuring and presenting key data. allocation of the necessary resources and human resource development. co-ordination within the EIONET - apart from formalised co-ordinating bodies e.g. common guidelines and formats can be used as mechanisms for co-ordination. organisation and especially division of responsibilities and the role of the EEA itself in relation to overall guidelines etc. a common view of the world for data to unify the data work in the very large organisational set-up that surrounds the agency.