Hierarchy of categories and indicators top-down approach

I have attempted to identify a set of performance macro-indicators from a literature review, either in how they illustrate road safety level and development in a country or how they offer a significant affect on accident rates. The quantitative relationship between the indicators and risk was discussed in the previous section. The indicators should be selected on the basis of the discussed criteria for selecting macro-performance indicators. Special attention has to be paid to indicators covered by data, which is already available. The chosen categories and indicators will not provide a complete picture of road safety issues in a country, rather they will give summary information on the national performance in the country, which can help in comparing its progress and experience with other countries. 

The full summary list of the possible macro-indicators in each category is shown in Table 3.2. The indicators have been classified into three classes according to their data availability, quality and type. When dealing with data availability, as with quality, it is necessary to have clear description of what is meant by data quality or data availability . For instance, one acceptable indicator is fatalities per vehicle kilometre and it is an important element in road safety, but this measure is still not available in most developing countries. On the other hand, the indicator percentage of motorways per road network has poor quality of data and there is difference of definitions of road standards across countries. In fact, there are several indicators that may play an essential role in the development of RSDI, but unfortunately these indicators are hard to measure for now and they will be kept for further and future development. 

A high avaUabihty of data means that enough data is available to access at all times. Medium means that data is under development (work in progress) and there is a call for data collection in these indicators. A low rating means that data is currently not available and they require further development and collection of data in the future for a large number of countries, especially from developing countries. 

A high quality of data means that data comes from reliable sources without errors and the results are accurate. Acceptable data means that it is fairly reliable and accurate. Poor quality means that we have a data quality problem and the results are questionable and should not be fiilly trusted. Not rated means indicators are not identified for now and there is no indication what the quality could be in future. 

The increase in availability of data will improve the quality of data. In other words, the quality of indicators is good when data is available. I attempted to estimate the size of quality and availability of the indicators as be given in (Table 3.2), although it is often hard to estimate that. However, any such future attempt would require especial techniques (done directly with computer) used to assess the availability and quality of data in different countries worldwide. The selection of the key macro-indicators is not final. The indicators will continue to be developed and refined. Further, efforts will be made to enable high quality data delivery. 

---