Nature and purpose of the SEO classification
1. The SEO Classification allows R&D data to be classified according to the researcher's perceived purpose. The purpose categories take account of processes, products, health, education and other social and environmental aspects of particular interest.
2. A purpose classification such as the SEO provides a set of categories which collectively exhaust all the objectives of research. In this respect, the scope of the SEO is more extensive than a classification of economic activities such as the Australian and New Zealand Standard Industrial Classification (ANZSIC), because not all R&D has an economic motive or context.
Structure of the SEO classification
3. The SEO Classification is arranged in a hierarchical structure. It has 5 divisions, 18 subdivisions, 107 groups and 594 classes.
5. Subdivisions, groups and classes are all assigned six-digit codes. Subdivisions are uniquely identified by the first two digits and the remainder of the code is zero filled. Groups are uniquely identified by the first four digits and the remainder of the code is zero filled. Classes have unique six-digit codes.
6. There are ninety-nine possible categories at the subdivision, group and class levels to allow for future expansion of the classification. The divisions are not reflected in the code system at the subdivision or finer levels.
4. The divisions and subdivisions are:
Guidelines for classifying R&D by SEO
7. The following general procedures are aimed to ensure consistent and successful classification of R&D data.
8. A Research Project is to be allocated to a class in a hierarchical manner. This is achieved by first determining the SEO division in which the research is being performed, then the most relevant subdivision within that division, then the most relevant group within that subdivision, and finally by selecting the relevant class within a chosen group.
9. It is vital to firstly identify the higher level classifications for the Research Project as some classes, although within different groups, have identical class titles.
10. In general, a Research Project is to be classified to one class only. There are cases however where a large Research Project is directed towards more than one socio-economic objective. In such cases, the aim should be to allocate R&D resources on a proportional basis.
11. Where a defined class cannot be identified within a group for a Research Project, the 'Other' or 'n.e.c.' category at the class level is to be used.
Relationship between the SEO classification and the ANZSIC
12. In studying industry performance, it is possible to compare trends in industry with the levels of R&D directed towards particular industries. ABS statistics have been compiled according to the Australian and New Zealand Standard Industrial Classification (ANZSIC).
14. The ANZSIC is a classification of industries. Business units reporting data to a range of ABS censuses and surveys are classified to the ANZSIC on the basis of their predominant economic activity (e.g. what they do to generate income). Normally income is generated through the sale of goods and services produced by the business or bought in from other businesses. An industry as represented in ABS statistics is made up of businesses which are classified to it in accordance with the ANZSIC.
15. When comparing R&D data classified by the SEO with industrial statistics based on the ANZSIC, there are some important considerations to be noted:
13. A broad comparison with the ANZSIC categories is shown below.
- Classifying to an SEO category is subjective, i.e. the category is chosen by the data provider to indicate the main purpose of R&D. Classifying a business to an industry is generally derived objectively through information about its main income generating activity.
- SEO categories do not always correspond with ANZSIC categories on a one to one basis and do not also necessarily correspond with identifiable target industries. For example where the environment is the main potential beneficiary of the R&D, there is no set of business units equivalent and therefore no ANZSIC class is applicable.
- Some SEO categories are too broad and cannot be correlated to ANZSIC industries. For example, R&D towards improving road safety has potential benefits to a wide range of industries, community services and individuals. There would be some effect on businesses within the transport industry, but this may be incidental to attempts at generally reducing the burden on emergency services, medical services, insurance services, disability services, police services, legal services, etc.
- The nature of R&D is such that there may be no observable effect on ABS industry level statistics, or at least the effect may be difficult to assess. The positive effects of R&D may be concealed at the aggregate industry level because of variation, for a variety of reasons, in data from establishments in the same industry. Additionally, in particular instances, R&D may not lead to initiatives which proceed beyond the test environment.