Categories of data reusers

CLASSIFICATION OF OPEN DATA REUSERS

If the data published has to make any impact, it turns compulsory that someone would use the released data again. It leads us to the next question. Who are the reusers and how to classify them. Due to the lack of former classifications here you can find a grouping of reusers. So, it would allow to make comparisons between different data sources.

Reusers’ classification

The term reuser is ambiguous and it is clear that it could be very different needs and goals for the different groups of people and entities interested on the data released.

esquema-de-reutilizadores-englishv2

In the Table 1 it is summarised the types of data reusers

Table 1: Reusers classification

Name

Definition

DIRECT REUSERS

1

Citizens

End users. Individuals, no exploitation beyond the personal use

2

Professional reusers

Organisations for profit. Create added value services or improve existing ones with the data source. i.e. supplier of public tenders lists

3

Social reusers

Organisations not for profit. Study data and it could provide services to some collectives in the society. i.e. NGO

4

Academic reusers

Individual or organisations. Use the data for academic purposes

5

Publisher reusers

Reusers belonging the publisher of the information. i.e. users of the very public entity publishing data. i.e. national data used by civil servants belonging the national government organisation.

6

Other public reusers

Reusers belonging to different public organisations. i.e. reusers belonging to municipalities reusing data from national government.

INDIRECT REUSERS

7

Professional users

For profit organisations purchasing or using services provided by professional reusers (type 2)

8

Social users

Not for profit organisations purchasing or using services provided by social reusers (type 3)

Illustration 1 describes the relation between the data sources and the different categories of data reusers.

First group (type 1), and possibly most important are the regular citizens, those who are mostly the taxpayers (directly or indirectly supporting the repository). Even though their consumption of data could be modest their influence on the rest of groups and on the managers of the repository definitely has to be taken into account. Their consumption is frequently associated with the need of transparency and accountability of the entity releasing the data.

Second group (type 2) are the professional reusers, for-profit entities using the data to enrich with data or to innovate in products and services. Those products and services finally are purchased by professional users, thus, they become indirect reusers. Remarkable examples of this type are data journalists (Gray et al, 2012) who explore data in order to find out stories with public interest. They are identified as 7 in the Illustration 1. so, every citizen when purchasing a newspaper with a data journalism article is a indirect reuser of the service provided by the data journalist.

The type 3 group of reusers are those that are non-profit or social organisations, their goals could be very specific for a collective of citizens, so do their requirements for the data to be released. There is a remarkable group of organisations taking data and creating awareness about some aspects of the existing policies. The group identified with 8 are those indirect reusers, that are users of these services. An example of this could be a NGO helping immigrants to find a new home, with the data of the social living facilities provided by the city.

The group 4 of reusers are those coming from the academia. Their needs could vary strongly from other groups. From interconnectivity with other repositories’ data, to semantic enrichment, to study of access mechanisms or etc. Their goals are exclusively related with research and academic purposes.

Now is the turn for two specific groups. They are identified in Illustration 1 with the figures 5 and 6. One is the very organisation releasing the data. Possibly one of the biggest consumers of the data released. The use of the data published could be understood as an internal resource to increase performance of the organisation. And secondly other public administrations that it could be also great consumers of the published information. In Illustration 1 it is assumed that the releasing entity is a public one, however this could not be the case. It is also true that currently, October 2016, it is by far the most frequent situation.

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