OPEN

Access dimension shows a positive relation with data consumption

As shown in results for the restricted data Illustration 18 and Illustration 19, there is a positive relation between the data consumption and reusability dimension of access. Causality between both magnitudes should be proved based on an extended analysis. The next two factors could explain the low level of relation:

1. It takes a long time (T_TIR) to create a useful application, service or product based on new information available. See 3.4.Analysis and Time to Implement Reuse (TTIR). It could be counted in months.
2. As we can see in Illustration 13, there is constant increase of PSI (open data) portals, meaning that a big percentage of the sampled sources in 3.2. Methodology for sampling public data sources are newer than the sampling of companies data were performed. (If data sources available were growing at the same rate than portals –which is a conservative hypothesis– 30% of data sources did not exist on June 2012, when data for infomediaries were sampled). Additionally newer sources tend to have a higher reusability MELODA index. So, their impact could exceed 50% of the overall result. This is commented in section 4.2, Illustration 17, on the difference between MELODA reusability indexes by scope and it would confirm this explanation for the weak relationship.

3. Technical standard does not show a positive relation with data consumption

   Contrary to the expectations, our own experience and common sense, results do not show a positive relation between the reusability for the technical standard dimension. Although it seems that in Illustration 20 could show such relation, deeper analysis of data refutes that statement. We find three possible explanations,

   1. The strong industrial crisis (which has reduced the sector in 24% from year 2011 to 2012) could hide results as this percentage exceeds potential relation effects.
   2. As introduced in the previous section, and described in 3.4 Analysis and Time to Implement Reuse (TTIR), there is a time gap between sampling of companies results (May-June of 2012) and sampling of PSI sources (Sep-Oct 2013). It could reflect a time lapse between the availability of sources and its economic effects.
   3. Technical standard integration is a one-shot investment. Once connected the data source for the infomediary company, contrary to the access dimension, there is no further costs for this dimension (unless that there were a change in the standard from the data source, which is uncommon). So this dimension, could be (like legal dimension), a pass non-pass dimension. If the forecasted cost is lower than potential profit, further increase in accessibility does not represent more reuse and therefore it would not show relation. Then this dimension could be only an economic threshold to start with its use.

   Global conclusions

   The economic modelling of PSI reuse is in its early ages. Not only is there a lack of theoretical models, but also there is a lack of data in order to oppose the theoretical model to the actual data. This research helps to create the theoretical framework to analyses systematically the problem of the economic impact of PSI reuse. Global description of the model, metric to assess the reusability of data sources and Time to Information Reuse would help on that. On the other hand the remarkable economic importance of the PSI reuse spurs further practical investigations on this field. Preliminary results in this work show that some factors affect the economic impact. Besides the legal licensing necessary for commercial reuse, access mechanisms appear as the first candidate dimension to drive this economic impact. It does not mean that it will be even the most relevant, and causality should be proved with further investigations. New data coming from infomediary sector would confirm to what extent such impact exists. On the other hand characterisation of the ‘Time to Implement Reuse‘ as described in 3.4. Analysis and Time to Implement Reuse (TTIR) could transform our practical vision of the economic impact evolution.