3.2 Analyzing values
Ronald Meijer et al.
Having identified the values playing a crucial role in OD, here we analyze how they are related to each other. Figure 1 resumes the OD values as described above. It depicts the public OD values transparency, trust, privacy and security and the way they assumingly relate to each other and to three selected intermediary elements, replicability, information overload and reliability. The way public values and intermediary elements relate to each other is depicted by arrows. These elements may reinforce each other, indicated by a“+” sign, or contradict,“ ‐” sign. The intention of this chart is not to be complete. Its intention is to show the apparent contradictions between the public values on which we focus in this paper. The intermediary elements will only be briefly described in relation to the values. An elaborate discussion of these elements is beyond the scope of this paper.
Figure 1: Open data values
OD ‐ making data accessible for( re‐) use to the public – is assumed to contribute to transparency. By giving access to research and( semi) government data, civilians, policy makers, journalist, audits and scientists get opportunities to control, verify the data, replicate research findings or create new findings. It is assumed that this results in maintaining or increasing trust. However there is a“ dark side” to opening data without constraints or restrictions imposed on the access to data. This“ dark side” may lead to several contradictions in the OD policy values.
In the first place OD may conflict with privacy. The opening of data is seriously impeded when privacy sensitive data are at stake. OD may not seem to be personal data at first glance, especially when it is anonymized or aggregated. However, it may become personal data by combining it with other publicly available data or when it is deanonymized( Kulk et al. 2012)( Denning and Denning 1979). Anonymizing data cannot be“ 100 % privacy proof”. Even when data with a high aggregation level is shared, the risk that one is able to deduce or abduce privacy‐sensitive information remains( Braak et al. 2012)( Ohm 2009). Opening up data without taking into account the privacy risks attached, may lead to privacy breaches with possibly very negative consequences for the trust of respondents who participated in research and civilians in research or government. We may have found a possible negative relation between the privacy value and trust. To prevent privacy breaches, it is necessary to eliminate privacy sensitive attributes. However this may have a negative impact on the possibility of using the OD for replicability as some of the attributes needed to ensure the replication cannot be used any longer. Thus as privacy is protected, not all results may be replicated as a consequence. This may have negative impact on trust.
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