Jan Leendertse on Sun, 31 May 2020 14:36:56 +0200 (CEST)


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Re: <nettime> nettime-l Digest, Vol 152, Issue 2 -> Remarks to big data


Am 02.05.20 um 12:00 schrieb nettime-l-request@mail.kein.org:
-- Data must be deleted after the immediate purpose of analysis has
been achieved and, if new data has been generated, the process of
collecting this data must end.

-- Analysis must to be restricted to predetermined ends of public
interest. This can be achieved by separating the entity framing the
research question(s), such as a public health institute, and the
entities undertaking the actual data analysis. This is necessary
to prevent mission creep and fishing expeditions based on the
availability of the data.

-- Data must be made available to multiple teams that are completely
independent from one another. This prevents the public from becoming
dependent on the analysis of data providers (say, social media
companies) and also allows for the cross-examination of different
methods of data analysis. Every model has its own biases, and their
justification can only be assessed in comparison to others.

A bit delayed, some remarks to the framework of big data regimes.

It might be necessary to clarify some aspects regarding the handling of big data sets.

If research uses big data sets, especially when funded by public organisations, they are obligated to keep the data, and this even with good reasons. Data driven research should be reproducible. This is only possible if the full research process is available for reproduction.

The analysis of data with new questions might reveal new insights. This should be weighed against disadvantages of keeping data, which can be leveraged against people. Pseudonymization or anonymizing as tool against data collection is an illusion, so possible misuse must be handled on a different level.

This belongs to the field of research data, not data used for data driven policy-making.


Best,

Jan
--
Jan Leendertse
https://leendertse.eu



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