Page 60 - Academic and Research Book_WEB

• Anonymous data refers to data that has been collected without referencing the informant so
much so that even the researcher may not know how the data has been collected and from
whom. For example, baseline data.
While collecting data, the highest ethical standards must be upheld. The research plan must describe
how data is being collected and for what purpose. It should also state how the data is going to be
stored and for how long, and who will be utilising it and whether in future, others will have access to
it in any form.
Data protection today is a highly sophisticated area of technology. Several tools and methods are
available to ensure that data can be stored securely. But here too the researcher cannot remain ignorant
of the methods of storage because of the ethical obligation to ensure secure storage and handling. Data
may be of two kinds: prospective data and retrospective data.

Prospective data is collected for the purpose of research. The researcher has more control over how
this data is collected and stored. All information collected must remain confidential. The questions
seeking information must be clear and succinct. Most importantly, a researcher must not collect more
information than is required. The participant’s time in providing the data must be acknowledged and
there must be no misuse of that time.
Retrospective data is collected for different purposes and is now available for other researchers.
Here questions have been raised about the ethics of using data that the participant has provided for a
purpose other than the current one. This amounts to stealing information from the participant under
false representation. It is therefore necessary to check how this data has been collected and if the
participant has given consent to the data being used by others. Seeking the origins of the data is not
just a methodological issue but it is one way of protecting the rights of the person who has provided
the data.

Strictly speaking, this is difficult to achieve since not all datasets that are available have this
information. However, it is possible to obtain access to raw data or at least to the provenance of
the raw data. In fact, many journals insist on knowing the provenance of the data while reviewing
an article for publication. Ethical concerns on using retrospective data are becoming increasingly
important because today large datasets are available for sale from commercial data aggregators.

An example of how failure to obtain information about the origin of data can put the entire research
in jeopardy revolves around a bunch of studies on the possibility of using hydroxyquinolines
in controlling COVID-19. A major study showing that the drug was not of much use, based on
aggregated global data that was made available by a commercial aggregator, Surgisphere, was hailed
as an important one and the WHO even changed its policy suggestion based on this study. However,
soon doubts were expressed on the validity of data in several countries, and this led to an examination
of the data. When the aggregator refused to reveal the sources of the raw data, not only did journals
withdraw the articles that had been published, but an entire slew of research based on this data had to
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be withdrawn and abandoned.
Ethical considerations come into play even when analysis of the data is interpreted and presented.
Data analysis is a subjective process using objective tools. The choice of data analysis software
and tools must include an ethical dimension. The question should be whether the best possible
interpretation may be given to the data in answering the research question and not how best to force
the data to tell the tale that will fit the hypothesis.

Presented data must not inadvertently disrespect the participants of the research. The choice of what
is to be presented lies with the researcher. Every effort must be made to ensure that the data does not

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