Goals & Rationale
When I began thinking of a way to ensure the just and safe progression of biotechnology, I instantly thought of Theranos – a multibillion-dollar biotech start-up with the goal of utilizing only a few drops of blood to perform essential clinical tests. In retrospect, what went wrong? Test results turned out to be inaccurate. Theranos began using the traditional machine instead of its own. No one was exposed to Theranos’ technology. Signs of protest were silenced. Investors donated funds blindly, without any scientific data to convince them. Theranos operated under total secrecy. The public was lied to and, as a side effect, trust in biotechnology significantly degraded.
We live in the shift towards open-access science:
1. Transparency and Openness Promotion (TOP) guidelines in scientific journals.
2. Funders, too, are increasingly adopting an open-data policy. Several strongly encourage, and some require, a system which provides availability of data. The US National Science Foundation, the Bill & Melinda Gates Foundation in Seattle, Washington, and the Wellcome Trust in London, also mandate open data from their grant recipients.
3. The Public Library of Science also requires authors who publish in its journals to share all the data necessary to reproduce their studies.
However, data sharing for open-access science isn’t always impeccable...
1. A researcher may decline sharing due to the ambiguity of future use of his/her data
2. Expectations of what data sharing entails may differ
Design & Requirements
An inter-connection amongst researchers under the same institution whereby third parties are able to assess validity of data – a “cross-check” system. What does it entail?
1. Open-data access of scientific data by a rightful requestor – to be able to reproduce a study, build another from existing results, refute non-coherent data to ensure validity and reliability, require transparency, and incentivize collaboration. Every single journal in the United States must publish a paper only if open-data sharing and access availability has been demonstrated.
2. A journalistic/institutional body to expose and translate the shared data to the public. As science becomes more complex, the ability to trust it becomes more difficult: the population must be kept up to date on truthful advancements introduced under principles of ethics, honesty, and collectivity.
3. A whistle-blowing system to report fraudulence without the threat of exposition.
An open “cross-check” system can yield a multitude of consequences: a system of equity in the sciences can be established, so that even a junior researcher can claim the authority to request data. The perception of science can be more transparent and accessible.
1. The institution must implement change: the policy of “cross-checking” and the features it entails must be treated as a requirement for employment, grant awarding, and general participation in an institution.
2. Scientific journals must contribute in placing pressures on received papers, accepting only those that have undergone the process of “cross-checking”. This can work: as Nature went to press, 538 publishers and journals — including Elsevier and Springer Nature — had signed up to the TOP guidelines, along with 57 organizations.
Assumptions & Risks of “Success”
1. I am assuming that a researcher will comply to the "cross-check" system does not know to what project his/her results may be going.
2. Corrupted partnership may arise within an institution.
3. Open-access data does not save researchers from publishing falsified data.
4. A researcher may seek to keep his project under the radar: the “obligation” to expose may heighten secrecy.
There are potential setbacks...
1. The institution (e.g. the hospital, the medical school) would have to increase spending for scientific equipment.
2. The duration of a research period may be lengthened and stalled as a result of “cross-checking” time requirements. Does the benefit of transparency outweigh the temporal cost?
3. A heightened sense of competition and rivalry may grow.
4. Internal corruption may become a ‘loophole’ within the system – negative or positive. If negative, a research team with the duty to “cross-check” another’s research project may purposefully sabotage it. If positive, research teams with obscure secrecy may collaborate together under no supervision.