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In pursuit of data immortality – Nature (Michael Eisenstein | April 2022)

Posted by Dr Gary Allen in Research Integrity on May 3, 2022
Keywords: Collaborative research, Data management, Good practice, Institutional responsibilities, Research integrity, Researcher responsibilities

The Linked Original Item was Posted On April 4, 2022

Data management - 3d white text over blue between grey boxes keyboard, business organizing concept words


Data sharing can save important scientific work from extinction, but only if researchers take care to ensure that resources are easy to find and reuse.

Between 1969 and 1972, the United States landed six crewed spacecraft on the Moon as part of the Apollo programme. The missions retrieved priceless samples. But for more than four decades, the data from those samples remained stashed away at a handful of US laboratories — until Kerstin Lehnert came along.

Can there be a more startling example of the problems with data and sample sharing than for more than 40 years, the research community did not have access to the samples returned from the moon?  Most sets of data and material won’t be quite as precious as the product of a flight to the moon (though in the coming years, samples will be returned to Earth from Mars and asteroids).  There are some excellent ethical reasons to retest human research (e.g. to reduce the burden on participants) and commentary that sharing can boost researcher careers.  Researchers must plan for open data and sharing, long term retention and metadata listing.

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A geoinformatician specializing in data rescue and preservation, Lehnert set out in 2014 to transform these data sets into a usable resource. Her team at Columbia University’s Lamont–Doherty Earth Observatory in Palisades, New York, pored through old conference abstracts, scanned reams of publications and debriefed the senior researchers who first studied those lunar samples to collect, organize and annotate as much information as possible. One scientist, Lehnert says, “came with a half-metre-high pile of old, folded printouts and we spent a whole summer typing those data into Excel spreadsheets”. Thanks to their efforts, these one-of-a-kind data are now freely available in the Astromaterials Data System.

Countless other laboratories, and their precious, irreplaceable data, are not so fortunate.

Lost to the ages
‘Big science’ efforts led by international consortia typically have data-management and sharing plans built in. But many labs doing small- to medium-scale studies in more specialized areas — such as analysing the biological contents of a single lake, or tracking the physiology of specific animal models — have no such systems. Their data often remain siloed in the labs that generated them, fading from memory as project members leave.

For the scientific community, that’s a tragedy of wasted effort, lost collaborative opportunities and irreproducibility. “Things don’t have to be really popular in order to be still very valuable,” says Erik Schultes, international science coordinator for the GO FAIR International Support and Coordination Office in Leiden, the Netherlands. Established in 2018 to develop best practices for data preservation and sharing, GO FAIR is one of several efforts engaging with researchers in almost every scientific discipline to secure today’s data for posterity. But success will require a concerted effort — and a shift in lab culture.

In pursuit of data immortality
Data sharing can save important scientific work from extinction, but only if researchers take care to ensure that resources are easy to find and reuse.

Related Reading

Time to recognize authorship of open data – Nature (Editorial | April 2022)

Revisiting: Is There a Business Case for Open Data? – Scholarly Kitchen (Tim Vines | August 2021)

An ethics argument for data sharing

Hong Kong Principles

Better Metadata Could Help Save The World! – Scholarly Kitchen (Alice Meadows | June 2019)

Credit data generators for data reuse – Nature (Heather H. Pierce, et al | June 2019)

Guest Post: Encouraging Data Sharing: A Small Investment for Large Potential Gain – Scholarly Kitchen (Rebecca Grant, et al | January 2019)

Move clinical trial data sharing from an option to an imperative – STAT (Rebecca Li | February 2019)

The main obstacles to better research data management and sharing are cultural. But change is in our hands – LSE Blog (Marta Teperek and Alastair Dunning | November 2018)

What factors do scientists perceive as promoting or hindering scientific data reuse? – LSE Impact Blog (Renata Gonçalves Curty, et al | March 2018)

What incentives increase data sharing in health and medical research? A systematic review (Papers: Anisa Rowhani-Farid, et al | May 2017)

Sharing Data and Materials in Psychological Science – Sage Journals (D. Stephen Lindsay | April 2017)

What Constitutes Peer Review of Data? A Survey of Peer Review Guidelines – Scholarly Kitchen (Todd A Carpenter | April 2017)

Data Ownership Guidelines (Resources: Example from an Australian school of Applied Psychology | 2016)

We must urgently clarify data-sharing rules – Nature (Jan-Eric Litton | January 2017)

Publishing and sharing data papers can increase impact and benefits researchers, publishers, funders and libraries – LSE Impact Blog (Fiona Murphy | October 2016)

Beyond open data: realising the health benefits of sharing data – theBMJ (Elizabeth Pisani, et al September 2016)

Data availability statements and data citations policy: guidance for authors – NatureResearch (Guidelines/Policies)

Addressing Global Data Sharing Challenges (Papers: George C. Alter Mary Vardigan 2015)

Consent and confidentiality in the light of recent demands for data sharing (Papers: Garrath Williams and Iris Pigeot )

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