CORVALLIS, Ore. – Science has become increasingly specialized and driven by the analysis of new data, creating a gap in training, funding and institutional support for researchers who are seeking to synthesize previous research findings, according to a group of scholars.
Despite cultural and technological barriers to the process, some of the most important research of the last quarter-century has resulted from “synthetic science,” which combines different data sets, results and unconnected methods or concepts – leading to new discoveries or trends.
In a commentary piece in the journal Evolution, the authors argue for removing these cultural and technological barriers to synthetic science.
“By putting together pieces of prior research, it is possible to transform how you do science and open the doors to findings that previously were unattainable,” said Brian Sidlauskas, a fish biologist from Oregon State University and lead author on the Evolution article. “But such an approach runs counter to the way science traditionally has been conducted, so pursuing synthetic science is somewhat risky.”
“We need to reduce the risk, remove the barriers, and encourage more pursuit of synthesis because the potential,” he added, “is staggering.”
The authors, who all are affiliated with the National Evolutionary Synthesis Center (NESCent), cite the work of J. John Sepkoski Jr., who over a 20-year period compiled a database of more than 37,000 entries tracking the first and last appearance of different organisms in the fossil record. The entries, they write, “cut across taxa, time, and geography to reveal emergent patterns over more than 500 million years of life that could not be extracted from the component data in isolation.”
“That database led to previously undetermined knowledge of five separate mass extinctions through time, understanding of how major geologic events can increase or reduce biodiversity, the realization that near-shore environments produce a disproportionately large share of evolutionary novelty and other findings,” Sidlauskas said. “It also spawned a new field of synthetic paleobiology.”
Sepkoski’s data aggregation is one of four methods of synthesis the authors say can transform science. The others, including examples of success, are:
- Re-use of results: A pair of landmark studies combined hundreds of previous results in single analyses to demonstrate conclusively that climate change alters species’ distribution, abundance and morphology in a large proportion of cases. These synthetic studies gathered more than 2,300 citations in just five years and substantially informed the current United States government policy on climate change.
- Integrating methods: Merging the types of analysis from two distinct research fields – such as genetics and evolutionary biology – has led to new ways to use modern DNA sequences to look into the past to understand the origin of genomes and reconstruct how their structure has changed over millions of years.
- Conceptual synthesis: The emerging discipline of evolutionary medicine is one example of how linking concepts from two distinct fields can yield new ways to approach scientific problems. Write the authors: “The incontrovertible value of viewing a modern person as the result of past evolutionary pressures, tied intimately to population genetics and historical environments, can assist physicians in understanding puzzling medical conditions.”
For example, a recent study in evolutionary medicine linked an increase in asthma rates to a heightened immune response that might originally have helped our ancestors fend off parasites.
Despite the promise, the researchers say, there are a number of cultural barriers to pursuing synthetic science. It is difficult for young scientists to find appropriate training in how to pursue this scientific approach; peer review and journal publication tend to emphasize the analysis of new data and would need to be re-evaluated; funding from state and federal agencies is more frequently directed toward more specific studies; and there are institutional challenges with job searches, promotion and tenure – all of which are geared toward more traditional science.
The technological barriers also are daunting, but offer tantalizing potential, Sidlauskas said.
“When you’re looking to synthesize data from several hundred individual studies, data formatting, storage and accessibility become huge issues,” he said. “There has been a growing movement by funding agencies and journals to permanently archive all raw data and materials in some kind of standardized format so they are not lost over time and can be used by researchers of the future.
“It’s kind of an open-source approach to science,” he added. “Data archives may require some kind of proprietary protection for a few months or years, but after a certain amount of time, they should become public domain. Only by saving the data that underlie today’s science will we allow future scientists to use those data in ways that may far exceed what the original researchers envisioned.”
Other authors on the commentary piece include Ganeshkumar Ganapathy, of the National Evolutionary Synthesis Center (NESCent); Einat Hazkani-Covo, Duke University Medical Center; Kristin P. Jenkins, NESCent; Hilmar Lapp, NESCent; Lauren W. McCall, NESCent; Samantha Price, University of California-Davis; Ryan Scherle, NESCent; Paula A. Spaeth, Northland College; and David M. Kidd, NERC Centre for Population Biology, Imperial College London.