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In einer neuen Episode des “Velocity of Content Podcasts” des CCC sprechen wir mit Mary Ellen Bates. Bates berät Kund:innen in forschungsintensiven Branchen zu ihrem Informationsbedarf. Kürzlich hat sie auf der gemeinsamen Konferenz der Medical Library Association und der Special Libraries Association in Detroit über die Ergebnisse ihrer aktuellen Studie zu Best Practices für Informationsprofis bei der Zusammenarbeit mit Datenprofis berichtet. In einer Vorschau erzählt in unserem Podcast, wie und wann Infoprofis an einem datengesteuerten Forschungsprojekt teilnehmen sollten. 

In 2012 in the Harvard Business Review, Thomas Davenport, an authority on data analytics, and mathematician DJ Patil, who served as first US chief data scientist, declared that data scientist would prove to be “The Sexiest Job of the 21st Century.” 

The demand for data scientists is indeed strong and is even accelerating, with the US Bureau of Labor Statistics expecting employment of data scientists to grow 36% from 2021 to 2031, much faster than the average for all occupations. 

Data scientists are found working in fields where data-driven decision making dominates, from financial services and information technology to healthcare and biotech. They often work closely with librarians and others trained in information science. The two roles are complementary, and organizations can benefit from aligning the positions strategically. 

Click to listen to the latest episode of the Velocity of Content podcast. 

Mary Ellen Bates advises clients in research-intensive industries on their information needs. Recently, she reported on findings from her latest study of best practices for info pros when working with data pros at the Medical Library Association/Special Libraries Association joint conference in Detroit. Bates told me about examples of how and when info pros should participate in a data-driven research project. 

“The info pros ensure that the organization isn’t spending a whole lot of money on data that can’t be used or that can’t be used the way they thought it could, that can’t be reused, and it causes more work downstream that isn’t worth the cost to the organization,” she explains. 

“Often, it’s making a strategic decision about not acquiring one kind of data, because while it appears good, the info pros see the bigger picture and see that the ramifications of acquiring this data does not actually serve the organization as well as the data scientists may have thought of it.“

Author: Christopher Kenneally

Christopher Kenneally hosted CCC's Velocity of Content podcast series for more than 18 years, organizing programs that addressed the business needs of all stakeholders in publishing and research. His reporting has appeared in the New York Times, Boston Globe, Los Angeles Times, The Independent (London), WBUR-FM, NPR, and WGBH-TV.