At last month’s London Book Fair special presentation on “The Data Dilemma,” Sybil Wong, Ph.D., Head of Marketing and Communications for Sparrho, called attention to the “irrelevance crisis” facing researchers in the lab and on campus.
“208,000 new articles are published every month, though a typical researcher only reads about 22 articles per month – just over 0.0001% of new publications,” said Wong.
In such a dark ocean of information, discoveries important to the researcher’s own work are easily overlooked. Machine curation, including text mining, may address the problem, though only up to a point. What a machine finds must be relevant or the human reader will dismiss it. Sparrho tackles the irrelevance crisis with an innovative personal recommendation platform for scientific content and opportunities.
“Machines can more easily make stringent decisions on large volumes of entries and help find ‘unexpected’ results from sources that humans may be biased against or not know about, such as smaller journals,” she explained.
Sybil Wong’s complete presentation, including slides, may also be viewed on YouTube.