30 research outputs found
Finding and Recommending Scholarly Articles
The rate at which scholarly literature is being produced has been increasing
at approximately 3.5 percent per year for decades. This means that during a
typical 40 year career the amount of new literature produced each year
increases by a factor of four. The methods scholars use to discover relevant
literature must change. Just like everybody else involved in information
discovery, scholars are confronted with information overload. Two decades ago,
this discovery process essentially consisted of paging through abstract books,
talking to colleagues and librarians, and browsing journals. A time-consuming
process, which could even be longer if material had to be shipped from
elsewhere. Now much of this discovery process is mediated by online scholarly
information systems. All these systems are relatively new, and all are still
changing. They all share a common goal: to provide their users with access to
the literature relevant to their specific needs. To achieve this each system
responds to actions by the user by displaying articles which the system judges
relevant to the user's current needs. Recently search systems which use
particularly sophisticated methodologies to recommend a few specific papers to
the user have been called "recommender systems". These methods are in line with
the current use of the term "recommender system" in computer science. We do not
adopt this definition, rather we view systems like these as components in a
larger whole, which is presented by the scholarly information systems
themselves. In what follows we view the recommender system as an aspect of the
entire information system; one which combines the massive memory capacities of
the machine with the cognitive abilities of the human user to achieve a
human-machine synergy.Comment: 14 pages, part of the forthcoming MIT book "Bibliometrics and Beyond:
Metrics-Based Evaluation of Scholarly Research" edited by Blaise Cronin and
Cassidy R. Sugimot
Merging the Astrophysics and Planetary Science Information Systems
Conceptually exoplanet research has one foot in the discipline of
Astrophysics and the other foot in Planetary Science. Research strategies for
exoplanets will require efficient access to data and information from both
realms. Astrophysics has a sophisticated, well integrated, distributed
information system with archives and data centers which are interlinked with
the technical literature via the Astrophysics Data System (ADS). The
information system for Planetary Science does not have a central component
linking the literature with the observational and theoretical data. Here we
propose that the Committee on an Exoplanet Science Strategy recommend that this
linkage be built, with the ADS playing the role in Planetary Science which it
already plays in Astrophysics. This will require additional resources for the
ADS, and the Planetary Data System (PDS), as well as other international
collaboratorsComment: Whitepaper submitted to the Committee on an Exoplanet Science
Strateg