21,216 research outputs found
Index to Library Trends Volume 33
published or submitted for publicatio
Better duplicate detection for systematic reviewers: Evaluation of Systematic Review Assistant-Deduplication Module
BACKGROUND: A major problem arising from searching across bibliographic databases is the retrieval of duplicate citations. Removing such duplicates is an essential task to ensure systematic reviewers do not waste time screening the same citation multiple times. Although reference management software use algorithms to remove duplicate records, this is only partially successful and necessitates removing the remaining duplicates manually. This time-consuming task leads to wasted resources. We sought to evaluate the effectiveness of a newly developed deduplication program against EndNote. METHODS: A literature search of 1,988 citations was manually inspected and duplicate citations identified and coded to create a benchmark dataset. The Systematic Review Assistant-Deduplication Module (SRA-DM) was iteratively developed and tested using the benchmark dataset and compared with EndNote’s default one step auto-deduplication process matching on (‘author’, ‘year’, ‘title’). The accuracy of deduplication was reported by calculating the sensitivity and specificity. Further validation tests, with three additional benchmarked literature searches comprising a total of 4,563 citations were performed to determine the reliability of the SRA-DM algorithm. RESULTS: The sensitivity (84%) and specificity (100%) of the SRA-DM was superior to EndNote (sensitivity 51%, specificity 99.83%). Validation testing on three additional biomedical literature searches demonstrated that SRA-DM consistently achieved higher sensitivity than EndNote (90% vs 63%), (84% vs 73%) and (84% vs 64%). Furthermore, the specificity of SRA-DM was 100%, whereas the specificity of EndNote was imperfect (average 99.75%) with some unique records wrongly assigned as duplicates. Overall, there was a 42.86% increase in the number of duplicates records detected with SRA-DM compared with EndNote auto-deduplication. CONCLUSIONS: The Systematic Review Assistant-Deduplication Module offers users a reliable program to remove duplicate records with greater sensitivity and specificity than EndNote. This application will save researchers and information specialists time and avoid research waste. The deduplication program is freely available online
A diachronic study of historiography
The humanities are often characterized by sociologists as having a low mutual
dependence among scholars and high task uncertainty. According to Fuchs' theory
of scientific change, this leads over time to intellectual and social
fragmentation, as new scholarship accumulates in the absence of shared unifying
theories. We consider here a set of specialisms in the discipline of history
and measure the connectivity properties of their bibliographic coupling
networks over time, in order to assess whether fragmentation is indeed
occurring. We construct networks using both reference overlap and textual
similarity. It is shown that the connectivity of reference overlap networks is
gradually and steadily declining over time, whilst that of textual similarity
networks is stable. Author bibliographic coupling networks also show signs of a
decline in connectivity, in the absence of an increasing propensity for
collaborations. We speculate that, despite the gradual weakening of ties among
historians as mapped by references, new scholarship might be continually
integrated through shared vocabularies and narratives. This would support our
belief that citations are but one kind of bibliometric data to consider ---
perhaps even of secondary importance --- when studying the humanities, while
text should play a more prominent role
POS Tagging and its Applications for Mathematics
Content analysis of scientific publications is a nontrivial task, but a
useful and important one for scientific information services. In the Gutenberg
era it was a domain of human experts; in the digital age many machine-based
methods, e.g., graph analysis tools and machine-learning techniques, have been
developed for it. Natural Language Processing (NLP) is a powerful
machine-learning approach to semiautomatic speech and language processing,
which is also applicable to mathematics. The well established methods of NLP
have to be adjusted for the special needs of mathematics, in particular for
handling mathematical formulae. We demonstrate a mathematics-aware part of
speech tagger and give a short overview about our adaptation of NLP methods for
mathematical publications. We show the use of the tools developed for key
phrase extraction and classification in the database zbMATH
Discipline Formation in Information Management: Case Study of Scientific and Technological Information Services
Discipline formation in information management is investigated through a case study of the origi-nation and development of information services for scientific and technical information in Australia. Particular reference is made to a case of AESIS, a national geoscience, minerals and petroleum reference database coordinated by the Australian Mineral Foundation. This study pro-vided a model for consideration of similar services and their contribution to the discipline. The perspective adopted is to consider information management at operational, analytical and strate-gic levels. Political and financial influences are considered along with analysis of scope, perform-ance and quality control. Factors that influenced the creation, transitions, and abeyance of the service are examined, and some conclusions are drawn about an information management disci-pline being exemplified by such services
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