Paper Info
Title
Exploring The Relationship Between The Engineering And Physical Sciences And The Health And Life Sciences By Advanced Bibliometric Methods
Abstract
We investigate the extent to which advances in the health and life sciences (HLS) are dependent on research in the engineering and physical sciences (EPS), particularly physics, chemistry, mathematics, and engineering. The analysis combines two different bibliometric approaches. The first approach to analyze the 'EPS-HLS interface' is based on term map visualizations of HLS research fields. We consider 16 clinical fields and five life science fields. On the basis of expert judgment, EPS research in these fields is studied by identifying EPS-related terms in the term maps. In the second approach, a large-scale citation-based network analysis is applied to publications from all fields of science. We work with about 22,000 clusters of publications, each representing a topic in the scientific literature. Citation relations are used to identify topics at the EPS-HLS interface. The two approaches complement each other. The advantages of working with textual data compensate for the limitations of working with citation relations and the other way around. An important advantage of working with textual data is in the in-depth qualitative insights it provides. Working with citation relations, on the other hand, yields many relevant quantitative statistics. We find that EPS research contributes to HLS developments mainly in the following five ways: new materials and their properties; chemical methods for analysis and molecular synthesis; imaging of parts of the body as well as of biomaterial surfaces; medical engineering mainly related to imaging, radiation therapy, signal processing technology, and other medical instrumentation; mathematical and statistical methods for data analysis. In our analysis, about 10% of all EPS and HLS publications are classified as being at the EPS-HLS interface. This percentage has remained more or less constant during the past decade.
Year
DOI
Venue
2014
10.1371/journal.pone.0111530
PLOS ONE
Field
DocType
Volume
Data science,Scientific literature,Engineering and Physical Sciences,Citation,Citation analysis,Biological Science Disciplines,Bibliometrics,Bioinformatics,Network analysis,Health informatics,Mathematics
Journal
9
Issue
ISSN
Citations 
10
1932-6203
2
PageRank 
References 
Authors
0.39
12
3
Name
Order
Citations
PageRank
Ludo Waltman1453.91
Anthony F. J. van Raan240.83
Sue Smart320.39