24,827 research outputs found
The Structure of Scientific Collaboration Networks in Scientometrics
No full textThe structure of scientific collaboration networks in scientometrics was investigated at the level of individuals by using bibliographic data of all papers published in the international journal Scientometrics retrieved from the Science Citation Index (SCI) during 1978 to 2004. Combined analysis of social network analysis (SNA), co-occurrence analysis, cluster analysis and frequency analysis of words was explored to reveal: (1) The microstructure of the collaboration network on scientists’ aspects of scientometrics; (2) The major collaborative fields of the collaborative sub-networks; (3) The collaborative center of the collaboration network in scientometrics
Collaboration in Iranian Scientific Publications
No full textThis study looks at international collaboration in Iranian scientific publications through the ISI Science Citation Index® (SCI) for the years 1995-1999, inclusive. These results are compared to and contrasted with the earlier findings for the periods covering 1985-1994 (Osareh & Wilson 2000). The results of Iran's increasing productivity over a 15-year period are presented. Iran doubled its output in the first two five-year periods and increased 2.8-fold from the second to the third five-year period. The rise in Iran's scientific publication output is due mainly to factors such as the ending of the war, better economic conditions, recent changes in the Iranian government's policy, basic changes in the political environment brought about by the Reformers, expansion of the Iranian presses for national publications, and the recent return of a large number of students trained overseas through government scholarships. External changes also account for the increased productivity, e.g., the acceptance of three Iranian source journals by the SCI, increased access to international databases through the Internet and better electronic communication facilities for international collaboration. One of the most important and significant factors that caused this dramatic rise seems to be the government's research policies in the last few years. Since 1999, the Iran Science, Research and Technology Ministry, has encouraged researchers to publish their non-Farsi language articles in highly ranked international scientific journals, for example, by giving prizes to researchers who publish their articles in ISI-ranked journals
The methodological status of co-authorship networks
No full textA powerful strategy within the study of collaboration
in science is to posit that co-authorship patterns
represent social networks.
It is prerequisite to an application of Social
Network Analysis (SNA) to define the network
entities. A network analysis of the inter-institutional
collaboration in COLLNET on the basis
of co-authorships was conducted. The study reveals
that it is crucial whether the co-authorship
itself is seen as an author's relational property or
as a social event that brings the authors together.
The former possibility is represented by a onemode
network in which each author can be related
to each other author. Quite distinct from
that are two-mode networks, the latter approach.
They consist of two single data sets in which relations
are only possible between different sets.
Different modes of representations require
different network approaches. One is that co-authorship
networks are seen as one-mode networks,
which has the advantage of the application
of a variety of measures. In contrast, twomode
networks, the other option, cannot be analysed
by standard techniques but its distinctive
features demand a new conceptualisation of
measures. In conclusion, the two-mode perspective
is more promising because it allows a dual
perspective on collaboration in science which includes
researchers as well as their scientific output
Co-authorship Network of Scientometrics Research Collaboration
No full textThis paper examines the co-authorship network in the field of scientometrics using social network analysis techniques with the aim of developing an understanding of research collaboration in this scientific community. Using co-authorship data from 3125 articles published in the journal Scientometrics with a time span of more than three decades (1980-2012), we construct an evolving co-authorship network and calculate three centrality measures (closeness, betweenness, and degree) for 3024 authors, 1207 institutions, 68 countries and 22 academic fields in this network. This paper also discusses the usability of centrality measures in author ranking, and suggests that centrality measures can be useful indicators for impact analysis. Findings revealed that scientometrics was not dominated by a couple of key researchers as quite a significant number of popular researchers were identified. The United States occupies the topmost position in all measures except for degree centrality. The most active, central and collaborative academic discipline in scientometrics is Information & Library Science
How retail delis refrigerate food : EHS-Net rindings and recommendations
No full textEHS-Net RecommendsWe recommend that food safety programs and retail delis\u2022 Encourage or require kitchen managers to be certified in food safety.\u2022 Monitor and record refrigerator temperatures.Most delis keep food cold enoughto reduce growth of Listeria monocytogenes (Lm) and other germs that cause foodborne illness and outbreaks, but 1 in 6 delis do not.This study was conducted by the Environmental Health Specialists Network (EHS-Net).EHS-Net is a federally funded collaboration of federal, state, and local environmental health specialists and epidemiologists working to better understand the environmental causes of foodborne illness.Visit EHS-Net at www.cdc.gov/nceh/ehs/EHSNet.CS286740-Ahow-retail-delis-refrigerate-food-h.pd
A focus on the collaboration efforts between Early Head Start (EHS) and other programs providing Part C services
No full textThis study focused on the collaboration efforts between Early Head Start (EHS) Programs and other programs providing Part C services for the Iowa state system of early intervention (Early Access). Early Head Start can be a service provider for Part C services but cannot take sole responsibility for serving children, birth through 3 years, with special needs and their families. Therefore, other programs that specifically serve this population must be involved. The study examined how the programs are integrating their services to serve children with special needs and their families. This study used qualitative methods to describe the efforts of collaboration between the Early Head Start (EHS) Programs and the Part C Programs from three sites in Iowa. Interviews were conducted with families being dually served, as well as, the direct service providers and local administrators from each program. The interview questions addressed collaboration efforts related to (a) recruitment and referral of children with special needs, (b) the family and child assessment process, and (c) service delivery from both programs. The service providers and local administrators also addressed training, committee membership, and interagency agreements. After organizing the interviews into program profiles and family case studies, the findings were summarized in a table and a model of collaboration was applied.
Findings from this study suggest that collaboration between the EHS and Part C programs is not apparent through all levels of the programs (families, service providers, and administrators). For the most part, the service providers from both programs who were directly involved with the families were working independently in regard to assessment and service delivery. However, at the administrative level, collaboration was suggested through membership on each other's committees and other community partnerships
Groundwater and Human Security
No full textThe new working paper by Fabrice Renaud, Jose Luis Martin-Bodes and Brigitte Schuster contains the results from the Kick-Off Workshop in January 2008 in Bonn. GWAHS-CS is the first practical activity under the “Quo Vadis Aquifers?” umbrella programme and is a collaboration between, among others, UNESCO-IHP, UNU-EHS and UNU-INWEH. Working Paper No. 4 includes the results of three brainstorming sessions which took place after the presentation of four case studies.The working paper deals with four case studies: Vietnam (2), Egypt and Iran
Measuring author influence in scientific collaboration networks
No full text
Purpose: The purpose of this paper is to measure author influence in scientific collaboration networks by considering the combined effects of multiple indexes. In the meanwhile, we intend to explore a method to avoid assigning subjective weights.
Design/methodology/approach: We applied four centrality measures (degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) and authors' published papers to the scientific collaboration network. The grey relational analysis (GRA) method based on information entropy was used to measure an author's impact in the collaboration network. The weight of each evaluation index was determined based on information entropy. The ACM SIGKDD collaboration network was selected as an example to demonstrate the practicality and effectiveness of our method.
Findings: Author influence was not always positively correlated with evaluation indexes such as degree centrality and betweenness centrality. This implies that combined effects of multiple indexes should be considered in author impact analysis. The introduction of the GRA method based on information entropy can reduce the interference of human factors in the evaluation process.
Research limitations: We only analyzed author influence from the perspective of scientific collaboration, but the impact of citation on author influence was ignored.
Practical implications: The proposed method can be also applied to detect influential authors in bibliographic co-citation network, author co-citation network, bibliographic coupling network or author coupling network. It would help facilitate scientific collaboration and enhance scholarly communication.
Originality/value: This paper proposes an analytical method of evaluating author influence in scientific collaboration networks, in which combined effects of multiple indexes are considered and the interference of human factors is reduced in the evaluation process.
Purpose: The purpose of this paper is to measure author influence in scientific collaboration networks by considering the combined effects of multiple indexes. In the meanwhile, we intend to explore a method to avoid assigning subjective weights.
Design/methodology/approach: We applied four centrality measures (degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) and authors' published papers to the scientific collaboration network. The grey relational analysis (GRA) method based on information entropy was used to measure an author's impact in the collaboration network. The weight of each evaluation index was determined based on information entropy. The ACM SIGKDD collaboration network was selected as an example to demonstrate the practicality and effectiveness of our method.
Findings: Author influence was not always positively correlated with evaluation indexes such as degree centrality and betweenness centrality. This implies that combined effects of multiple indexes should be considered in author impact analysis. The introduction of the GRA method based on information entropy can reduce the interference of human factors in the evaluation process.
Research limitations: We only analyzed author influence from the perspective of scientific collaboration, but the impact of citation on author influence was ignored.
Practical implications: The proposed method can be also applied to detect influential authors in bibliographic co-citation network, author co-citation network, bibliographic coupling network or author coupling network. It would help facilitate scientific collaboration and enhance scholarly communication.
Originality/value: This paper proposes an analytical method of evaluating author influence in scientific collaboration networks, in which combined effects of multiple indexes are considered and the interference of human factors is reduced in the evaluation process.</div
Inter-institutional scientific collaboration: an approach from social network
No full textThis paper presents a tool that can be used to characterize, analyze and interpret the
patterns of collaboration among institutions by means of the visual display of scientific
information. These graphic representations allow for a combined analysis of a given
institution in the system of relations (network), and of the particular attributes of that
institution (indicators). The tool affords the possibility of regenerating the network to
make any number of aggregates appear or disappear, thus allowing one to focus on
institutional sectors, geographic regions, etc. It also allows for analysis of sectorial
interaction, institutional backing of research, and the influence of geographic proximity,
linguistic affinity, or regional politics. This is indeed a versatile analytical tool, and it is
bound to prove its potential for evaluating patterns of collaborative research, development
and innovation
EHS/NA22 Collaboration N.M. AGABABYAN
No full text: A triple Regge analysis is performed of inclusive production in the proton fragmentation region of K + ! + X and ß + ! +X at 250 GeV/c. Slope and intercept of the leading strange meson trajectory are determined. The results obtained here are compared with those of other experiments. Inclusive production has been studied in the framework of the triple Regge model in the proton fragmentation region of pp[1 \Gamma 4], ß \Gamma p[5], K \Gamma p[6 \Gamma 8] and K + p interactions [9,10] . However, in only few of these experiments the data have been analysed at large enough energies and with sufficient statistics. In this paper we apply the triple Regge analysis to the reactions K + p ! +X (1) ß + p ! +X (2) at 250 GeV/c, the highest beam momentum so far reached for positive mesonproton collisions. The data presented here come from the NA22 experiment performed at CERN. In this experiment the European Hybrid Spectrometer (EHS) is equipped with the Rapid Cycling Bubble..
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