24,732 research outputs found
SPASE: Current Uses, Tools, and Plans
No full textThe Space Physics Archive Search and Extract (SPASE) project is an international collaboration among Heliophysics (solar and space physics) groups concerned with data acquisition and archiving. Within this community there are a variety of old and new data centers, resident archives, "virtual observatories", etc. acquiring, holding, and distributing data. The main product of the SPASE group is an XML-based SPASE Data Model now in operational use to enable searches for and ultimate acquisition of data of interest to a researcher. The SPASE Data Model defines the content of resource descriptions (metadata). The intent is to describe all SCientifically usable Heliophysics data sets using the Data Model. Another product of the SPASE group, in collaboration with NASA's Virtual Observatories, is a set of tools and services which work with SPASE meta data. This includes Registry Services which can retrieve and render metadata using resource identifiers and facilitate the downloading of the data referenced by the meta data. The SPASE Data Model has also been used as a vocabulary in specialized data models. One example is the Heliophysics Event List Manager (HELM) model. The SPASE Data Model is also being expanded to provide the means for more detailed description of data sets with the aim of enabling more automated ingestion and use of the data through detailed format descriptions. The evolution is based on a number of lessons learned and feedback from our community. Some of the lessons learned are unique to Heliophysics, and some are common to the various data diSCiplines. We will discuss the present state of SPASE usage, the role the SPASE Data Model can play in speCialized data models and how we foresee the development direction in the future
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
SPASE: The Connection along Solar and Space Physics Data Centers
No full textThe Space Physics Archive Search and Extract (SPASE) project is an international collaboration among Heliophysics (solar and space physics) groups concerned with data acquisition and archiving. The SPASE group has simplified the search for data through the development of the SPASE Data model as a common method to describe data sets in the archives. The data model is an XML-based schema and is now in operational use. The use is expanding, but there are still other groups who could benefit from adopting SPASE. We discuss the present state of SPASE usage and how we foresee development in the future
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
SPASE: The Connection Among Solar and Space Physics Data Centers
No full textThe Space Physics Archive Search and Extract (SPASE) project is an international collaboration among Heliophysics (solar and space physics) groups concerned with data acquisition and archiving. Within this community there are a variety of old and new data centers, resident archives, "virtual observatories", etc. acquiring, holding, and distributing data. A researcher interested in finding data of value for his or her study faces a complex data environment. The SPASE group has simplified the search for data through the development of the SPASE Data Model as a common method to describe data sets in the various archives. The data model is an XML-based schema and is now in operational use. There are both positives and negatives to this approach. The advantage is the common metadata language enabling wide-ranging searches across the archives, but it is difficult to inspire the data holders to spend the time necessary to describe their data using the Model. Software tools have helped, but the main motivational factor is wide-ranging use of the standard by the community. The use is expanding, but there are still other groups who could benefit from adopting SPASE. The SPASE Data Model is also being expanded in the sense of providing the means for more detailed description of data sets with the aim of enabling more automated ingestion and use of the data through detailed format descriptions. We will discuss the present state of SPASE usage and how we foresee development in the future. The evolution is based on a number of lessons learned - some unique to Heliophysics, but many common to the various data disciplines
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
Calibration and survey of AMANDA with the SPASE detectors
No full textWe report on the analysis of air showers observed in coincidence by the Antarctic Muon and Neutrino detector array (AMANDA-B10) and the South Pole Air Shower Experiment (SPASE-1 and SPASE-2). We discuss the use of coincident events for calibration and survey of the deep AMANDA detector as well as the response of AMANDA to muon bundles. This analysis uses data taken during 1997 when both SPASE-1 and SPASE-2 were in operation to provide a stereo view of AMANDA
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
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
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