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SciMAT (Science Mapping Analysis software Tool) is a new open source science mapping software tool developed at University of Granada. It integrates the advantages of the science mapping software tools available while reducing dependence on third party software. It can be freely downloaded, modified and redistributed according to the terms of GPLv3 license.
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Version 1.0
User guide
M.J. Cobo, A.G. López-Herrera, E. Herrera-Viedma, F. Herrera
University of Granada. Spain
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1) Introduction
SciMAT (Science Mapping Analysis software Tool) is a new open source science
mapping software tool developed at University of Granada. It integrates the advantages
of the science mapping software tools available while reducing dependence on third
party software. It can be freely downloaded, modified and redistributed according to the
terms of GPLv3 license.
It is based on the science mapping analysis approach presented in Cobo et al. (2011)
which allows us to carry out science mapping studies under a longitudinal framework
(Garfield, 1994; Price & Gürsey, 1975).
The main characteristics of SciMAT are:
- It incorporates all modules necessary to carry out all the steps of the science mapping
workflow, which can be configured ad-hoc. It helps the analyst to carry out the
different steps of the science mapping workflow, from data acquisition and
preprocessing to the visualization and interpretation of the results.
- It incorporates methods to build the majority of the bibliometric networks, different
similarity measures to normalize them and build the maps using clustering
algorithms, and different visualization techniques useful for interpreting the output.
- It implements a wide range of preprocessing tools such as detecting duplicate and
misspelled items, time slicing, data reduction and network preprocessing.
- According to Cobo et al. (2011), SciMAT allows the analyst to perform a science
mapping analysis in a longitudinal framework in order to analyze and track the
conceptual, intellectual or social evolution of a research field through the course of
consecutive time periods.
- Similarly, according to Cobo et al. (2011), SciMAT builds science maps enriched
with bibliometric measures based on citations such as: h-index (Alonso et al., 2009;
Hirsch, 2005), g-index (Egghe, 2006), hg-index (Alonso et al., 2010), q
2
-index
(Cabrerizo et al., 2010), etc.
SciMAT is divided into three different modules: i) a module dedicated to the
management of the knowledge base and its entities, ii) a module responsible for
carrying out the science mapping analysis, and iii) a module to visualize the generated
results and maps. These modules allow the analyst to carry out the different steps of the
science mapping workflow.
In the following sections the structure of the knowledge base used by SciMAT is
described and each of its modules is shown.
2) Knowledge base
SciMAT generates a knowledge base from a set of scientific documents, where the
relations of the different entities related with each document (authors, keywords,
journal, references, etc.) are stored. This structure helps the analyst to edit and
preprocess the knowledge base in order to improve the quality of the data and
consequently, obtain better results in the science mapping analysis.
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The knowledge base is composed of sixteen entities. The principal one is the Document
which represents a scientific document (usually, articles, letters, reviews or proceedings
papers). It contains information such as, the title, abstract, doi, citations, etc. The
Document has a variety of information associated with it, such as the authors,
affiliations, keywords, cited references, the journal (or conference), and the publication
year. Each one is considered an entity in the knowledge base.
The Author is the entity that represents the person who has been involved in the
development of a Document. An Author can be associated with a set of Documents, and
in a similar way, a Document has a set of Authors. Furthermore, an Author has an
associated position in his/her Documents.
The Affiliation represents the author's affiliations. Due to the fact that the authors may
work in different places (universities, institutes, etc.) during their research, an Author
has a set of associated Affiliations.
Usually, the scientific documents have a set of keywords associated with them.
Furthermore, depending on the bibliometric database used to retrieve the data, the
documents can contain descriptive words provided by the database. For example, the
ISIWoS adds a set of keywords called ISI Keywords PLUS to each document. In this
sense, the entity Word represents a descriptive term of a document. A set of Words can
appear in different Documents and each Document can have a set of Words. Each Word
can have different roles in the Documents in which it appears. In this way, a document
can have words provided by the authors (author's words), provided by the database
(source's words), or added in the preprocessing step (extracted words).
The entity Reference represents the intellectual base of a scientific document. Similarly
to the Word, a Document has a set of References associated with it, and each Reference
can be present in different Documents. The references can often be divided into small
pieces of information. Depending on the database used to retrieve the data, these pieces
may be different, but some information appears more often, such as the author, journal
and the year. For this reason, there are two entities related to the Reference: the Author-
Reference and the Source-Reference.
Other entities associated with a Document are the Journal and the Publish Date.
Logically, a Document can only have one Journal (or conference) and one Publish Date
associated with it, whereas both entities can have one set of Documents associated.
Moreover, these entities have an associated Subject Category which represents a global
category, often given by the bibliometric database, which classifies the journal in main
knowledge categories. The Journal can be associated with many Subject Categories, and
this relation can change throughout the years.
The entity Period represents a set of (not necessarily disjointed) years. Usually, a set of
Periods are defined to perform a longitudinal science mapping analysis.
We should point out that five of the above described entities can be used as a unit of
analysis in the science mapping analysis carried out by SciMAT: Author, Word,
Reference, Author of Reference and Source of Reference. These entities should be
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- ysy20042015-02-01谢谢分享。 对知识可视化很感兴趣,下来学习学习。
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