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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
'Sciencenet'--towards a global search and share engine for all scientific knowledge.
Dominic S Lütjohann1, Asmi H Shah, Michael P Christen
1Institute of Organic Chemistry, Karlsruhe, Germany.
Bioinformatics (Oxford, England)
|April 16, 2011
Summary
A new distributed search engine, Sciencenet, enables rapid searching across vast, geographically distributed life science datasets. This peer-to-peer platform supports e-Science by allowing users to contribute data and ensures scientific content discovery.
Area of Science:
- Life Sciences
- Bioinformatics
- e-Science
Background:
- Modern biological experiments generate massive, geographically distributed datasets.
- Existing search engine technologies do not adequately address the cross-linking of diverse life science data types.
Purpose of the Study:
- To develop a prototype distributed scientific search engine technology for life sciences.
- To facilitate rapid searching and cross-linking of petabyte-scale datasets and billions of documents.
Main Methods:
- Developed 'Sciencenet', a distributed search engine prototype.
- Implemented a peer-to-peer architecture, bringing the search engine to the data.
- Utilized ASP.NET for the web portal, Python 2.7 for data publishing, and Java 1.6 for the backend search engine.
Main Results:
- Achieved rapid searching over large, distributed life science data spaces.
- Enabled users to contribute to the search index and publish large-scale data.
- Ensured scalability for the science web without performance trade-offs.
Conclusions:
- Sciencenet addresses the need for a unified search solution in life sciences.
- The platform supports e-Science initiatives by facilitating data sharing and discovery.
- A community-driven approach guarantees the relevance and scientific integrity of the indexed content.
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