Posts Tagged ‘Sciverse’
There has been plenty of excitement about publishers opening up their data to be used in new applications. The vision is that new tools will emerge that help researchers in ways that may not have been thought of by publishers and could not easily be provided by publishers themselves.
A Dublin-based startup has developed a way of extracting insight into laboratory instruments and materials from the experimental sections of journal articles (from Elsevier SciVerse).
“I was at a meeting and met a product manager at Elsevier just as they were starting to open up their APIs and we realised that the methods section of papers mentions equipment all the time,’ explained David Kavanagh, the founder. ‘Scientists could benefit from applications using this, but we could also make money from it. It makes sense for scientists and for the companies that supply materials and equipment and it is also scaleable and a value-add for publishers.’
The Scrazzl application pulls all the product information out of a journal paper and organises that information by company. This is supplemented with links to product descriptions and user-generated content such as product reviews. It can also link with inventory control so that a researcher can see that their lab does have a sample of, for example, a particular antibody and in which freezer it is stored.
Read the full article at:
Altmetric tracks tens of thousands of article mentions a month across Twitter, the scientific blogosphere and publishers including The Guardian, the NYT and New Scientist. It assigns scientific papers a score derived from this data. Around 10 – 15% of all new papers added to PubMed each month are covered (Altmetric covers articles not found in PubMed too).
Searching in the SciVerse Hub or on ScienceDirect while the app is active will rank articles by their Almetric score. Relevant information is also shown under the results themselves.
Tap through to see the actual tweets, snippets of blog posts, Mendeley & CiteULike reader counts and links to news sites
Video on Youtube:
Mentioned also by:
Life sciences software provider NextBio, US, has announced the launch of two new applications on the Elsevier SciVerse platform.
The new applications are projected to demonstrate NextBio’s capabilities for searching for relevant text in all types of content at the document, section, paragraph and sentence level.
The two new applications are SearchAssist and Section Search application.
The SearchAssist application leverages NextBio’s auto-complete API and provides auto-complete suggestions composed of terms gathered from diseases, compounds, drugs, anatomy, organisms, genes, biogroups, SNPs (over 18 million), author names (over 6 million) and other biological concepts. It leverages a number of open ontologies including MeSH, Snomed CT, PubChem, DrugBank and Gene Ontology.
The Section Search application decomposes an article into eight sections: Title, Abstract, Introduction, Methods, Results, Discussion, Summary and Captions. A user can search through one or more of these sections to retrieve articles of interest and further filter their results using faceted (Year, Journals, Authors and Affiliations) navigation.
The 2011 annual conference of the NFAIS (National Federation of Advanced Information Services), was dedicated to Information obesity, abundance, overload, tsunami, etc.
Some of the slides are freely available, including those of brilliant speakers like Rafael Sidi (Elsevier Sciverse), Victor Camlek (Springer), Dan Pollock (Nature), etc.
As far as I Know, this is the first published review of the recent Sciverse ScienceDirect.
The author gives an in-depth vision of the product: search facilities, screen shots, resources content, list of improvements, etc.
He reminds the aim of the project: “The aim seems to be not only to create an interface that provides broad functionality on par with other database search tools that many searchers use regularly but also to create an open platform that could be changed to respond effectively to the needs of customers”.
Conclusions of the reviewer are rather positive:
“The image search is a handy feature. The images search allows users to find articles containing images, including tables, in which they are interested. This allows users to not only use those images but also to cite them properly by their article of origin. (…)
SciVerse has its shortcomings, but it is an excellent all-around search tool. (…). by offering advanced keyword searching, citation searching, a very solid image search, strong tools within the list of returns, and an integrated package, Elsevier has made an extremely useful product for the research community.”
Bengtson, Jason (2011). ‘ScienceDirect Through SciVerse: A New Way To Approach Elsevier’, Medical Reference Services Quarterly, 30: 1, 42 — 49
Elsevier announced the integration of Collexis Expert Profiling, into the SciVal suite as SciVal Experts ( www.info.scival.com/experts).
The offering enables institutions to find experts while fostering collaboration within the organization.
SciVal Experts provides institutions with a customizable faculty information system based on content from SciVerse Scopus.
By generating Fingerprints of individual researcher’s expertise and exposing connections among authors, SciVal Experts enables researchers, research administrators and senior leadership to identify experts within and across institutions for all disciplines.
SciVal Experts visualizes network connections within an organization to help facilitate further collaboration and provides links to download publication data for deeper analysis.Press release:
http://www.elsevier.com/wps/find/authored_newsitem.cws_home/companynews05_01791 Commercial pages:
SciVerse, the latest release of Elsevier which is now used by 15 millions of users worlwide, has released a new application de dedicated to improve the search experience.
HealthMash, by Weblib, utilizes proprietary natural language processing and semantic technology tools and resources in order to find highly relevant, reliable and recent health information from the most trusted sources and facilitate focused user exploration and discovery.
- vertical semantic search (Trusted Health Information, MeSH)
- federated search (Health News, Videos, etc.),
- semantic synthesis with mouse-over contexts for exploration and discovery (Related Concepts, Health Concerns, Tests and Treatments),
- and TABLE OF CONTENTS and TOPIC CLUSTERS for drill down in search results and dynamic query modification.
By explicitly identifying facets of particular interest to users: disorders, signs/symptoms, tests and diagnosis, treatments/procedures, drugs and their side effects, interactions/contraindications, and alternative medicine approaches; the user is presented with the most recent, reliable and comprehensive information on their query/topic.