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on page 1 showing 20 out of 127 results

Cite this (Academia.edu, RRID:SCR_000080)

URL: http://www.academia.edu/

Resource Type: Resource, portal, community building portal, data or information resource

Social networking site for academic researchers that allows researchers to share papers, find people working in a field and see analytics on papers etc

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Cite this (Acumen Consortium, RRID:SCR_006599)

URL: http://research-acumen.eu/

Resource Type: Resource, organization portal, portal, data or information resource

European research collaboration aimed at understanding the ways in which researchers are evaluated by their peers and by institutions, and at assessing how the science system can be improved and enhanced. This FP7 project is a cooperation among nine European research institutes with Professor Paul Wouters (CWTS ?????? Leiden University) as principal investigator.

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Cite this (Adobe FormsCentral, RRID:SCR_001729)

URL: https://www.acrobat.com/formscentral/en/

Resource Type: Resource, service resource, commercial organization

Service to create PDF and web forms.

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Cite this (Altmetric API, RRID:SCR_001736)

URL: http://www.altmetric.com/api.php

Resource Type: Resource, software resource, application programming interface, data access protocol

Application programming interface that gives one programmatic access to the article level metrics data associated with articles and datasets collected by Altmetric. It extracts, disambiguates and collates mentions of scholarly works online, allowing one to focus on one's core product.

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Cite this (Altmetric Badges, RRID:SCR_002558)

URL: http://www.altmetric.com/badges.php

Resource Type: Resource, commercial organization

A single line of code to add your article pages to include the Altmetric score and donut graphic on your own site with minimal technical effort. Choose from an array of different badge styles, including the colourful and iconic Altmetric donut. Implement article level metrics into your pages in minutes. Their pricing is based on the number of journals you want covered, with significant discounts for larger portfolios. You can try out the badges for free and without any commitment - however, your visitors will only see a subset of activity for each article when they click through. See the technical documentation for details.

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Cite this (Altmetric Bookmarklet, RRID:SCR_000427)

URL: http://www.altmetric.com/bookmarklet.php

Resource Type: Resource, software resource

Free bookmarklet for Chrome, Firefox and Safari that allows you to instantly get article level metrics for any recent paper. Simply drag the button below to your bookmarks bar, navigate to a journal article page, and hit Altmetric it!

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Cite this (Altmetric Explorer, RRID:SCR_000428)

URL: http://www.altmetric.com/aboutexplorer.php

Resource Type: Resource, service resource, commercial organization

Service to monitor, search and measure conversations about your publications and those of your competitors captured by Altmetric including tweets, blog posts, news stories and other content that mention scholarly articles. Use the Explorer to deliver insights, track mentions and measure levels of attention over time.

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Cite this (AlzSWAN Knowledge Base, RRID:SCR_003017)

URL: http://hypothesis.alzforum.org/

Resource Type: Resource, portal, knowledge environment, community building portal, knowledgebase, data or information resource

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A community-driven knowledgebase of Alzheimer disease, in which researchers can annotate scientific claims, data, and information, putting these into the context of testable hypotheses and treatment discovery. This SWAN project adds a collection of hand-curated hypotheses to a research paper, which are then related through a set of discourse relationships. They can be browsed and relations between claims, as well as support networks for a specific claim, are made and visualized. AlzSWAN is where you explore scientific knowledge about Alzheimer disease and share your own ideas, comments and questions in a semantically structured system. AlzSWAN is enabled by Semantic Web technology, a new standard for knowledge organization and transfer on the Web. AlzSWAN organizes and manages knowledge using formal knowledge descriptions called ontologies. Using these formal knowledge descriptions, they can tie statements made in scientific publications or on the Web to scientific evidence, biological terminologies, and knowledgebases, and to claims and counterclaims made by other researchers.

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Cite this (A modular structure for scientific articles in an electronic environment, RRID:SCR_002451)

URL: http://www.science.uva.nl/projects/commphys/papers/thesisfh/Front.html

Resource Type: Resource, narrative resource, thesis, data or information resource

This thesis proposes a modular form for Physics papers: by investigating a collection of papers, a more fine-grained structure for science papers and an extensive relationships taxonomy is proposed. Examples of modular articles are included.

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Cite this (A.nnotate, RRID:SCR_002839)

URL: http://a.nnotate.com/

Resource Type: Resource, software resource, service resource, commercial organization, storage service resource

An online annotation, collaboration and indexing system for documents and images, supporting PDF and MS Office formats. Instead of emailing different versions of a document back and forth you can all comment on a single read-only copy online. Unlike online word processors, the document is displayed in high quality with fonts and layout just like the printed version. It is easy to use and runs in all common web browsers, with no software or plugins to install. Hosted solutions are available for individuals and workgroups. For enterprise users the full system is available for local installation. Special discounts apply for educational use. The FREE hosted solution offers single-user accounts for uploading up to 30 pages per month. Documents can be shared with any number of annotators.

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Cite this (Annotation Ontology, RRID:SCR_002862)

URL: http://code.google.com/p/annotation-ontology/

Resource Type: Resource, ontology, data or information resource, controlled vocabulary

A vocabulary for performing several types of annotation - comment, entities annotation (or semantic tags), textual annotation (classic tags), notes, examples, erratum... - on any kind of electronic document (text, images, audio, tables...) and document parts. AO is not providing any domain ontology but it is fostering the reuse of the existing ones for not breaking the principle of scalability of the Semantic Web.

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Cite this (AQnowledge Bookmarklet, RRID:SCR_002501)

URL: http://aqnowledge.com/aqnowledge-semantic-knowledge-navigation-overview.html

Resource Type: Resource, software resource

Bookmarklet suitable for all main browsers, that, when invoked, highlights concepts of scientific significance in text and offers links to many open information resources about any concept highlighted.

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Cite this (Argumentative Zoning: Information Extraction from Scientific Articles, RRID:SCR_006303)

URL: http://www.cl.cam.ac.uk/~sht25/az.html

Resource Type: Resource, narrative resource, thesis, data or information resource

Simone Teufel''s thesis introducing a rhetorical-level analysis of scientific research articles called Argumentative Zoning that aims to provide an intelligent library search tool for researchers. This could include the summarization of single or multiple articles, and also improved citation indexes. A construct called a citation maps could help people grasp relationships between papers. The definition of the argumentative Zones is given by the sentential-rhetorical speech act of single, important sentences (landmark sentences, e.g. in the paper they develop a method for or in contrast to REFERENCE, their approach uses ...). That means, she is particularly interested in the rhetorical status of that sentence with respect to the communicative function of the whole paper. The zones, each associated with one or more sentences, are the following: * BKG: General scientific background (yellow) * OTH: Neutral descriptions of other people''s work (orange) * OWN: Neutral descriptions of the own, new work (blue) * AIM: Statements of the particular aim of the current paper (pink) * TXT: Statements of textual organization of the current paper (in chapter 1, we introduce...) (red) * CTR: Contrastive or comparative statements about other work; explicit mention of weaknesses of other work (green) * BAS: Statements that own work is based on other work (purple) The thesis looks at how humans perform the analysis, how much they agree or disagree (they agree pretty much!) and how an automatic, rather shallow process can apply the analysis, based on machine learning and sentential features.

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Cite this (aTag Generator, RRID:SCR_000801)

URL: http://hcls.deri.org/atag/generator/

Resource Type: Resource, software resource

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 13, 2012. Snippets of HTML that capture the information that is most important in a machine-readable, interlinked format, making it easier to see the big picture. aTags work with any Web text and can store and connect any textual element that is highlighted in a browser. The structure of the embedded RDF/OWL is decidedly simple: a very short piece of human-readable text that is "tagged" with relevant ontological entities. An aTag generator can be easily added to any web browser and allows researchers to quickly generate aTags out of key statements from web pages, such as PubMed abstracts. The resulting aTags can be embedded anywhere on the web, for example on blogs, wikis, or biomedical databases. aTag demonstrates how the resulting statements that are distributed over the web can be searched, visualized and aggregated with Semantic Web / Linked Data tools, and discusses how aTags can be used to answer practically relevant biomedical questions even though their structure is very simple. aTags are based on Semantic Web standards and Linked Data practices. Specifically, they make use of RDFa, the SIOC vocabulary and various domain ontologies and taxonomies that are available in RDF/OWL format. The autocomplete functionality is based on Apache Solr. Reference: Simple, ontology-based representation of biomedical statements through fine-granular entity tagging and new web standards Matthias Samwald and Holger Stenzhorn. Bio-Ontologies 2009.

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    Authorea

Cite this (Authorea, RRID:SCR_002547)

URL: https://www.authorea.com/

Resource Type: Resource, software resource, software application, commercial organization, authoring tool

Online word processor for scientific and scholarly papers. Write, share, cite, comment, export, and track changes of articles in one place.

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Cite this (Bamboo DiRT, RRID:SCR_002556)

URL: http://dirt.projectbamboo.org/

Resource Type: Resource, data or information resource, database

Registry of digital research tools for scholarly use that makes it easy for digital humanists and others conducting digital research to find and compare resources ranging from content management systems to music OCR, statistical analysis packages to mindmapping software.

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Cite this (BioCreative, RRID:SCR_006311)

URL: http://biocreative.sourceforge.net/

Resource Type: Resource, topical portal, challenge, benchmark, data set, portal, data or information resource

Community-wide effort (Challenge) for evaluating text mining and information extraction systems applied to the biological domain. It is focused on the comparison of methods and the community assessment of scientific progress, rather than on the purely competitive aspects. There is a considerable difficulty in constructing suitable gold standard data for training and testing new information extraction systems which handle life science literature. Thus the data sets derived from the BioCreAtIvE challenge - because they have been examined by biological database curators and domain experts - serve as useful resources for the development of new applications as well as helping to improve existing ones. Two main issues are addressed at BioCreAtIvE, both concerned with the extraction of biologically relevant and useful information from the literature. The first one is concerned with the detection of biologically significant entities (names) such as gene and protein names and their association to existing database entries. The second one is concerned with the detection of entity-fact associations (e.g. protein - functional term associations ).

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Cite this (Bio-Formats, RRID:SCR_000450)

URL: https://www.openmicroscopy.org/site/products/bio-formats

Resource Type: Resource, data processing software, software library, software application, software resource, software toolkit, image processing software

A standalone Java library for reading microscopy image data files in any format and writing image data using standardized, open formats. It currently reads and converts more than 120 file formats to the OME-TIFF data standard. (Dec. 2013)

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Cite this (BioLexicon, RRID:SCR_000589)

URL: http://www.nactem.ac.uk/biolexicon/

Resource Type: Resource, data or information resource, database

A large-scale English terminological database that contains over 2.2.M lexical entries (3.3M semantic relations), terminological variants and rich linguistic information (subcategorization frames) which supports text mining systems. It is primarily intended to support text mining and information retrieval in the biomedical domain. The BioLexicon provides specific information to help determine the relevant facts to be extracted. BioLexicon is available in a relational database format (MySQL dump format) and it adheres to the EAGLES/ISO standards for lexical resources.

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    Biotea

Cite this (Biotea, RRID:SCR_006285)

URL: http://biotea.idiginfo.org/

Resource Type: Resource, data set, web service, software resource, data access protocol, data or information resource

Access to semantically processed full-text of the open-access subset of PubMed Central. The RDF model and resulting dataset make extensive reuse of existing ontologies and semantic enrichment services. The entire enriched data set is available for download or via REST services. A SPARQL query interface to 10,000 enriched articles is available. The entire collection of RDF documents is available for download as a collection of ZIP files. Each document consists of three RDF files serialized as XML.

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