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Annotations

How to use annotations 


What are they and how are they useful?

Annotations are biological terms or relations, such as diseases, chemicals or protein interactions, which can be highlighted for readers on abstracts and full text articles. These terms are identified by text mining algorithms, developed by a variety of text mining groups.

For readers, annotations make it easier to scan an article and get a quick overview, find key concepts, and discover evidence, such as gene disease associations or molecular interactions. Annotations enable users to locate the primary data in the text by linking text-mined entities to public life sciences and chemistry databases. The goal of annotations is to support scientists and database curators in their literature research by harnessing the power of text mining, and to promote the contribution of text miners to the advancement of science.

What types of annotations are available?

Annotations are provided for:

  • Europe PMC - Database Accessions and Resource names, Gene/Protein names, Organisms, Diseases, Chemicals, Gene Ontology terms and Experimental Methods
  • Metagenomics (EMERALD) - Sample-Material, Body-Site, Host, State, Site, Place, Date, Engineered, Ecoregion, Treatment, Kit, Primer, Gene, LS, LCM, Sequencing
  • ExTRI - Transcription factors-Gene targets
  • IntAct - Protein–protein Interactions
  • PubTator - Gene mutations
  • PheneBank - Cells, Gene mutations, Phenotypes, Molecules, Anatomy, Pathways
  • NaCTEM - Biological events (Phosphorylation)
  • OntoGene - Cells, Cell lines, Clinical drugs, Sequences, Molecular processes, Organ/Tissues
  • Open Targets Platform and DisGeNET - Gene–Disease associations
  • SIB - Gene Function (GeneRIF) statements and COVoc

Using annotations

When viewing an article, a link to 'Annotations' is shown in the tools menu on the right, as shown below.

View key terms

Clicking or tapping on 'Annotations' opens a new panel on the right. Selecting the term in the panel highlights the relevant annotation in the text of the article on the left. Hovering over the highlight opens a popup window.

Highlighted term

The pop-up window displays a link to related database record, the source of the annotation, and the feedback link. In the case of overlapping annotations in a sentence, we highlight the longest annotation, and the individual annotations within the phrase can be seen in the pop-up window.

Use the 'find' and 'arrow' link to the right of the term to find the first, and subsequent instances of the term in the text.

It is of critical importance that readers find the annotations useful. Readers can provide feedback on each annotation, e.g. mark incorrect annotations or endorse useful ones. This information is fed back to the Europe PMC team and will be acted upon, helping to improve the annotations overall. If you find an incorrect annotation, or the annotation is too generic and is highlighted too often, you can report it by clicking or tapping on the highlighted term and using the Feedback link in the pop-up window. You can also endorse annotations using the Feedback link, if they are useful to you.

Provide annotations 


Europe PMC is a community platform, open for contributions that enhance our interaction with scientific literature. The SciLite annotations service enables text miners to showcase their work to the wider public. We welcome contributions from text-mining and other associated communities and encourage them to share annotations on the SciLite annotations platform. Any text-mining group can participate by providing their annotations in a specific format.

Getting started

If you are a text-mining group and can supply annotations in the format we require, please get in contact with us. Annotations may be generated on your own local set up, or a virtual machine on the EBI Embassy Cloud could also be used.

Ground rules

  • Annotations appear on all abstracts, and full text articles with a CC-BY, CC-BY-NC, CC0, CC-BY-SA OR CC-BY-NC-SA license.
  • In the case of overlapping annotations, we highlight the maximum length, and the individual contributors can be seen on the pop-up menu.
  • The reader is in control of which annotations they see, and can provide feedback if they wish.
  • Europe PMC does not make quality judgements on the annotations: this is in the gift of the readers and the wider text-mining community.

Access annotations API 


SciLite annotations data can be accessed programmatically using the new Annotations API. Technical documentation is available. The API will provide annotations on all abstracts and full text articles with a CC-BY, CC-BY-NC or CC0 license or open access. The annotations can be provided to the user in the following formats:

  • JSON
  • XML
  • JSON-LD
  • ID_LIST

The JSON-LD (JSON for Linking Data) format is based on the Web Annotation Data Model recommended by the W3C. This model provides specifications that allows the exchange of annotations across different platforms.

Join the Europe PMC web service users' Google group to receive notifications about annotations API.