These data services are a REST based service to access NIF data and are defined by a WADL file (http://wadl.java.net/) which allows clients to automatically generate code for these services.
The publicly accessible server for the NIF data services is nif-services.neuinfo.org. The WADL urls for the services respectively are: http://nif-services.neuinfo.org/servicesv1/application.wadl
Documentation specific to each service can be viewed here: http://nif-services.neuinfo.org/servicesv1/
All services are subject to change at any time.
The services include the ability to:
Retrieve a federation summary, e.g., http://nif-services.neuinfo.org/servicesv1/v1/summary?q=*
Retrieve data records from a NIF federation source for a search,
Retrieve registry data records from NIF, e.g., http://nif-services.neuinfo.org/servicesv1/v1/federation/data/nlx_144509-1?q=miame
Retrieve a complete search summary, e.g., http://nif-services.neuinfo.org/servicesv1/v1/federation/search?q=cortex
Retrieve NIF auto-complete suggestions, e.g., http://nif-services.neuinfo.org/servicesv1/v1/vocabulary?prefix=hippo
Use the NIF annotator for arbitrary text, e.g., http://nif-services.neuinfo.org/servicesv1/v1/annotate?content=The%20cerebellum%20is%20a%20wonderful%20thing
To access data suitable for "display" (formatted with HTML) for any NIF source you can use the following formats (json, jsonp, xml, or csv):
To access the raw data supporting each display (no HTML formatting and potentially unhelpful column names) you can update the exportType parameter:
To access both the HTML and raw data in a single call:
To use the FIND command (e.g., find:molecule test):
Strict search url construction for terms that you would like to expand to synonyms
Search for terms that you would not like to expand to synonyms. Note, this works with queries that you would like to use specified Boolean operators with (OR NOT AND)
Retrieve LinkOuts per PMID: http://disco.neuinfo.org/webportal/WebServices/REST/DISCOInfo/getResourceLinkOutData/20878786
LDA Pipeline - statistical analysis of topics based on paper abstracts (accepts as many &pmid= elements as needed, for best results use your own papers and set the number of topics to a number less than the number of papers)
- the output is xml, and it classifies topics per paper, then total topic terms. For some reason the first topic is labeled Topic 0. This version of implementation runs through the stemming library, but not the ontology.
More like this by PMID search (different algorithm for similarity):
http://nif-services.neuinfo.org/servicesv1/v1/literature/moreLikePmid?pmid=2797545&pmid=18637315&pmid=15574605&pmid=16270700&pmid=12949310&pmid=2747212&pmid=700458&pmid=10778103&pmid=7368378&pmid=12437142&pmid=2570336 supports filters (&yearFilter=2011)
Reconcile service for use with Google Refine