Semantic Web Services Integration for Biomedical Applications
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README.md

SCALEUS

Semantic Web Services Integration for Biomedical Applications

Dashboard

Scaleus is a semantic web migration tool designed to be simple to deploy and use. The solution is tailored to help users in the creation of new semantic web applications from scratch. In a single package, we include a high-perfomance triplestore supporting multiple independent datasets, simplified API and services for data integration and management, and a SPARQL query engine, supporting real-time inference mechanisms and optimized text searches over the knowledge base.

Sparql

AngularJS + Jetty Embedded (RESTfull API) + Apache Jena Framework

Download

Main Features:

  • Easy to deploy.
  • Simple RESTfull API for data management.
  • RDFS Inference support over SPARQL queries. Inference rules are also supported.
  • Multiple datasets support.
  • Spreedsheet import (.xlsx, .xls, .ods, etc.).

Documentation

Run

Simple run the application at http://localhost/scaleus/:

java -jar target/scaleus-1.0-jar-with-dependencies.jar

Run in another port:

java -jar target/scaleus-1.0-SNAPSHOT-jar-with-dependencies.jar -p {port}

Run and import data:

java -jar target/scaleus-1.0-SNAPSHOT-jar-with-dependencies.jar -d {dataset_name} -i {file_location}

REST API

List all datasets available:

GET /api/v1/dataset/ HTTP/1.1
Content-Type: application/json

Add dataset:

POST /api/v1/dataset/{dataset} HTTP/1.1

Remove dataset:

DELETE /api/v1/dataset/{dataset} HTTP/1.1

SPARQL endpoint:

GET /api/v1/sparqler/{dataset}/sparql?query={query}&inference={inference}&rules={rules}&format={format} HTTP/1.1
Content-Type: application/json

Sample parameters:

query = SELECT * { ?s ?p ?o } LIMIT 100
inference = true | false
rules = [rule1:  (?x rdfs:subClassOf ?y), (?a rdf:type ?x) -> (?a rdf:type ?y)] [rule2: ... ]
format = json | rdf | ttl | rdf | text | csv

Store triple:

POST /api/v1/store/{dataset} HTTP/1.1
Content-Type: application/json

{
	"s":"http://bioinformatics.ua.pt",
	"p":"http://purl.org/dc/elements/1.1/title",
	"o":"University of Aveiro"
}

Remove triple:

DELETE /api/v1/store/{dataset} HTTP/1.1
Content-Type: application/json

{
	"s":"http://bioinformatics.ua.pt",
	"p":"http://purl.org/dc/elements/1.1/title",
	"o":"University of Aveiro"
}

Add namespace:


POST /api/v1/namespaces/{dataset} HTTP/1.1
Content-Type: application/json

{
  "prefix": "coeus",
  "namespace": "http://bioinformatics.ua.pt/coeus/"
}

Remove namespace:


DELETE /api/v1/namespaces/{dataset}/{prefix} HTTP/1.1
Content-Type: application/json

Get namespaces:

GET /api/v1/namespaces/{dataset} HTTP/1.1
Content-Type: application/json

Get resources matching:

GET /api/v1/resources/{dataset}/{match} HTTP/1.1
Content-Type: application/json

Get properties matching:

GET /api/v1/properties/{dataset}/{match} HTTP/1.1
Content-Type: application/json

Get TTL data:

GET /api/v1/data/{dataset} HTTP/1.1
Content-Type: text/plain

Replace TTL data:

POST /api/v1/data/{dataset} HTTP/1.1
Content-Type: application/x-www-form-urlencoded

@prefix coeus: <http://bioinformatics.ua.pt/coeus/> .
@prefix dc:    <http://purl.org/dc/elements/1.1/> .

coeus:ieeta dc:title "University of Aveiro" .

Describe Resource:

GET /api/v1/resource/{dataset}/{prefix}/{resource}/{format} HTTP/1.1

Sample parameters:

format = json | rdf | ttl | ld 

Python API

scaleus-python

Reference

Please use this reference when citing SCALEUS in your work: