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Sefarad is an environment developed to explore, analyse and visualize data.


Sefarad environment is divided in modules, each one is focused in one concrete task:

  • Visualisation, the main function of this module is to represent data which were processed and draw different charts to visualize interesting data. This visualisation is structured in several dashboards, which are web pages oriented to display all the collected information . In addition, these dashboards are divided in other components (Polymer Web Components) that globally compound the dashboard itself.
  • ElasticSearch, represents the persistence layer of the project and stores all the amount of data needed for the visualisation.


As shown in the architecture, Serafad is also capable to retrieve semantic data from external sources, such as Fuseki or DBPedia.


Sefarad framework has multiple predefined dashboards which are ready to be used. Due to its high flexibility, it enables to display any kind of information, either user custom data sets or others included by default in the project.

In this section we are going to explain each dashboard, detailing most user-attractive functionalities using a predefined dataset and presenting the real value of the tool, so anyone can use Sefarad framework by applying their customized data.

Due to the modular architecture offered by Sefarad framework, each dashboard has its own structure regardless, being able to interact with the components without influecing the rest. Moreover we are going to focus on explain what can be done in every dashboard through a case study without deepening inside its internal behaviour.


DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data.

This dashboard provides a graphic interface to ask SPARQL queries against DBpedia.



TourPedia is the result of an European project. It is a demo of OpenNER (Open Polarity Enhanced Name Entity Recognition). It contains information about accommodations, restaurants, points of interest and attractions of different places in Europe.

TourPedia provides two main datasets: Places and Reviews. Each place contains useful information such as the name, the address and its URI to Facebook, Foursquare, GooglePlaces and Booking. Reviews contain also some useful details ready for us to exploit.

This dashboard also allows you to ask SPARQL quereies against our TourPedia database.


Financial Twitter Tracker

Financial Twitter Tracker is an R&D project of GSI Group that contains information about people talking about brands in social media like Twitter, Facebook, and more…

This dashboard provides interactive Web Components to visualize people’s opinion polarities and also has a SPARQL editor to ask queries about these opinions using RDF specifications.



Footballmood is an application developed for sentiment analysis of football in Twitter. This dashboard provides interactive Web Components to visualize people’s opinion polarities and also has a SPARQL editor to ask queries about football players against DBpedia.



Aspects dashboard is an analyser developed for aspects sentiment analysis of restaurant reviews. This is the result of analysis showed on a dashboard based on web components and D3.js. To view your data you can use widgets and visualize it through them.

The data used for the dashboard is the Semeval 2015 ABSA dataset (Task 12) for restaurant domain, available here