Towards an RDF Analytics Language: Learning from Successful Experiences

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COLD 2013 @ ISWC 2013

Fadi Maali and Stefan Decker

Towards an RDF Analytics Language: Learning from Successful Experiences



A Tale of Two Cities…







Jaql




Jaql




Jaql Jaql



Thesis

Jaql Jaql

There is a need for an analytics

language specifically designed for

large scale RDF data



Data Model

Adoption of “relaxed” versions of the relational data mdeol

Define a data model on top of RDF that works at a more abstract level than individual triples

Observation Challenge



Data Processing Operators

Supporting a subset of relational algebra

Define a subset of SPARQL algebra that is sufficient to address common needs and is amenable to distributed execution




Schema

From rigid schemas to partial or no schemas

Support partial and evolving schema mapping




Programming Paradigm

A shift from pure declarative languages toward hybrid ones

Adopt a hybrid declarative-imperative programming paradigm for RDF processing




In-situ Data Processing

In-place processing has become an important tool for dealing with data

Support in-situ RDF data processing and in-place transformation of non-RDF data




RDF-specific Requirements

Ø  Graph-based data Ø  Inference Ø  HTTP accessibility



Summary

Ø  Data model

Ø  Data processing operators

Ø  Schema restrictions

Ø  Programming paradigm

Ø  In-situ data processing

Technology

Towards an RDF Analytics Language: Learning from Successful Experiences