In a previous blog post I have discussed the power of SPARQL to go beyond data retrieval to analytics. Here I look into the possibilities to implement a product recommender all in SPARQL. Products are considered to be similar if they share relevant characteristics, and the higher the overlap the higher the similarity. In the case of movies or TV programs there are static characteristics (e.g. genre, actors, director) and dynamic ones like viewing patterns of the audience.
The static part of this we can look up in resources like the DBpedia. If we look at the data related to the resource <http://dbpedia.org/resource/Friends> (that represents the TV show “Friends”) we can use for example the associated subjects (see predicate dcterms:subject). In this case[read more]
The ADEQUATe project builds on two observations: An increasing amount of Open Data becomes available as an important resource for emerging businesses and furtheron the integration of such open, freely re-usable data sources into organisations’ data warehouse and data management systems is seen as a key success factor for competitive advantages in a data-driven economy.
The project now identifies crucial issues which have to be tackled to fully exploit the value of open data and the efficient integration with other data sources:
Semantic Web Company and its PoolParty team are participating in the H2020 funded project ALIGNED. This project evaluates software engineering and data engineering processes in the context of how this both worlds can be aligned in an efficient way. All project partners are working on several use cases, which shall result in a set of detailed requirements for combined software and data engineering. The ALIGNED project framework also includes work and research on data consistency in PoolParty Thesaurus Server (PPT).ALIGNED: Describing, finding and repairing inconsistencies in RDF data sets
When using RDF to represent the data model of applications, inconsistencies can occur. Compared with the schema approach of relational databases, a data model using RDF offers much more[read more]
You have always thought that SPARQL is only a query language for RDF data? Then think again, because SPARQL can also be used to implement some cool analytics. I show here two queries that demonstrate that principle.
The query shown here starts from the class dbp:Athlete and retrieves sub classes thereof that cover different sports. With that athletes of that areas are obtained and their birth and death dates (i.e. we only take into account deceased individuals). From the dates the years are extracted. Here a regular expression is used[read more]