Industry Relevance of the Semantic Publishing Benchmark
Why do leading media companies, like the BBC and publishers, from FT to DK and Elsevier, use triplestores?
Atanas Kiryakov, Ontotext
OWL-empowered SPARQL Query Optimization
The Linked Data paradigm has become the prominent enabler for sharing huge volumes of data using Semantic Web technologies, and has created novel challenges for non-relational data management systems, such as RDF and graph engines. Efficient data access through queries is perhaps the most important data management task, and is enabled through query optimization techniques, which amount to the discovery of optimal or close to optimal execution plans for a given query.
GRADES2015 - deadline March 11
At SIGMOD 2015, the third international workshop on Graph Datamagement Experience and Systems (GRADES2015) will be organized.
See: http://event.cwi.nl/grades2015
GRADES since its inception has been one of the best attended workshops at SIGMOD, and papers published in it are getting noted.
LDBC is a co-sponsor of the GRADES workshops and is being led this year by Tedd Willke (Intel Corp.) and Josep Lluis Larriba Pey (LDBC coordinator).
The workshop will be held on Sunday May 31, in Melbourne, Australia.
Person activity subgraph features in LDBC DATAGEN
When talking about DATAGEN and other graph generators with social network characteristics, our attention is typically borrowed by the friendship subgraph and/or its structure. However, a social graph is more than a bunch of people being connected by friendship relations, but has a lot more of other things is worth to look at. With a quick view to commercial social networks like Facebook, Twitter or Google+, one can easily identify a lot of other elements such as text images or even video assets. More importantly, all these elements form other subgraphs within the social network!
6th LDBC Technical User Community meeting
The LDBC consortium are pleased to announce its Sixth Technical User Community (TUC) meeting.
This will be a two-day event at Universitat Politècnica de Catalunya, Barcelona on Thursday and Friday March 19/20, 2015.
The LDBC FP7 EC funded project is reaching its finalisation, and this will be the last event sponsored directly by the project. However, tasks within LDBC will continue based on the LDBC independent organisation. The event will basically set the following aspects:
5th LDBC TUC meeting
The 5th LDBC Technical User Community (TUC) meeting took place in Athens on 14.11.2014 being well attended by both Graph and RDF databases industry and academia. In the morning session, members of the LDBC project gave an update on the status of the project and its benchmarks:
SNB Driver - Part 3: Workload Execution - Putting it all together
Up until now we have introduced the challenges faced when executing the LDBC SNB benchmark, as well as explained how some of these are overcome. With the foundations laid, we can now explain precisely how operations are executed.
SNB Driver - Part 2: Tracking Dependencies Between Queries
The SNB Driver part 1 post introduced, broadly, the challenges faced when developing a workload driver for the LDBC SNB benchmark. In this blog we'll drill down deeper into the details of what it means to execute "dependent queries" during benchmark execution, and how this is handled in the driver. First of all, as many driver-specific terms will be used, below is a listing of their definitions. There is no need to read them in detail, it is just there to serve as a point of reference.
Definitions
Running the Semantic Publishing Benchmark on Sesame, a Step-by-Step Guide
Until now we have discussed several aspects of the Semantic Publishing Benchmark (SPB) such as the difference in performance between virtual and real servers configuration
Semantic Publishing Instance Matching Benchmark
The Semantic Publishing Instance Matching Benchmark (SPIMBench) is a novel benchmark for the assessment of instance matching techniques for RDF data with an associated schema. SPIMBench extends the state-of-the art instance matching benchmarks for RDF data in three main aspects: it allows for systematic scalability testing, supports a wider range of test cases including semantics-aware ones, and provides an enriched gold standard.