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Guest Talk: Flexible Techniques for Querying RDF Graphs on the Web

Maribel Acosta, PhD 

Date/Time: 26.11.2018, 16:00 

Loca­tion: D2.2.094 


Linked Data initia­tives have encou­raged the publi­ca­tion of RDF data­sets on the web. To support online querying over RDF graphs, web access inter­faces such as SPARQL endpoints or Triple Pattern Frag­ments (TPFs) have been deployed. However, the effi­ci­ency of query engines that consume Linked Data from SPARQL endpoints or TPFs can be nega­tively impacted by the unpre­dic­table data transfer rates and server workload. The problem is mainly gene­rated because SPARQL engines imple­ment the tradi­tional opti­mi­ze-­t­hen-e­xe­cute para­digm where querying stra­te­gies follow a fixed plan. An ortho­gonal but equally important aspect of querying RDF graphs on the web is the quality of the retrieved data. Execu­ting SPARQL queries against graphs with quality issues leads to low-qua­lity and even incom­plete results.

In this talk, I will present flexible querying tech­ni­ques to evaluate queries effi­ci­ently and effec­tively over remote sources. Our proposed solu­tion relies on Adap­tive Query Proces­sing (AQP) to adjust on-t­he-fly the execu­tion sche­du­lers accor­ding to the current condi­tions, as well as on Crowd­sour­cing to complete missing state­ments in the RDF graphs. Our expe­ri­mental results indi­cate that adap­ti­vity speeds up query execu­tion in compa­rison to fixed plans. In addi­tion, we empi­ri­cally show that crowd­sour­cing is a feasible solu­tion for enhan­cing comple­teness of RDF graphs in diffe­rent know­ledge domains.

Finally, this talk will provide insights of open rese­arch direc­tions to support more compre­hen­sive RDF querying solu­tions on the web.


Maribel Acosta holds a PhD from the Insti­tute AIFB in the Karls­ruhe Insti­tute of Tech­no­logy (KIT), where she actually works as Postdoc rese­ar­cher. She is currently focused on rese­ar­ching the enhan­ce­ment of Semantic Web tech­no­lo­gies with human-­based compu­ta­tion, parti­cu­larly applied to SPARQL query execu­tion. Her rese­arch inte­rests also include adap­tive tech­ni­ques for Linked Data manage­ment and federated query proces­sing.

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