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PhD Project end-user friendly query languages for temporal and numerical data

End-user friendly query languages for temporal and numerical data

Principal supervisor: Dr Vladislav Ryzhikov

The main motivation behind SPARQL, and many emerging knowledge graph (KG) query languages, is their simplicity for an end-user. This is in contrast with more traditional relational databases, which may have complex schemas. Unfortunately, SPARQL and KG languages are not well-suited for the applications, where the data is a time series data of measurements related to some process (e.g., operation of drilling rig). The focus of this project is to develop an end-user friendly query language for such applications, which, similarly to SPARQL, will be based on concepts and relations. The project will involve identifying the syntax and semantics, as well as implementation and optimisation of the query answering system.

Candidate Requirements:

This PhD is aimed at graduates with a strong interest in database and semantic web technology. Prior experience in one of these areas is desirable.

Key References:

[1] Sebastian Brandt, Elem Güzel Kalayci, Vladislav Ryzhikov, Guohui Xiao, and Michael Zakharyaschev. 2018. Querying log data with metric temporal logic. J. Artif. Int. Res. 62, 1 (May 2018), 829–877. DOI:https://doi.org/10.1613/jair.1.11229

[2] Sebastian Brandt, Diego Calvanese, Elem Güzel Kalayci, Roman Kontchakov, Benjamin Mörzinger, Vladislav Ryzhikov, Guohui Xiao, Michael Zakharyaschev: Two-Dimensional Rule Language for Querying Sensor Log Data: A Framework and Use Cases. TIME 2019: 7:1-7:15

Further details about the project may be obtained from:

Principal supervisor: Dr Vladislav Ryzhikov

Further information about PhDs at CSIS is available via this link.