arXiv subjects

Dharmen Punjani

Publications and source records attributed to Dharmen Punjani.

4 recordsLinked to original sources

arXiv2021

Template-Based Question Answering over Linked Geospatial Data

Large amounts of geospatial data have been made available recently on the linked open data cloud and the portals of many national cartographic agencies (e.g., OpenStreetMap data, administrative geographies of various countries, or land cover/land use data sets). These datasets use various geospatial vocabularies and can be queried using SPARQL or its OGC-standardized extension GeoSPARQL. In this paper, we go beyond these approaches to offer a question-answering engine for natural language questions on top of linked geospatial data sources. Our system has been implemented as re-usable components of the Frankenstein question answering architecture. We give a detailed description of the system's architecture, its underlying algorithms, and its evaluation using a set of 201 natural language questions. The set of questions is offered to the research community as a gold standard dataset for the comparative evaluation of future geospatial question answering engines.

cs.IR↗

arXiv2019

Towards an Integrated Graph Algebra for Graph Pattern Matching with Gremlin (Extended Version)

Graph data management (also called NoSQL) has revealed beneficial characteristics in terms of flexibility and scalability by differently balancing between query expressivity and schema flexibility. This peculiar advantage has resulted into an unforeseen race of developing new task-specific graph systems, query languages and data models, such as property graphs, key-value, wide column, resource description framework (RDF), etc. Present-day graph query languages are focused towards flexible graph pattern matching (aka sub-graph matching), whereas graph computing frameworks aim towards providing fast parallel (distributed) execution of instructions. The consequence of this rapid growth in the variety of graph-based data management systems has resulted in a lack of standardization. Gremlin, a graph traversal language, and machine provides a common platform for supporting any graph computing system (such as an OLTP graph database or OLAP graph processors). We present a formalization of graph pattern matching for Gremlin queries. We also study, discuss and consolidate various existing graph algebra operators into an integrated graph algebra.

cs.DB↗

arXiv2018

A Stitch in Time Saves Nine -- SPARQL querying of Property Graphs using Gremlin Traversals

Knowledge graphs have become popular over the past years and frequently rely on the Resource Description Framework (RDF) or Property Graphs (PG) as underlying data models. However, the query languages for these two data models -- SPARQL for RDF and Gremlin for property graph traversal -- are lacking interoperability. We present Gremlinator, a novel SPARQL to Gremlin translator. Gremlinator translates SPARQL queries to Gremlin traversals for executing graph pattern matching queries over graph databases. This allows to access and query a wide variety of Graph Data Management Systems (DMS) using the W3C standardized SPARQL query language and avoid the learning curve of a new Graph Query Language. Gremlin is a system-agnostic traversal language covering both OLTP graph database or OLAP graph processors, thus making it a desirable choice for supporting interoperability wrt. querying Graph DMSs. We present a comprehensive empirical evaluation of Gremlinator and demonstrate its validity and applicability by executing SPARQL queries on top of the leading graph stores Neo4J, Sparksee, and Apache TinkerGraph and compare the performance with the RDF stores Virtuoso, 4Store and JenaTDB. Our evaluation demonstrates the substantial performance gain obtained by the Gremlin counterparts of the SPARQL queries, especially for star-shaped and complex queries.

cs.DB↗

arXiv2018

Killing Two Birds with One Stone -- Querying Property Graphs using SPARQL via GREMLINATOR

Knowledge graphs have become popular over the past decade and frequently rely on the Resource Description Framework (RDF) or Property Graph (PG) databases as data models. However, the query languages for these two data models -- SPARQL for RDF and the PG traversal language Gremlin -- are lacking interoperability. We present Gremlinator, the first translator from SPARQL -- the W3C standardized language for RDF -- and Gremlin -- a popular property graph traversal language. Gremlinator translates SPARQL queries to Gremlin path traversals for executing graph pattern matching queries over graph databases. This allows a user, who is well versed in SPARQL, to access and query a wide variety of Graph Data Management Systems (DMSs) avoiding the steep learning curve for adapting to a new Graph Query Language (GQL). Gremlin is a graph computing system-agnostic traversal language (covering both OLTP graph database or OLAP graph processors), making it a desirable choice for supporting interoperability for querying Graph DMSs. Gremlinator currently supports the translation of a subset of SPARQL 1.0, specifically the SPARQL SELECT queries.

cs.DB↗