Qualifying Ontology-Based Visual Query Formulation

Soylu, Ahmet; Giese, Martin

doi:10.1007/978-3-319-26154-6_19

Cited by 8 publications

(11 citation statements)

References 31 publications

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“…OptiqueVQS is composed of communicating widgets (i.e., user-interface mashup) [48,13]. Along with flexibility, modularity, and adaptability, such an approach allow us combine multiple representation and interaction paradigms [49,47].…”

Section: Visual Query Formulationmentioning

confidence: 99%

Ontology Based Data Access in Statoil

Kharlamov

Hovland

Skjæveland

et al. 2017

Journal of Web Semantics

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Ontology Based Data Access (OBDA) is a prominent approach to query databases which uses an ontology to expose data in a conceptually clear manner by abstracting away from the technical schema-level details of the underlying data. The ontology is 'connected' to the data via mappings that allow to automatically translate queries posed over the ontology into data-level queries that can be executed by the underlying database management system. Despite a lot of attention from the research community, there are still few instances of real world industrial use of OBDA systems. In this work we present data access challenges in the data-intensive petroleum company Statoil and our experience in addressing these challenges with OBDA technology. In particular, we have developed a deployment module to create ontologies and mappings from relational databases in a semi-automatic fashion; a query processing module to perform and optimise the process of translating ontological queries into data queries and their execution over either a single DB of federated DBs; and a query formulation module to support query construction for engineers with a limited IT background. Our modules have been integrated in one OBDA system, deployed at Statoil, integrated with Statoil's infrastructure, and evaluated with Statoil's engineers and data.

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Section: Visual Query Formulationmentioning

confidence: 99%

Ontology Based Data Access in Statoil

Kharlamov

Hovland

Skjæveland

et al. 2017

Journal of Web Semantics

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“…Such an approach offers flexibility, modularity, and adaptability and enables us to combine multiple representation paradigms, such as forms, diagrams and icons, and interaction paradigms, such as schema navigation, range selection, and matching [12]. A multi-paradigm approach is important to support different user and task types as stated earlier [46,47].…”

Section: Optiquevqsmentioning

confidence: 99%

“…Since OptiqueVQS is a data retrieval (DR) tool, where a single missing or irrelevant object implies a total failure contrary to information retrieval (IR) [61,5], effectiveness is measured in terms of a binary measure of success (i.e., correct/incorrect query) and efficiency is measured in terms of total time taken to formulate a query [46,47]. The results of the experiment are presented in Table 4.…”

Section: User Studymentioning

confidence: 99%

“…The operational efficiency and effectiveness of business processes rely on domain experts' agility in interpreting data into ac- tionable business information, so as to give reactive and proactive responses with respect to important data patterns appearing in data streams [62]. However, domain experts, who have extensive domain knowledge, may or may not have technical skills and knowledge on databases and formal textual query languages for stream-temporal data sources, such as CQL [3], C-SPARQL [6] and STARQL [36], to specify and extract data of interest [46]. Therefore, centralised approaches are often preferred.…”

Section: Introductionmentioning

confidence: 99%

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Querying industrial stream-temporal data: An ontology-based visual approach1

Soylu

Giese

Schlatte

et al. 2017

AIS

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Abstract. An increasing number of sensors are being deployed in business-critical environments, systems, and equipment; and stream a vast amount of data. The operational efficiency and effectiveness of business processes rely on domain experts' agility in interpreting data into actionable business information. A domain expert has extensive domain knowledge but not necessarily skills and knowledge on databases and formal query languages. Therefore, centralised approaches are often preferred. These require IT experts to translate the information needs of domain experts into extract-transform-load (ETL) processes in order to extract and integrate data and then let domain experts apply predefined analytics. Since such a workflow is too time intensive, heavy-weight and inflexible given the high volume and velocity of data, domain experts need to extract and analyse the data of interest directly. Ontologies, i.e., semantically rich conceptual domain models, present an intelligible solution by describing the domain of interest on a higher level of abstraction closer to the reality. Moreover, recent ontology-based data access (OBDA) technologies enable end users to formulate their information needs into queries using a set of terms defined in an ontology. Ontological queries could then be translated into SQL or some other database query languages, and executed over the data in its original place and format automatically. To this end, this article reports an ontology-based visual query system (VQS), namely OptiqueVQS, how it is extended for a stream-temporal query language called STARQL, a user experiment with the domain experts at Siemens AG, and STARQL's query answering performance over a proof of concept implementation for PostgreSQL.

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“…(iii) Task synopsis: Domain experts' information needs are often structurally complex, requiring to join multiple relations. We have conducted a literature survey [85,86] to identify best practices and design patterns. The survey revealed that a multi-paradigm design combining multiple representation and interaction paradigms is key to address a broad range of user groups having frequent, unpredicted and sophisticated information needs [71,87].…”

Section: Visual Query Formulationmentioning

confidence: 99%

Semantic access to streaming and static data at Siemens

Kharlamov

Mailis

Mehdi

et al. 2017

Journal of Web Semantics

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We present a description and analysis of the data access challenge in Siemens Energy. We advocate Ontology Based Data Access (OBDA) as a suitable Semantic Web driven technology to address the challenge. We derive requirements for applying OBDA in Siemens, review existing OBDA systems and discuss their limitations with respect to the Siemens requirements. We then introduce the Optique platform as a suitable OBDA solution for Siemens. The platform is based on a number of novel techniques and components including a deployment module, BootOX for ontology and mapping bootstrapping, a query language STARQL that allows for a uniform querying of both streaming and static data, a highly optimised backend, ExaStream, for processing such data, and a query formulation interface, OptiqueVQS, that allows to formulate STARQL queries without prior knowledge of its formal syntax. Finally, we describe our installation and evaluation of the platform in Siemens.

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Qualifying Ontology-Based Visual Query Formulation

Cited by 8 publications

References 31 publications

Ontology Based Data Access in Statoil

Ontology Based Data Access in Statoil

Querying industrial stream-temporal data: An ontology-based visual approach1

Semantic access to streaming and static data at Siemens

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