Martin G. Skjæveland

Sgvizler: A JavaScript Wrapper for Easy Visualization of SPARQL Result Sets

Sgvizler is a small JavaScript wrapper for visualization of SPARQL results sets. It integrates well with HTML web pages by letting the user specify SPARQL SELECT queries directly into designated HTML elements, which are rendered to contain the specified visualization type on page load or on function call. Sgvizler supports a vast number of visualization types, most notably all of the major charts available in the Google Chart Tools, but also by allowing users to easily modify and extend the set of rendering functions, e.g., specified using direct DOM manipulation or external JavaScript visualization tool-kits. Sgvizler is compatible with all modern web browsers.

Publishing the Norwegian Petroleum Directorate's FactPages as Semantic Web Data

This paper motivates, documents and evaluates the process and results of converting the Norwegian Petroleum Directorates FactPages, a well-known and diverse set of tabular data, but with little and incomplete schema information, stepwise into other representations where in each step more semantics is added to the dataset. The different representations we consider are a regular relational database, a linked open data dataset, and an ontology. For each conversion step we explain and discuss necessary design choices which are due to the specific shape of the dataset, but also those due to the characteristics and idiosyncrasies of the representation formats. We additionally evaluate the output, performance and cost of querying the different formats using questions provided by users of the FactPages.

BootOX: Practical Mapping of RDBs to OWL 2

Ontologies have recently became a popular mechanism to expose relational database RDBs due to their ability to describe the domain of data in terms of classes and properties that are clear to domain experts. Ontological terms are related to the schema of the underlying databases with the help of mappings, i.e., declarative specifications associating SQL queries to ontological terms. Developing appropriate ontologies and mappings for given RDBs is a challenging and time consuming task. In this work we present BootOX, a system that aims at facilitating ontology and mapping development by their automatic extraction i.e., bootstrapping from RDBs, and our experience with the use of BootOX in industrial and research contexts. BootOX has a number of advantages: it allows to control the OWL 2 profile of the output ontologies, bootstrap complex and provenance mappings, which are beyond the W3C direct mapping specification. Moreover, BootOX allows to import pre-existing ontologies via alignment.

RODI: A Benchmark for Automatic Mapping Generation in Relational-to-Ontology Data Integration

A major challenge in information management today is the integration of huge amounts of data distributed across multiple data sources. A suggested approach to this problem is ontology-based data integration where legacy data systems are integrated via a common ontology that represents a unified global view over all data sources. However, data is often not natively born using these ontologies. Instead, much data resides in legacy relational databases. Therefore, mappings that relate the legacy relational data sources to the ontology need to be constructed. Recent techniques and systems that automatically construct such mappings have been developed. The quality metrics of these systems are, however, often only based on self-designed benchmarks. This paper introduces a new publicly available benchmarking suite called RODI, which is designed to cover a wide range of mapping challenges in Relational-to-Ontology Data Integration scenarios. RODI provides a set of different relational data sources and ontologies representing a wide range of mapping challenges as well as a scoring function with which the performance of relational-to-ontology mapping construction systems may be evaluated.

A Preliminary Approach on Ontology-Based Visual Query Formulation for Big Data

Data access in an enterprise setting is a determining factor for the potential of value creation processes such as sense-making, decision making, and intelligence analysis. As such, providing friendly data access tools that directly engage domain experts (i.e., end-users) with data, as opposed to the situations where database/IT experts are required to extract data from databases, could substantially increase competitiveness and profitability. However, the ever increasing volume, complexity, velocity, and variety of data, known as the Big Data phenomenon, renders the end-user data access problem even more challenging. Optique, an ongoing European project with a strong industrial perspective, aims to countervail the Big Data effect, and to enable scalable end-user data access to traditional relational databases by using an ontology-based approach. In this paper, we specifically present the preliminary design and development of our ontology-based visual query system and discuss directions for addressing the Big Data effect.

Engineering ontology-based access to real-world data sources

The preparation of existing real-world datasets for publication as high-quality semantic web data is a complex task that requires the concerted execution of a variety of processing steps using a range of different tools. Faced with both changing input data and evolving requirements on the produced output, we face a significant engineering task for schema and data transformation. We argue that to achieve a robust and flexible transformation process, a high-level declarative description is needed, that can be used to drive the entire tool chain. We have implemented this idea for the deployment of ontology-based data access (OBDA) solutions, where semantically annotated views that integrate multiple data sources on different formats are created, based on an ontology and a collection of mappings. Furthermore, we exemplify our approach and show how a single declarative description helps to orchestrate a complete tool chain, beginning with the download of datasets, and through to the installation of the datasets for a variety of tool applications, including data and query transformation processes and reasoning services. Our case study is based on several publicly available tabular and relational datasets concerning the operations of the petroleum industry in Norway. We include a discussion of the relative performance of the used tools on our case study, and an overview of lessons learnt for practical deployment of OBDA on real-world datasets.

RODI: Benchmarking relational-to-ontology mapping generation quality

Accessing and utilizing enterprise or Web data that is scattered across multiple data sources is an important task for both applications and users. Ontology-based data integration, where an ontology mediates between the raw data and its consumers, is a promising approach to facilitate such scenarios. This approach crucially relies on useful mappings to relate the ontology and the data, the latter being typically stored in relational databases. A number of systems to support the construction of such mappings have recently been developed. A generic and effective benchmark for reliable and comparable evaluation of the practical utility of such systems would make an important contribution to the development of ontology-based data integration systems and their application in practice. We have proposed such a benchmark, called RODI. In this paper, we present a new version of RODI, which significantly extends our previous benchmark, and we evaluate various systems with it. RODI includes test scenarios from the domains of scientific conferences, geographical data, and oil and gas exploration. Scenarios are constituted of databases, ontologies, and queries to test expected results. Systems that compute relational-to-ontology mappings can be evaluated using RODI by checking how well they can handle various features of relational schemas and ontologies, and how well the computed mappings work for query answering. Using RODI, we conducted a comprehensive evaluation of seven systems.

Preserving information content in RDF using bounded homomorphisms

The topic of study in the present paper is the class of RDF homomorphisms that substitute one predicate for another throughout a set of RDF triples, on the condition that the predicate in question is not also a subject or object. These maps turn out to be suitable for reasoning about similarities in information content between two or more RDF graphs. As such they are very useful e.g. for migrating data from one RDF vocabulary to another. In this paper we address a particular instance of this problem and try to provide an answer to the question of when we are licensed to say that data is being transformed, reused or merged in a non-distortive manner. We place this problem in the context of RDF and Linked Data, and study the problem in relation to SPARQL construct queries.

Ontology-Based Data Access to Slegge

We report on our experience in ontology-based data access to the Slegge database at Statoil and share the resources employed in this use case: end-user information needs (in natural language), their translations into SPARQL, the Subsurface Exploration Ontology, the schema of the Slegge database with integrity constraints, and the mappings connecting the ontology and the schema.

Practical Ontology Pattern Instantiation, Discovery, and Maintenance with Reasonable Ontology Templates

Reasonable Ontology Templates ( Open image in new window ) is a language for representing ontology modelling patterns in the form of parameterised ontologies. Ontology templates are simple and powerful abstractions useful for constructing, interacting with, and maintaining ontologies. With ontology templates, modelling patterns can be uniquely identified and encapsulated, broken down into convenient and manageable pieces, instantiated, and used as queries. Formal relations defined over templates support sophisticated maintenance tasks for sets of templates, such as revealing redundancies and suggesting new templates for representing implicit patterns. Ontology templates are designed for practical use; an Open image in new window vocabulary, convenient serialisation formats for the semantic web and for terse specification of template definitions and bulk instances are available, including an open source implementation for using templates. Our approach is successfully tested on a real-world large-scale ontology in the engineering domain.