E ective, collaborative integration of software and big data engineering for Web-scale systems, is now a crucial technical and economic challenge. This requires new combined data and software engineering processes and tools. Semantic metadata standards and linked data principles, provide a technical grounding for such integrated systems given an appropriate model of the domain. In this paper we introduce the ALIGNED suite of ontologies speci cally designed to model the information exchange needs of combined software and data engineering. The models have been deployed to enable: tool-chain integration, such as the exchange of data quality reports; cross-domain communication, such as interlinked data and software unit testing; mediation of the system design process through the capture of design intents and as a source of context for model-driven software engineering processes. These ontologies are deployed in web-scale, data-intensive, system development environments in both the commercial and academic domains. We exemplify the usage of the suite on a complex collaborative software and data engineering scenario from the legal information system domain.
This paper has been accepted in the ISWC 2016 Resources track. Recent years have seen a signi cant increase in the demand for data-intensive applications. However our engineering techniques for building data-intensive systems are both immature and often partitioned into software engineering and data engineering processes, tasks or teams. The expressivity of semantic models makes them useful for both addressing data quality [2] and applying model-driven approaches to software engineering. Semantic data, in the form of enterprise linked data is also useful for describing, fusing and managing the combined data and software engineering lifecycles to increase productivity, agility and system quality.
In this paper, we present a suite of ontologies developed within the ALIGNED5
project, that aim to align the divergent processes encapsulating data and
software engineering. The key aim of the ALIGNED ontology suite is to support
the generation of combined software and data engineering processes and tools
for improved productivity, agility and quality. The suite contains linked data
ontologies/vocabularies designed to: (
This ontology suite has been deployed for validation and incremental improvement in the ALIGNED project on four, large-scale data-intensive systems engineering use cases: the Seshat Global History Databank which is compiling linked data time series relating to all human societies over the past 12,000 years; JURION7, a legal information platform developed by Wolters Kluwer Germany; PoolParty8, a semantic technology middleware developed by the Semantic Web Company; and the DBpedia+9 data quality and release processes.
The paper is structured as follows: Section 2 presents an overview of the ALIGNED suite. It provides a brief description of the core ontologies in the suite.Section 3 presents an evaluation of the ontologies in the suite. Finally, Section 4 presents conclusions. 2
Figure 1 illustrates the ALIGNED suite of ontologies split into the provenance, generic, and domain-speci c layers. As can be seen from the gure, a high emphasis has been placed on reusing existing, well known and standardised specications where available. At the top layer, the W3C provenance standard forms the baseline for all our speci cations and all our models extend it in some way. The split of the ALIGNED ontology suite between a generic layer and a domain speci c extensions layer allows rapid evolution of domain-speci c extensions for the ALIGNED use cases/trial environments (JURION, Seshat, DBpedia, PoolParty) based on a stable set of core concepts modelled in the generic layer. As the project progresses these extensions will be evaluated and incorporated into the generic layer if they prove valuable or more widely applicable than a single domain. Within the project the suite of ontologies is known as the "ALIGNED metamodel" due to the links with software engineering practices. 6http://www.w3.org/ns/prov-o 7https://www.jurion.de/ 8https://www.poolparty.biz/ 9http://wiki.dbpedia.org/
The ALIGNED suite of ontologies
Fig. 1. The ALIGNED Suite of Ontologies 3
Combining data and software engineering processes to increase productivity and agility, is a challenge being faced by several organisations aiming to exploit the bene ts of big data. Ontologies and vocabularies developed in accordance to competency questions, objective criteria and ontology engineering principles can provide useful support to data scientists and software engineers undertaking the challenge. In this paper we have proposed the ALIGNED suite of ontologies that provide semantic models of design intents, domain speci c datasets, software engineering processes, quality heuristics and error handling mechanisms. The suite contributes immensely towards enabling interoperability and alleviating some of the complexities involved. We have exempli ed the usage of the suite on a real-world use case from the legal domain and evaluated it against the desired criteria. As ontologies from the suite are now in various stages of adoption by the ALIGNED use cases, the next steps would incorporate their empirical evaluation.
10https://figshare.com/articles/ISWC2016_Resources_Track_Review_ Instructions/2016852
Generic criteria Evaluation
Value Addition (
Reuse (
Design and Technical quality All ontologies have been designed as OWL DL ontologies, in accordance to ontology engineeirng principles. Axiomatisations in the ontologies have been de ned based on the competency questions identi ed during requirements scoping.
Sustainability All ontologies are deployed on a public Github repositories. Long term sustainability has been assured by the ontology engineers involved in the design.
Speci c criteria Design suitability
Individual ontologies in the suite have been developed in close association with the requirements emerging from corresponding, potential exploiting application.Thus they closely conform to the suitability of the tasks for which they have been designed.
Design elegance and quality Axiomatisation in the ontologies have been developed following Gruber's principles [1] of clarity, coherence, extendability, minimum encoding bias and minimum ontological commitment.
Logical correctness The ontologies have been veri ed using DL reasoners for satis ability, incoherency and inconsistencies. Speci cally, inconsistencies for DIO has been checked against the instance data in the governance triple store.
External resources reuse External ontologies such as PROV-O, SKOS have been extensively used. Documentation The ALIGNED public deliverables and publications [3, 4] include detailed descriptions of the models. The ontologies have been well documented using rdfs:label and rdfs:comment. HTML documentation via the LODE service has also been enabled.
All ontologies have been graphically illustrated.
This research has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 644055, the ALIGNED project (www.aligned-project.eu).