On the performance impact of using JSON, beyond impedance mismatch

NOSQL database management systems adopt semi-structured data models, such as JSON, to easily accommodate schema evolution and overcome the overhead generated from transforming internal structures to tabular data (i.e., impedance mismatch). There exist multiple, and equivalent, ways to physically represent semi-structured data, but there is a lack of evidence about the potential impact on space and query performance. In this paper, we embark on the task of quantifying that, precisely for document stores. We empirically compare multiple ways of representing semi-structured data, which allows us to derive a set of guidelines for efficient physical database design considering both JSON and relational options in the same palette.Partly funded by the European Commission through the programme “EM IT4BI-DC”.Peer ReviewedPostprint (author's final draft

Engineering Agile Big-Data Systems

To be effective, data-intensive systems require extensive ongoing customisation to reflect changing user requirements, organisational policies, and the structure and interpretation of the data they hold. Manual customisation is expensive, time-consuming, and error-prone. In large complex systems, the value of the data can be such that exhaustive testing is necessary before any new feature can be added to the existing design. In most cases, the precise details of requirements, policies and data will change during the lifetime of the system, forcing a choice between expensive modification and continued operation with an inefficient design.Engineering Agile Big-Data Systems outlines an approach to dealing with these problems in software and data engineering, describing a methodology for aligning these processes throughout product lifecycles. It discusses tools which can be used to achieve these goals, and, in a number of case studies, shows how the tools and methodology have been used to improve a variety of academic and business systems

Building Information Modelling and Asset Management: Semantic and Syntactic Interoperability

Building Information Modelling (BIM) has the potential to improve the design, construction and operation of assets using a standardised machine-readable information model. Despite the rapidly increasing adoption of BIM in design and construction stages, the adoption of BIM for Operation and Maintenance (O&M) is still relatively weak. While there are multifaceted challenges behind that weak adoption, there are recurring themes of the poor data integration between BIM and existing Asset Management (AM) systems and of how to structure BIM models for use in the O&M phase. Reflecting on that interoperability challenge, this research aims to provide a methodology to design, develop and transfer the information required to support O&M from BIM models. To achieve the research aim, firstly a critical review of the literature was undertaken to develop a conceptual framework of the interoperability aspects for BIM implementation in AM. The proposed conceptual framework would facilitate the transfer of information from BIM models to AM tools through the development of a specific Model View Definition (MVD) and a Revit Plug-in. The MVD and Revit Plug-in are developed based on a taxonomy of the required data and based on a cross-mapping between the different standards and guidelines used in the Architecture, Engineering, Construction and Operation (AECO) industry. To achieve these aspects, semi-structured interviews and focus group are adapted to identify the required information and an effective cross-mapping between the standards where ontologies are utilised to publish and share machine-readable inter-Linked Data on the web. On the other hand, a prototyping approach is employed for the MVD and the Revit Plug-in development, while a case study method is used for evaluating the developed concepts and prototypes. The developed capabilities can enable facility managers to semantically link the BIM objects to the maintenance records in the Semantic Web during the O&M phase in order to provide a BIM environment without the specific BIM authoring application. Due to the assets’ heterogeneity, this research provides an interoperability solution for the data exchange of assets that consume energy from the BIM systems to the AM systems during the handover stage. Although the stated contributions of this research are anchored on assets that consume energy only, the outputs can still be updated and adapted to cover all of the operable and maintainable building assets

Architectural Principles for Autonomous Microservices

In the last decade architectural patterns like microservices and event-driven architectures have emerged to meet the challenges of distributed computing. This paper explores recent practices and research in microservice- and event-driven architectures to identify the challenges in architecting such systems. With a proof-of-concept study approach, we distilled a set of design principles to address these challenges, creating asynchronous and agnostic microservice architectures. Further, we provide a generic toolkit for implementing such architectures. An example of this architecture was implemented in the company TechnipFMC. Concurrently, an architecture trade-off analysis was performed using a utility-tree based approach, highlighting the impact and importance of our proposed principles and their generalizability. The evaluation provides evidence for the viability of the proposed design principles