Why Geospatial Linked Open Data for Smart Mobility?

While the concept of Smart Cities is gaining momentum around the world and government data are increasingly available and accessible on the World Wide Web, key issues remain about Open Data and data standards for smart cities. A better integration and interoperabilty of data through the World Wide Web is only possible when everyone agrees on the standards for data representation and sharing. Linked Open Data positions itself as a solution for such standardization, being a method of publishing structured data using standard Web technologies. This facilitates the interlinking between datasets, makes them readable by computers, and easily accesible on the World Wide Web. We illustrate this through the example of an evolution from a traditional Content Management System with a geoportal, to a semantic based aproach. The Traffic Safety Monitor was developed in the period of 2012-2015 to monitor the road safety and to support policy development on road safety in Flanders (the northern part of Belgium). The system is built as a Content Management System (CMS), with publication tools to present geospatial indicators on road safety (e.g. the number of accidents with cars and the number of positive alcohol tests) as Web maps using stardardized Open Geospatial Consortium Webservices. The Traffic Safety Monitor is currently further developed towards a Mobility Monitor. Here, the focus is on the development of a business process model for the semantic exchange and publication of spatial data using Linked Open Data principles targeting indicators of sustainable and smart mobility. In the future, the usability of cycling Infrastructure for vehicles such as mobility scooters, bicycle trailers etc. can be assessed using Linked Open Data. The data and metadata is published in Linked open data format, opening the door for their reuse by a wide range of (smart) applications

SwissEnvEO: A FAIR National Environmental Data Repository for Earth Observation Open Science

Environmental scientific research is highly becoming data-driven and dependent on high performance computing infrastructures to process ever increasing large volume and diverse data sets. Consequently, there is a growing recognition of the need to share data, methods, algorithms, and infrastructure to make scientific research more effective, efficient, open, transparent, reproducible, accessible, and usable by different users. However, Earth Observations (EO) Open Science is still undervalued, and different challenges remains to achieve the vision of transforming EO data into actionable knowledge by lowering the entry barrier to massive-use Big Earth Data analysis and derived information products. Currently, FAIR-compliant digital repositories cannot fully satisfy the needs of EO users, while Spatial Data Infrastructures (SDI) are not fully FAIR-compliant and have difficulties in handling Big Earth Data. In response to these issues and the need to strengthen Open and Reproducible EO science, this paper presents SwissEnvEO, a Spatial Data Infrastructure complemented with digital repository capabilities to facilitate the publication of Ready to Use information products, at national scale, derived from satellite EO data available in an EO Data Cube in full compliance with FAIR principles

Mapping heterogeneous research infrastructure metadata into a unified catalogue for use in a generic virtual research environment

Virtual Research Environments (VREs), also known as science gateways or virtual laboratories, assist researchers in data science by integrating tools for data discovery, data retrieval, workflow management and researcher collaboration, often coupled with a specific computing infrastructure. Recently, the push for better open data science has led to the creation of a variety of dedicated research infrastructures (RIs) that gather data and provide services to different research communities, all of which can be used independently of any specific VRE. There is therefore a need for generic VREs that can be coupled with the resources of many different RIs simultaneously, easily customised to the needs of specific communities. The resource metadata produced by these RIs rarely all adhere to any one standard or vocabulary however, making it difficult to search and discover resources independently of their providers without some translation into a common framework. Cross-RI search can be expedited by using mapping services that harvest RI-published metadata to build unified resource catalogues, but the development and operation of such services pose a number of challenges. In this paper, we discuss some of these challenges and look specifically at the VRE4EIC Metadata Portal, which uses X3ML mappings to build a single catalogue for describing data products and other resources provided by multiple RIs. The Metadata Portal was built in accordance to the e-VRE Reference Architecture, a microservice-based architecture for generic modular VREs, and uses the CERIF standard to structure its catalogued metadata. We consider the extent to which it addresses the challenges of cross-RI search, particularly in the environmental and earth science domain, and how it can be further augmented, for example to take advantage of linked vocabularies to provide more intelligent semantic search across multiple domains of discourse

IMPROVEMENTS IN AUTOMATED DERIVATION OF OWL ONTOLOGIES FROM GEOSPATIAL UML MODELS

Standards from ISO/TC 211 are the foundation for modelling a universe of discourse in a geospatial context. UML models based on the standards, and in particular based on the UML profile defined in ISO 19103, have been developed and implemented in applications and databases for a wide range of geospatial information, from international to national and agency level. Amounts of information has been collected, maintained and made available based on the models, but mainly through specific services and exchange formats for geospatial information. To make the models and the information available in The Semantic Web, the geospatial UML models need to be transformed from UML to OWL ontologies, and the information needs to be transformed from UML-based structures to RDF triples. This paper investigates methods for transforming UML models of geospatial information to OWL ontologies, identifies challenges, suggest improvements and identifies needs for further research. Several methods for automated transformation from geospatial UML models to OWL handle basic concepts, but some concepts and context-closed restrictions from UML cannot be directly transformed to the open world of The Semantic Web. None of the analysed methods handles all of these issues, and suggested improvements include combining and improving transformation rules, as well as modifications in the UML models. To what degree and how these issues need to be handled will depend on whether the scope of the ontologies is to simply present geospatial information on The Semantic Web, or if they shall be used in a bidirectional information exchange

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions

Constraints oriented approaches in advancing spatial data infrastructure: case of Southern African Customs Union

Spatial data infrastructure (SDI) concept has made in-roads in a number of economies across the world, but Africa, on average is reported as lagging behind in implementation. This status has been confirmed through a number of continental SDI Assessments done in Africa. Africa SDI Assessments average its development as slow, which is problematic considering the fourth industrial revolution where; technology, communication, information and connectivity are the main enablers of political and socio-economic development. The problem of slow SDI development in Africa has acted as a catalyst for this study, with the five Southern African Customs Union (SACU) countries forming the scope for the investigations. This study focussed on investigating SACU countries SDIs and the associated sub-region with the aim of fostering on-going improvement. To do that, the prevailing SDI assessments in Africa were reviewed and utilised to propose a seven stepped constraint-oriented methodological approach as a means for guiding SDI development and progression within SACU. Management theories being; Theory of Constraints (TOC) and Due Diligence (DD) were utilised alongside the well-known SDI assessments of State of play (SoP) and Readiness Index (RI) to propose SDI On-Going Improvement Framework (SDIOGIF). This framework as suggested, has been enhanced using study data collected through documents, websites, workshops, interviews and questionnaires relating to SDIs within the SACU countries. Results from these instruments are revealing fundamental disparities in SDI implementations among study case countries, especially SDI aspects relating to legal frameworks and organisational setups. Some countries possess SDI legal frameworks and others don’t. In addition, these countries are found to base SDIs on varying institutional sectors such as; Surveying and Mapping (Geoinformation), Statistics, Environmental and Information Technology Agencies. Studying these countries’ SDIs, helped in establishing context-based constraints in their advancement. Through inductive reasoning, these constraints are aggregated as; macro-environment, organisation, legal, marketing, financial, management, informational and technology. They are designed into SDIOGIF, to guide country specific SDI improvements and their comparative analysis performed as a pre-cursor to establishing the proposed SACU Regional SDI which is currently non-existent