Public transit route planning through lightweight linked data interfaces

While some public transit data publishers only provide a data dump – which only few reusers can afford to integrate within their applications – others provide a use case limiting origin-destination route planning api. The Linked Connections framework instead introduces a hypermedia api, over which the extendable base route planning algorithm “Connections Scan Algorithm” can be implemented. We compare the cpu usage and query execution time of a traditional server-side route planner with the cpu time and query execution time of a Linked Connections interface by evaluating query mixes with increasing load. We found that, at the expense of a higher bandwidth consumption, more queries can be answered using the same hardware with the Linked Connections server interface than with an origin-destination api, thanks to an average cache hit rate of 78%. The findings from this research show a cost-efficient way of publishing transport data that can bring federated public transit route planning at the fingertips of anyone

Enacting the Semantic Web: Ontological Orderings, Negotiated Standards, and Human-machine Translations

Artificial intelligence (AI) that is based upon semantic search has become one of the dominant means for accessing information in recent years. This is particularly the case in mobile contexts, as search based AI are embedded in each of the major mobile operating systems. The implications are such that information is becoming less a matter of choosing between different sets of results, and more of a presentation of a single answer, limiting both the availability of, and exposure to, alternate sources of information. Thus, it is essential to understand how that information comes to be structured and how deterministic systems like search based AI come to understand the indeterminate worlds they are tasked with interrogating. The semantic web, one of the technologies underpinning these systems, creates machine-readable data from the existing web of text and formalizes those machine-readable understandings in ontologies. This study investigates the ways that those semantic assemblages structure, and thus define, the world. In accordance with assemblage theory, it is necessary to study the interactions between the components that make up such data assemblages. As yet, the social sciences have been slow to systematically investigate data assemblages, the semantic web, and the components of these important socio-technical systems. This study investigates one major ontology, Schema.org. It uses netnographic methods to study the construction and use of Schema.org to determine how ontological states are declared and how human-machine translations occur in those development and use processes. This study has two main findings that bear on the relevant literature. First, I find that development and use of the ontology is a product of negotiations with technical standards such that ontologists and users must work around, with, and through the affordances and constraints of standards. Second, these groups adopt a pragmatic and generalizable approach to data modeling and semantic markup that determines ontological context in local and global ways. This first finding is significant in that past work has largely focused on how people work around standards’ limitations, whereas this shows that practitioners also strategically engage with standards to achieve their aims. Second, the particular approach that these groups use in translating human knowledge to machines, differs from the formalized and positivistic approaches described in past work. At a larger level, this study fills a lacuna in the collective understanding of how data assemblages are constructed and operate

SIGHTED: A Framework for Semantic Integration of Heterogeneous Sensor Data on the Internet of Things

AbstractSensors are embedded nowadays in a growing number of everyday life objects. Smartphones, wearables, and sensor networks together play an important role in bridging the gap between physical and cyber worlds, a fundamental aspect of the Internet of Things vision. The ability to reuse sensor data integrated from multiple heterogeneous sources is a step towards building innovative applications and services. In this paper SIGHTED, a sensor data integration framework, is proposed exploiting semantic web technologies and linked data principles. It provides a layered structure as a guideline for integrating sensor data from various sources supporting accessibility and usability. DotThing, a demo platform, is implemented as an instantiation of SIGHTED framework and evaluated. Smartphones and sensor nodes are connected to DotThing showing the ability to query and reuse integrated sensor data from multiple sources to create more flexible horizontal applications. DotThing implementation also demonstrates the need for adding a semantic layer to existing IoT cloud-based platforms, like Xively, that generally lack such layer resulting in proprietary vertical solutions with limited data integration and discovery capabilities. DotThing makes use of vocabularies from existing ontologies on the linked data cloud providing a unified model to annotate data and link it to existing resources on the web

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

A Framework for Automating the Invocation of Web APIs

Web APIs, characterized by their relative simplicity and their natural suitability for the Web, have become increasingly dominant in the world of services on the Web. Despite their popularity, Web APIs are so heterogeneous in terms of the underlying principles adopted and the means used for publishing them that discovering, understanding and notably invoking Web APIs is nowadays more an art than a science. In this paper, we present our work towards supporting the automated invocation of Web APIs. In particular, we describe a framework that provides a unique entry point for the invocation of most Web APIs that can be found on the Web, by exploiting non-intrusive semantic annotations of HTML pages describing Web APIs in order to capture both their semantics as well as information necessary to carry out their invocation