The Function Hub : an implementation-independent read/write function description repository

Functions are essential building blocks of any (computer) information system. However, development efforts to implement these functions are fragmented: a function has multiple implementations, each within a specific development context. Manual effort is needed handling various search interfaces and access methods to find the desired function, its metadata (if any), and associated implementations. This laborious process inhibits discovery, and thus reuse. Uniform, implementation-independent access is needed. We demo the Function Hub, available online at https://fno.io/hub: a Web application using a semantic interoperable model to map function descriptions to (multiple) implementations. The Function Hub allows editing and discovering function description metadata, and add information about alternative implementations. This way, the Function Hub enables users to discover relevant functions independently of their implementation, and to link to original published implementations

Detailed provenance capture of data processing

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An ontology to semantically declare and describe functions

Applications built on top of the Semantic Web are emerging as a novel solution in different areas, such as decision making and route planning. However, to connect results of these solutions -i.e., the semantically annotated data - with real-world applications, this semantic data needs to be connected to actionable events. A lot of work has been done (both semantically as non-semantically) to describe and define Web services, but there is still a gap on a more abstract level, i.e., describing interfaces independent of the technology used. In this paper, we present a data model, specification, and ontology to semantically declare and describe functions independently of the used technology. This way, we can declare and use actionable events in semantic applications, without restricting ourselves to programming language-dependent implementations. The ontology allows for extensions, and is proposed as a possible solution for semantic applications in various domains

Mapping languages analysis of comparative characteristics

RDF generation processes are becoming more interoperable, reusable, and maintainable due to the increased usage of mapping languages: languages used to describe how to generate an RDF graph from (semi-)structured data. This gives rise to new mapping languages, each with different characteristics. However, it is not clear which mapping language is fit for a given task. Thus, a comparative framework is needed. In this paper, we investigate a set of mapping languages that inhibit complementary characteristics, and present an initial set of comparative characteristics based on requirements as put forward by the reference works of those mapping languages. Initial investigation found 9 broad characteristics, classified in 3 categories. To further formalize and complete the set of characteristics, further investigation is needed, requiring a joint effort of the community

Hypermedia-based discovery for source selection using low-cost linked data interfaces

Evaluating federated Linked Data queries requires consulting multiple sources on the Web. Before a client can execute queries, it must discover data sources, and determine which ones are relevant. Federated query execution research focuses on the actual execution, while data source discovery is often marginally discussed-even though it has a strong impact on selecting sources that contribute to the query results. Therefore, the authors introduce a discovery approach for Linked Data interfaces based on hypermedia links and controls, and apply it to federated query execution with Triple Pattern Fragments. In addition, the authors identify quantitative metrics to evaluate this discovery approach. This article describes generic evaluation measures and results for their concrete approach. With low-cost data summaries as seed, interfaces to eight large real-world datasets can discover each other within 7 minutes. Hypermedia-based client-side querying shows a promising gain of up to 50% in execution time, but demands algorithms that visit a higher number of interfaces to improve result completeness