Implementing Transitive Credit with JSON-LD

Science and engineering research increasingly relies on activities that facilitate research but are not currently rewarded or recognized, such as: data sharing; developing common data resources, software and methodologies; and annotating data and publications. To promote and advance these activities, we must develop mechanisms for assigning credit, facilitate the appropriate attribution of research outcomes, devise incentives for activities that facilitate research, and allocate funds to maximize return on investment. In this article, we focus on addressing the issue of assigning credit for both direct and indirect contributions, specifically by using JSON-LD to implement a prototype transitive credit system.Comment: accepted by WSSSPE2 - http://wssspe.researchcomputing.org.uk/wssspe2

JSON-LD 1.0 : a JSON-based serialization for linked data

JSON es una serialización útil de datos y formato de mensajería. Esta especificación define JSON-LD, un formato basado en JSON para serializar datos enlazados. La sintaxis está diseñada para integrarse fácilmente en los sistemas implementados que ya usan JSON, y proporciona una ruta de actualización sin problemas de JSON a JSON-LD. Está destinado principalmente a ser una manera de utilizar los datos enlazados en entornos de programación basados ​​en la Web, para crear servicios Web interoperables, y para almacenar datos enlazados en los motores de almacenamiento basadas en JSON.W3

JSON-LD 1.0 processing algorithms and API

Esta especificación define un conjunto de algoritmos para transformaciones programáticas de documentos JSON-LD. La reestructuración de datos de acuerdo con las transformaciones definidas a menudo simplifica drásticamente su uso. Además, este documento propone una interfaz de programación de aplicaciones (API) para desarrolladores que implementen los algoritmos especificados.W3

Towards a biodiversity knowledge graph

One way to think about "core" biodiversity data is as a network of connected entities, such as taxa, taxonomic names, publications, people, species, sequences, images, and collections that form the "biodiversity knowledge graph". Many questions in biodiversity informatics can be framed as paths in this graph. This article explores this futher, and sketches a set of services and tools we would need in order to construct the graph

Coverages, JSON-LD and RDF data cubes

Many kinds of scientific data, including satellite imagery, climate simulations and sensor data, can be represented as coverages, which are essentially mappings from points in space and time to data values. Coverage data are typically encoded as multidimensional arrays in com- pact binary forms such as NetCDF, HDF and GeoTIFF, most of which require specialist knowledge and tools to process and manipulate. There is considerable current interest in helping the wider Web community use coverage data, by providing data in more general formats such as JSON and RDF, and by using commonly-accepted vocabularies. This short discussion paper outlines some current work in the area and highlights some of the main inherent issues

PROV-JSONLD: a JSON and linked data representation for provenance

In this paper, we propose a representation for PROV in JSON-LD, the JSON format for Linked Data, called PROV-JSONLD. As a JSON-based format, this provenance representation can be readily consumed by Web applications currently supporting JSON. As a Linked Data format, at the same time, it also represents provenance data in RDF using the PROV ontology. Hence, it is suitable for usages in both the Web and the Semantic Web