Linked Open Data for Cultural Heritage

This paper surveys the landscape of linked open data projects in cultural heritage, examining the work of groups from around the world. Traditionally, linked open data has been ranked using the five star method proposed by Tim Berners-Lee. We found this ranking to be lacking when evaluating how cultural heritage groups not merely develop linked open datasets, but find ways to use linked data to augment user experience. Building on the five-star method, we developed a six-stage life cycle describing both dataset development and dataset usage. We use this framework to describe and evaluate fifteen linked open data projects in the realm of cultural heritage

A linked data approach to publishing complex scientific workflows

Past data management practices in many fields of natural science, including climate research, have focused primarily on the final research output - the research publication - with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. Data were often regarded merely as an adjunct to the publication, rather than a scientific resource in their own right. In this paper, we attempt to address the issues of capturing and publishing detailed workflows associated with the climate/research datasets held by the Climatic Research Unit (CRU) at the University of East Anglia. To this end, we present a customisable approach to exposing climate research workflows for the effective re-use of the associated data, through the adoption of linked-data principles, existing widely adopted citation techniques (Digital Object Identifier) and data exchange mechanisms (Open Archives Initiative Object Reuse and Exchange)

Characterizing the Landscape of Musical Data on the Web: State of the Art and Challenges

Musical data can be analysed, combined, transformed and exploited for diverse purposes. However, despite the proliferation of digital libraries and repositories for music, infrastructures and tools, such uses of musical data remain scarce. As an initial step to help fill this gap, we present a survey of the landscape of musical data on the Web, available as a Linked Open Dataset: the musoW dataset of catalogued musical resources. We present the dataset and the methodology and criteria for its creation and assessment. We map the identified dimensions and parameters to existing Linked Data vocabularies, present insights gained from SPARQL queries, and identify significant relations between resource features. We present a thematic analysis of the original research questions associated with surveyed resources and identify the extent to which the collected resources are Linked Data-ready

A-posteriori provenance-enabled linking of publications and datasets via crowdsourcing

This paper aims to share with the digital library community different opportunities to leverage crowdsourcing for a-posteriori capturing of dataset citation graphs. We describe a practical approach, which exploits one possible crowdsourcing technique to collect these graphs from domain experts and proposes their publication as Linked Data using the W3C PROV standard. Based on our findings from a study we ran during the USEWOD 2014 workshop, we propose a semi-automatic approach that generates metadata by leveraging information extraction as an additional step to crowdsourcing, to generate high-quality data citation graphs. Furthermore, we consider the design implications on our crowdsourcing approach when non-expert participants are involved in the process<br/

Mejorando la Ciencia Abierta Usando Datos Abiertos Enlazados: Caso de Uso CONICET Digital

Los servicios de publicación científica están cambiando drásticamente, los investigadores demandan servicios de búsqueda inteligentes para descubrir y relacionar publicaciones científicas. Los editores deben incorporar información semántica para organizar mejor sus activos digitales y hacer que las publicaciones sean más visibles. En este documento, presentamos el trabajo en curso para publicar un subconjunto de publicaciones científicas de CONICET Digital como datos abiertos enlazados. El objetivo de este trabajo es mejorar la recuperación y la reutilización de datos a través de tecnologías de Web Semántica y Datos Enlazados en el dominio de las publicaciones científicas. Para lograr estos objetivos, se han tenido en cuenta los estándares de la Web Semántica y los esquemas RDF (Dublín Core, FOAF, VoID, etc.). El proceso de conversión y publicación se basa en las pautas metodológicas para publicar datos vinculados de gobierno. También describimos como estos datos se pueden vincular a otros conjuntos de datos como DBLP, Wikidata y DBPedia. Finalmente, mostramos algunos ejemplos de consultas que responden a preguntas que inicialmente no permite CONICET Digital.Scientific publication services are changing drastically, researchers demand intelligent search services to discover and relate scientific publications. Publishersneed to incorporate semantic information to better organize their digital assets and make publications more discoverable. In this paper, we present the on-going work to publish a subset of scientific publications of CONICET Digital as Linked Open Data. The objective of this work is to improve the recovery andreuse of data through Semantic Web technologies and Linked Data in the domain of scientific publications.To achieve these goals, Semantic Web standards and reference RDF schema?s have been taken into account (Dublin Core, FOAF, VoID, etc.). The conversion and publication process is guided by the methodological guidelines for publishing government linked data. We also outline how these data can be linked to other datasets DBLP, WIKIDATA and DBPEDIA on the web of data. Finally, we show some examples of queries that answer questions that initially CONICET Digital does not allowFil: Zárate, Marcos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFil: Carlos Buckle. Universidad Nacional de la Patagonia "San Juan Bosco"; ArgentinaFil: Mazzanti, Renato. Universidad Nacional de la Patagonia "San Juan Bosco"; ArgentinaFil: Samec, Gustavo Daniel. Universidad Nacional de la Patagonia "San Juan Bosco"; Argentin

Representing Dataset Quality Metadata using Multi-Dimensional Views

Data quality is commonly defined as fitness for use. The problem of identifying quality of data is faced by many data consumers. Data publishers often do not have the means to identify quality problems in their data. To make the task for both stakeholders easier, we have developed the Dataset Quality Ontology (daQ). daQ is a core vocabulary for representing the results of quality benchmarking of a linked dataset. It represents quality metadata as multi-dimensional and statistical observations using the Data Cube vocabulary. Quality metadata are organised as a self-contained graph, which can, e.g., be embedded into linked open datasets. We discuss the design considerations, give examples for extending daQ by custom quality metrics, and present use cases such as analysing data versions, browsing datasets by quality, and link identification. We finally discuss how data cube visualisation tools enable data publishers and consumers to analyse better the quality of their data.Comment: Preprint of a paper submitted to the forthcoming SEMANTiCS 2014, 4-5 September 2014, Leipzig, German