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Extending R2RML with Support for RDF Collections and Containers to Generate MADS-RDF Datasets
Abstract
It is a best practice to avoid the use of RDF collections and containers when publishing Linked Data, but sometimes vocabularies such as MADS-RDF prescribe these constructs. The Library of Trinity College Dublin is building a new asset management system backed by a relational database and wants to publish their metadata according to these vocabularies. We chose to use the W3C Recommendation R2RML to relate the database to RDF datasets, but R2RML unfortunately does not provide support for collections and containers. In this paper, we propose an extension to R2RML to address this problem. We support gathering collections and containers from different fields in a row of a (logical) table as well as across rows. We furthermore prescribe how the extended R2RML engine deals with named graphs in the RDF dataset as well as empty sets. Examples and our demonstration on a part of the Library’s database prove the feasibility of our approach.
... This issue inspired a separate project in which an R2RML expansion supporting the mapping of RDF Collections (and Containers) was developed [11]. This expansion facilitated the uplift of all metadata in the database to RDF, allowing for the publication of complete MODS records. ...
By generating bibliographic records in RDF, libraries can publish and interlink their metadata on the Semantic Web. However, there are currently many barriers which prevent libraries from doing this. This paper describes the process of developing an RDF-enabled cataloguing tool for a university library in an attempt to overcome some of these obstacles.
Digital curation requires substantial human expertise in order to achieve and maintain document collections of high quality. This necessitates usually expert knowledge of a librarian or curator in order to interpret the content and categorize it accordingly. This process is at the same time expensive and time-consuming. With the advent of knowledge bases and the plenitude of information contained within them new opportunities emerge at the horizon. In particular, entity-level analytics allows to semantically enrich contents via linked open data (LOD). To this end, we assess in this paper the approach of concise content annotation as a means of supporting the process of digital curation. In particular, we compare various entity-level annotation methods and highlight the importance of concise semantic tagging based on qualitative as well as quantitative evaluations.
With the growing amount of data being continuously produced, it is crucial to come up with solutions to expose data from ever more heterogeneous databases (e.g. NoSQL systems) as linked data.
In this paper we present {xR2RML}, a language designed to describe the mapping of various types of databases to RDF. {xR2RML} flexibly adapts to heterogeneous query languages and data models while remaining free from any specific language or syntax. It extends R2RML, the W3C recommendation for the mapping of relational databases to RDF, and relies on RML for the handling of various data representation formats. We analyse data models of several modern databases as well as the format in which query results are returned, and we show that {xR2RML} can translate any data element within such results into RDF, relying on existing languages such as XPath and JSONPath if needed. We illustrate some features of {xR2RML} such as the generation of RDF collections and containers, and the ability to deal with mixed content.
Despite the significant number of existing tools, incorporating data from multiple sources and different formats into the Linked Open Data cloud remains complicated. No mapping formalisation exists to define how to map such heterogeneous sources into RDF in an integrated and interoperable fashion. This paper introduces the RML mapping language, a generic language based on an extension over R2RML, the W3C standard for mapping relational databases into RDF. Broadening RML’s scope, the language becomes source-agnostic and extensible, while facilitating the definition of mappings of multiple heterogeneous sources. This leads to higher integrity within datasets and richer interlinking among resources.
R2RML: RDB to RDF mapping language
- S Das
- S Sundara
- R Cyganiak
Das, S., Sundara, S, Cyganiak, R.: R2RML: RDB to RDF mapping language. In: W3C
Recommendation (2012)