Wikipedia as an encyclopaedia of life

In his 2003 essay E O Wilson outlined his vision for an “encyclopaedia of life” comprising “an electronic page for each species of organism on Earth”, each page containing “the scientific name of the species, a pictorial or genomic presentation of the primary type specimen on which its name is based, and a summary of its diagnostic traits.” Although the “quiet revolution” in biodiversity informatics has generated numerous online resources, including some directly inspired by Wilson's essay (e.g., "http://ispecies.org":http://ispecies.org, "http://www.eol.org":http://www.eol.org), we are still some way from the goal of having available online all relevant information about a species, such as its taxonomy, evolutionary history, genomics, morphology, ecology, and behaviour. While the biodiversity community has been developing a plethora of databases, some with overlapping goals and duplicated content, Wikipedia has been slowly growing to the point where it now has over 100,000 pages on biological taxa. My goal in this essay is to explore the idea that, largely independent of the efforts of biodiversity informatics and well-funded international efforts, Wikipedia ("http://en.wikipedia.org/wiki/Main_Page":http://en.wikipedia.org/wiki/Main_Page) has emerged as potentially the best platform for fulfilling E O Wilson’s vision

Linked Data approach for selection process automation in Systematic Reviews

Background: a systematic review identifies, evaluates and synthesizes the available literature on a given topic using scientific and repeatable methodologies. The significant workload required and the subjectivity bias could affect results. Aim: semi-automate the selection process to reduce the amount of manual work needed and the consequent subjectivity bias. Method: extend and enrich the selection of primary studies using the existing technologies in the field of Linked Data and text mining. We define formally the selection process and we also develop a prototype that implements it. Finally, we conduct a case study that simulates the selection process of a systematic literature published in literature. Results: the process presented in this paper could reduce the work load of 20% with respect to the work load needed in the fully manually selection, with a recall of 100%. Conclusions: the extraction of knowledge from scientific studies through Linked Data and text mining techniques could be used in the selection phase of the systematic review process to reduce the work load and subjectivity bia

DBpedia's triple pattern fragments: usage patterns and insights

Queryable Linked Data is published through several interfaces, including SPARQL endpoints and Linked Data documents. In October 2014, the DBpedia Association announced an official Triple Pattern Fragments interface to its popular DBpedia dataset. This interface proposes to improve the availability of live queryable data by dividing query execution between clients and servers. In this paper, we present a usage analysis between November 2014 and July 2015. In 9 months time, the interface had an average availability of 99.99 %, handling 16,776,170 requests, 43.0% of which were served from cache. These numbers provide promising evidence that low-cost Triple Pattern Fragments interfaces provide a viable strategy for live applications on top of public, queryable datasets