24:I[63208,["8920","static/chunks/8920-efbff8517d590b7e.js","9097","static/chunks/9097-7e60ff382fede0de.js","5914","static/chunks/5914-356082358a498a0b.js","9903","static/chunks/9903-11222066602aad8e.js","5438","static/chunks/5438-cfc6cd3ec63ed58c.js","3851","static/chunks/3851-d9d99b9df58ccefb.js","4621","static/chunks/4621-60797c2425663d2a.js","6871","static/chunks/6871-85cb03c97585f46a.js","6736","static/chunks/6736-932312a004c99faf.js","4550","static/chunks/4550-0bf059e3050c08b3.js","688","static/chunks/688-a6a2ac7bff269cd3.js","3984","static/chunks/3984-063c0b62f32133c7.js","7038","static/chunks/7038-4f87670d4e55ef18.js","9039","static/chunks/9039-75366c62dc7d0d0e.js","4563","static/chunks/4563-ad980d1babbf7b0b.js","6761","static/chunks/6761-0c10d1446de7ae1c.js","744","static/chunks/744-1e76229abb9e297b.js","7342","static/chunks/7342-1586df78600bf911.js","3617","static/chunks/3617-1f62a097637f4747.js","5895","static/chunks/5895-caa6c774914eb108.js","7481","static/chunks/7481-3b84c503a2ebfb3f.js","3668","static/chunks/3668-7dab69e4121c33af.js","39","static/chunks/39-e93a27d0920e6d92.js","2881","static/chunks/2881-445cc2384af2c6f9.js","2364","static/chunks/2364-e83d52fb21729d99.js","3208","static/chunks/3208-e65462d166bd3688.js","7582","static/chunks/app/toc/%5Btla%5D/%5Bvolume%5D/%5Bissue%5D/page-694a0e465c2c1334.js"],"default"] 25:T441,

An increasing number of solutions aim to support the steady increase of the number of requirements and requests for Linked Data at scale. This plethora of solutions leads to a growing need for objective means that facilitate the selection of adequate solutions for particular use cases. We hence present Hobbit, a distributed benchmarking platform designed for the unified execution of benchmarks for Linked Data solutions. The Hobbit benchmarking platform is based on the FAIR principles and is the first benchmarking platform able to scale up to benchmarking real-world scenarios for Big Linked Data solutions. Our online instance of the platform has more than 300 registered users and offers more than 40 benchmarks. It has been used in eleven benchmarking challenges and for more than 13000 experiments. We give an overview of the results achieved during 2 of these challenges and point to some of the novel insights that were gained from the results of the platform. Hobbit is open-source and available at http://github.com/hobbit-project.

26:T4ea,

The FAIR Guiding Principles, published in 2016, aim to improve the findability, accessibility, interoperability and reusability of digital research objects for both humans and machines. Until now the FAIR principles have been mostly applied to research data. The ideas behind these principles are, however, also directly relevant to research software. Hence there is a distinct need to explore how the FAIR principles can be applied to software. In this work, we aim to summarize the current status of the debate around FAIR and software, as basis for the development of community-agreed principles for FAIR research software in the future. We discuss what makes software different from data with regard to the application of the FAIR principles, and which desired characteristics of research software go beyond FAIR. Then we present an analysis of where the existing principles can directly be applied to software, where they need to be adapted or reinterpreted, and where the definition of additional principles is required. Here interoperability has proven to be the most challenging principle, calling for particular attention in future discussions. Finally, we outline next steps on the way towards definite FAIR principles for research software.

27:T5d9,