19,911 research outputs found
Sustainable Software Ecosystems for Open Science
Sustainable software ecosystems are difficult to build, and require concerted
effort, community norms and collaborations. In science it is especially
important to establish communities in which faculty, staff, students and
open-source professionals work together and treat software as a first-class
product of scientific investigation-just as mathematics is treated in the
physical sciences. Kitware has a rich history of establishing collaborative
projects in the science, engineering and medical research fields, and continues
to work on improving that model as new technologies and approaches become
available. This approach closely follows and is enhanced by the movement
towards practicing open, reproducible research in the sciences where data,
source code, methodology and approach are all available so that complex
experiments can be independently reproduced and verified.Comment: Workshop on Sustainable Software: Practices and Experiences, 4 pages,
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Automating Metadata Extraction: Genre Classification
A problem that frequently arises in the management and integration of scientific data is the lack of context and semantics that would link data encoded in disparate ways. To bridge the discrepancy, it often helps to mine scientific texts to aid the understanding of the database. Mining relevant text can be significantly aided by the availability of descriptive and semantic metadata. The Digital Curation Centre (DCC) has undertaken research to automate the extraction of metadata from documents in PDF([22]). Documents may include scientific journal papers, lab notes or even emails. We suggest genre classification as a first step toward automating metadata extraction. The classification method will be built on looking at the documents from five directions; as an object of specific visual format, a layout of strings with characteristic grammar, an object with stylo-metric signatures, an object with meaning and purpose, and an object linked to previously classified objects and external sources. Some results of experiments in relation to the first two directions are described here; they are meant to be indicative of the promise underlying this multi-faceted approach.
Univalent Foundations as a Foundation for Mathematical Practice
I prove that invoking the univalence axiom is equivalent to arguing 'without loss of generality' (WLOG) within Propositional Univalent Foundations (PropUF), the fragment of Univalent Foundations (UF) in which all homotopy types are mere propositions. As a consequence, I argue that practicing mathematicians, in accepting WLOG as a valid form of argument, implicitly accept the univalence axiom and that UF rightly serves as a Foundation for Mathematical Practice. By contrast, ZFC is inconsistent with WLOG as it is applied, and therefore cannot serve as a foundation for practice
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