Networked engineering notebooks for smart manufacturing

A goal of the industrial internet is to make information about manufacturing processes and resources available wherever decision making may be required. Agile use of information is a cornerstone of data analytics, but analytical methods more generally, including model-based investigations of manufacturability and operations, do not so easily benefit from this data. Rather than relating anonymous patterns of data to outcomes, these latter analytical methods are distinguished as relying on conceptual or physics-based models of the real world. Such models require careful consideration of the fitness of the data to the purpose of the analysis. Verification of these analyses, then, is a significant bottleneck. A related problem, that of ascertaining reproducible results in scientific claims, is being addressed through executable notebook technology. This paper proposes to use notebook technologies to address that bottleneck. It describes how this notebook technology, linked to internet-addressable ontologies and analytical metamodels, can be used to make model-based analytical methods more verifiable, and thus more effective for manufacturers

Skills and Knowledge for Data-Intensive Environmental Research.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap

The World Wide Web

An encyclopedic review of the World Wide Web, its origins, workings, and current statu

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Integrating science and literacy for young English learners : a pilot study.

This pilot investigated the promise of positive outcomes in literacy, science, and social behavior on K– 2 English learner (﴾EL)﴿ students after two months of implementation of the Science Inquiry Centered Argumentation Model (﴾ScICAM)﴿—a systematic teaching approach to science learning that integrates literacy instruction and argument-‐based inquiry. The sample included 17 teachers and 31 EL students. Results indicated that teacher practices (﴾proximal outcomes)﴿ aligned well with the ScICAM approach and resulted in increases in EL student learning (﴾distal outcomes)﴿. Teacher increase in the use of inquiry and writing scaffolds and student growth in the ability to express understandings through oral and written modes also suggested that ScICAM practices are supportive of key practices identified by the Next Generation Science Standards (﴾NGSS Lead States, 2013)﴿. These results highlight the merit of pursuing larger, long-‐term projects that collaborate with teachers on developing and implementing ScICAM interventions

Computational reproducibility of Jupyter notebooks from biomedical publications

Jupyter notebooks facilitate the bundling of executable code with its documentation and output in one interactive environment, and they represent a popular mechanism to document and share computational workflows. The reproducibility of computational aspects of research is a key component of scientific reproducibility but has not yet been assessed at scale for Jupyter notebooks associated with biomedical publications. We address computational reproducibility at two levels: First, using fully automated workflows, we analyzed the computational reproducibility of Jupyter notebooks related to publications indexed in PubMed Central. We identified such notebooks by mining the articles full text, locating them on GitHub and re-running them in an environment as close to the original as possible. We documented reproduction success and exceptions and explored relationships between notebook reproducibility and variables related to the notebooks or publications. Second, this study represents a reproducibility attempt in and of itself, using essentially the same methodology twice on PubMed Central over two years. Out of 27271 notebooks from 2660 GitHub repositories associated with 3467 articles, 22578 notebooks were written in Python, including 15817 that had their dependencies declared in standard requirement files and that we attempted to re-run automatically. For 10388 of these, all declared dependencies could be installed successfully, and we re-ran them to assess reproducibility. Of these, 1203 notebooks ran through without any errors, including 879 that produced results identical to those reported in the original notebook and 324 for which our results differed from the originally reported ones. Running the other notebooks resulted in exceptions. We zoom in on common problems, highlight trends and discuss potential improvements to Jupyter-related workflows associated with biomedical publications.Comment: arXiv admin note: substantial text overlap with arXiv:2209.0430

Becoming music

Following a confused encounter with a music manuscript, the author explores the underpinnings of that experience, to understand the nature and structure of music notations as drawing systems. A music notation is an almost-impossibly complicated bit of drawing. Calling it a map does not quite do the trick, even if the page somehow works like a map. Labelling it a diagram, typically a didactic visual tool, is off the mark as well. Furthermore, the traditional western staff notation, as an example with historical authority, happens to be a richly developed system for reading and writing, for composition. This mixed bag of structure and function makes the staff notation a persistently vital teaching tool, even in our vexing era of computational solutions. In its hybrid display, a music notation gives its many user-communities a strategic, two-dimensional mechanism for cross-modal analysis and annotation, and ultimately performance of its content, in higher dimensions. How does a music drawing relate to other drawing systems? And how is it that we are enabled to fix and re-fix the multi-dimensional complexes of musical performance onto a page