Maximizing Network Lifetime on the Line with Adjustable Sensing Ranges
Given n sensors on a line, each of which is equipped with a unit battery charge and an adjustable sensing radius, what schedule will maximize the lifetime of a network that covers the entire line?...
View ArticleThe Forestecology R Package for Fitting and Assessing Neighborhood Models of...
Neighborhood competition models are powerful tools to measure the effect of interspecific competition. Statistical methods to ease the application of these models are currently lacking. We present the...
View ArticleTeaching Computational Machine Learning (without Statistics)
This paper presents an undergraduate machine learning course that emphasizes algorithmic understanding and programming skills while assuming no statistical training. Emphasizing the development of...
View ArticleSuPP & MaPP: Adaptable Structure-Based Representations For Mir Tasks
Accurate and flexible representations of music data are paramount to addressing MIR tasks, yet many of the existing approaches are difficult to interpret or rigid in nature. This work introduces two...
View ArticleInfer: An R Package for Tidyverse-Friendly Statistical Inference
infer implements an expressive grammar to perform statistical inference that adheres to the tidyverse design framework (Wickham et al., 2019). Rather than providing methods for specific statistical...
View ArticleFacilitating Team-Based Data Science: Lessons Learned from the DSC-WAV Project
While coursework provides undergraduate data science students with some relevant analytic skills, many are not given the rich experiences with data and computing they need to be successful in the...
View ArticleAn Educator’s Perspective of the Tidyverse
Computing makes up a large and growing component of data science and statistics courses. Many of those courses, especially when taught by faculty who are statisticians by training, teach R as the...
View ArticlePopulation Modeling with Machine Learning can Enhance Measures of Mental...
Efforts to predict trait phenotypes based on functional MRI data from large cohorts have been hampered by low prediction accuracy and/or small effect sizes. Although these findings are highly...
View ArticleMental Health in the UK Biobank: A Roadmap to Self-Report Measures and...
The UK Biobank (UKB) is a highly promising dataset for brain biomarker research into population mental health due to its unprecedented sample size and extensive phenotypic, imaging, and biological...
View ArticleEvaluation of EDISON's Data Science Competency Framework Through a...
During the emergence of Data Science as a distinct discipline, discussions of what exactly constitutes Data Science have been a source of contention, with no clear resolution. These disagreements have...
View ArticleImplementing GitHub Actions Continuous Integration to Reduce Error Rates in...
Accurate field data are essential to understanding ecological systems and forecasting their responses to global change. Yet, data collection errors are common, and data analysis often lags far enough...
View ArticleAttending to the Cultures of Data Science Work
This essay reflects on the shifting attention to the “social” and the “cultural” in data science communities. While recently the “social” and the “cultural” have been prioritized in data science...
View ArticleAccountable Data: The Politics and Pragmatics of Disclosure Datasets
This paper attends specifically to what I call "disclosure datasets"- tabular datasets produced in accordance with laws requiring various kinds of disclosure. For the purposes of this paper, the most...
View ArticleMoving Ethnography: Infrastructuring Doubletakes and Switchbacks in...
In this article, we describe how our work at a particular nexus of STS, ethnography, and critical theory—informed by experimental sensibilities in both the arts and sciences—transformed as we built...
View ArticleReading Datasets: Strategies for Interpreting the Politics of Data Signification
All datasets emerge from and are enmeshed in power-laden semiotic systems. While emerging data ethics curriculum is supporting data science students in identifying data biases and their consequences,...
View ArticleClassification as Catachresis: Double Binds of Representing Difference with...
Background; This article explores the results of a three-year ethnographic study of how semiotic infrastructures-or digital standards and frameworks such as taxonomies, schemas, and ontologies that...
View ArticleData Sharing at Scale: A Heuristic for Affirming Data Cultures
Addressing the most pressing contemporary social, environmental, and technological challenges will require integrating insights and sharing data across disciplines, geographies, and cultures....
View ArticlePushback: Critical Data Designers and Pollution Politics
In this paper, we describe how critical data designers have created projects that ‘push back’ against the eclipse of environmental problems by dominant orders: the pioneering pollution database...
View Article
