The Types, Roles, and Practices of Documentation in Data Analytics Open Source Software Libraries: A Collaborative Ethnography of Documentation Work

Computational research and data analytics increasingly relies on complex ecosystems of open source software (OSS) "libraries" -- curated collections of reusable code that programmers import to perform a specific task. Software documentation for these libraries is crucial in helping programmers/analysts know what libraries are available and how to use them. Yet documentation for open source software libraries is widely considered low-quality. This article is a collaboration between CSCW researchers and contributors to data analytics OSS libraries, based on ethnographic fieldwork and qualitative interviews. We examine several issues around the formats, practices, and challenges around documentation in these largely volunteer-based projects. There are many different kinds and formats of documentation that exist around such libraries, which play a variety of educational, promotional, and organizational roles. The work behind documentation is similarly multifaceted, including writing, reviewing, maintaining, and organizing documentation. Different aspects of documentation work require contributors to have different sets of skills and overcome various social and technical barriers. Finally, most of our interviewees do not report high levels of intrinsic enjoyment for doing documentation work (compared to writing code). Their motivation is affected by personal and project-specific factors, such as the perceived level of credit for doing documentation work versus more "technical" tasks like adding new features or fixing bugs. In studying documentation work for data analytics OSS libraries, we gain a new window into the changing practices of data-intensive research, as well as help practitioners better understand how to support this often invisible and infrastructural work in their projects

Beyond advertising: New infrastructures for publishing integrated research objects

ABSTRACT: Moving beyond static text and illustrations is a central challenge for scientific publishing in the 21st century. As early as 1995, Donoho and Buckheit paraphrased John Claerbout that “an article about [a] computational result is advertising, not scholarship. The actual scholarship is the full software environment, code and data, that produced the result” [1]. Awareness of this problem has only grown over the last 25 years; nonetheless, scientific publishing infrastructures remain remarkably resistant to change [2]. Even as these infrastructures have largely stagnated, the internet has ushered in a transition “from the wet lab to the web lab” [3]. New expectations have emerged in this shift, but these expectations must play against the reality of currently available infrastructures and associated sociological pressures. Here, we compare current scientific publishing norms against those associated with online content more broadly, and we argue that meeting the “Claerbout challenge” of providing the full software environment, code, and data supporting a scientific result will require open infrastructure development to create environments for authoring, reviewing, and accessing interactive research objects

Multivoxel codes for representing and integrating acoustic features in human cortex

Using fMRI and multivariate pattern analysis, we determined whether acoustic features are represented by independent or integrated neural codes in human cortex. Male and female listeners heard band-pass noise varying simultaneously in spectral (frequency) and temporal (amplitude-modulation [AM] rate) features. In the superior temporal plane, changes in multivoxel activity due to frequency were largely invariant with respect to AM rate (and vice versa), consistent with an independent representation. In contrast, in posterior parietal cortex, neural representation was exclusively integrated and tuned to specific conjunctions of frequency and AM features. Direct between-region comparisons show that whereas independent coding of frequency and AM weakened with increasing levels of the hierarchy, integrated coding strengthened at the transition between non-core and parietal cortex. Our findings support the notion that primary auditory cortex can represent component acoustic features in an independent fashion and suggest a role for parietal cortex in feature integration and the structuring of acoustic input. Significance statement A major goal for neuroscience is discovering the sensory features to which the brain is tuned and how those features are integrated into cohesive perception. We used whole-brain human fMRI and a statistical modeling approach to quantify the extent to which sound features are represented separately or in an integrated fashion in cortical activity patterns. We show that frequency and AM rate, two acoustic features that are fundamental to characterizing biological important sounds such as speech, are represented separately in primary auditory cortex but in an integrated fashion in parietal cortex. These findings suggest that representations in primary auditory cortex can be simpler than previously thought and also implicate a role for parietal cortex in integrating features for coherent perception

iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology

The Brain Imaging Data Structure (BIDS) is a community-driven specification for organizing neuroscience data and metadata with the aim to make datasets more transparent, reusable, and reproducible. Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measurements of the living human brain. To improve internal (re)use and external sharing of these unique data, we present a specification for storing and sharing iEEG data: iEEG-BIDS

Predictive models of auditory perception in human electrophysiology

It has long been thought that sensory systems operate by representing information in a hierarchy of sensory features, and that these features build upon one another. From low-level information such as spectral content, to high-level information such as word content, the sensory system must rapidly extract all of these features from the world. However, the precise nature of these levels of representation, as well as how they interact with one another, is not well-understood. In audition, intermediate sensory representations are often studied in animals, using techniques that treat neurons as a linear filter for incoming sensory inputs. If those inputs are spectro-temporal features (e.g., a spectrogram), then the result is a Spectro Temporal Receptive Field (STRF). This describes how the neural unit in question (e.g., a neuron) will respond to patterns in spectro-temporal space. It has been a crucial tool in understanding sensory processing in low-level neural activity. Using this approach it is also possible to study how this neural representation changes under different experimental conditions. STRF plasticity has been shown in both reward- and context-modulated experiments in animals.In recent years, it has been suggested that similar techniques may work in modeling the activity of neural signals recorded from humans. As we cannot generally record from single unit activity in humans, this approach relies on proxies for neural activity – specifically in the high-frequency activity (HFA) of electrocorticography electrodes. This poses a unique opportunity for two reasons: First, human language is a natural stimulus set for studying hierarchical feature representations in the brain. There are many ways to decompose speech into both auditory and linguistic components, and each of these could serve as inputs to the modeling technique described above. Second, humans are especially skilled at using high-level context such as their experience and assumptions about the world in order to change their behavior. This poses a unique opportunity to study the plasticity of speech representations in the brain.This thesis reports several new approaches towards studying the sensory representation of speech in the human brain, as well as how these representations may change due to experience. It aims to bridge the literature in rodents and songbirds with ideas in human electrophysiology in order to pursue new approaches to studying perception in humans