The CROSS Incubator: A Case Study for funding and training RSEs
- URL: http://arxiv.org/abs/2012.01144v1
- Date: Mon, 30 Nov 2020 20:16:43 GMT
- Title: The CROSS Incubator: A Case Study for funding and training RSEs
- Authors: Stephanie Lieggi and Ivo Jimenez and Jeff LeFevre and Carlos Maltzahn
- Abstract summary: The Center for Research in Open Source Software (CROSS) at UC Santa Cruz has been very effective at promoting the professional development of research software engineers.
Carlos Maltzahn founded CROSS in 2015 with a generous gift of $2,000,000 from UC Santa Cruz alumnus Dr. Sage Weil and founding memberships of Toshiba America Electronic Components, SK Hynix Memory Solutions, and Micron Technology.
This position paper will present CROSS fellowships as case studies for how university-led open source projects can create a real-world, reproducible model for effectively training, funding and supporting research software engineers.
- Score: 0.8472211480603307
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: The incubator and research projects sponsored by the Center for Research in
Open Source Software (CROSS, cross.ucsc.edu) at UC Santa Cruz have been very
effective at promoting the professional and technical development of research
software engineers. Carlos Maltzahn founded CROSS in 2015 with a generous gift
of $2,000,000 from UC Santa Cruz alumnus Dr. Sage Weil and founding memberships
of Toshiba America Electronic Components, SK Hynix Memory Solutions, and Micron
Technology. Over the past five years, CROSS funding has enabled PhD students to
not only create research software projects but also learn how to draw in new
contributors and leverage established open source software communities. This
position paper will present CROSS fellowships as case studies for how
university-led open source projects can create a real-world, reproducible model
for effectively training, funding and supporting research software engineers.
Related papers
- Student-Powered Digital Scholarship CoLab Project in the HKUST Library: Develop a Chinese Named-Entity Recognition (NER) Tool within One Semester from the Ground Up [0.0]
Starting in February 2024, the HKUST Library further extended the scope of AI literacy to AI utilization.
A key focus of the DS CoLab scheme has been on cultivating talents and enabling students to utilize advanced technologies in practical context.
arXiv Detail & Related papers (2025-03-29T04:15:34Z) - Open Source at a Crossroads: The Future of Licensing Driven by Monetization [11.149764135999437]
Open Source Software Licenses (OSS licenses) ensure that software can be sold or distributed as part of aggregate programs from various sources without requiring a royalty or fee.
We argue that open source is at a crossroads, with a growing need to redefine its licensing models and support communities and critical software.
arXiv Detail & Related papers (2025-03-04T17:44:01Z) - Making Software FAIR: A machine-assisted workflow for the research software lifecycle [2.682583873311538]
SoFAIR will extend the capabilities of widely used open scholarly infrastructures.
It will deliver and deploy an effective solution for the management of the research software lifecycle.
arXiv Detail & Related papers (2025-01-08T14:17:26Z) - Empirical Analysis of Pull Requests for Google Summer of Code [0.0]
The Google Summer of Code (GSoC) is a global initiative that matches students or new contributors with experienced mentors to work on open-source projects.
This study presents an empirical analysis of pull requests created by interns during the GSoC program.
arXiv Detail & Related papers (2024-12-17T17:42:43Z) - No Free Lunch: Research Software Testing in Teaching [1.4396109429521227]
This research explores the effects of research software testing integrated into teaching on research software.
In an in-vivo experiment, we integrated the engineering of a test suite for a large-scale network simulation as group projects into a course on software testing at the Blekinge Institute of Technology, Sweden.
We found that the research software benefited from the integration through substantially improved documentation and fewer hardware and software dependencies.
arXiv Detail & Related papers (2024-05-20T11:40:01Z) - Public-private funding models in open source software development: A case study on scikit-learn [0.0]
This study is a case study on scikit-learn, a Python library for machine learning funded by public research grants, commercial sponsorship, micro-donations, and a 32 euro million grant announced in France's artificial intelligence strategy.
Through 25 interviews with scikit-learn's maintainers and funders, this study makes two key contributions.
It contributes empirical findings about the benefits and drawbacks of public and private funding in an impactful OSS project, and the governance protocols employed by the maintainers to balance the diverse interests of their community and funders.
arXiv Detail & Related papers (2024-04-09T17:35:11Z) - SciCat: A Curated Dataset of Scientific Software Repositories [4.77982299447395]
We introduce the SciCat dataset -- a comprehensive collection of Free-Libre Open Source Software (FLOSS) projects.
Our approach involves selecting projects from a pool of 131 million deforked repositories from the World of Code data source.
Our classification focuses on software designed for scientific purposes, research-related projects, and research support software.
arXiv Detail & Related papers (2023-12-11T13:46:33Z) - Introducing High School Students to Version Control, Continuous
Integration, and Quality Assurance [0.0]
Two high school students volunteered in our lab at Wayne State University where I'm a graduate research assistant and Ph.D. student in computer science.
The students had taken AP Computer Science but had no prior experience with software engineering or software testing.
This paper documents our experience devising a group project to teach the requisite software engineering skills to implement automated tests.
arXiv Detail & Related papers (2023-10-05T21:44:11Z) - A pragmatic workflow for research software engineering in computational
science [0.0]
University research groups in Computational Science and Engineering (CSE) generally lack dedicated funding and personnel for Research Software Engineering (RSE)
RSE shifts the focus away from sustainable research software development and reproducible results.
We propose a RSE workflow for CSE that addresses these challenges, that improves the quality of research output in CSE.
arXiv Detail & Related papers (2023-10-02T08:04:12Z) - Using Machine Learning To Identify Software Weaknesses From Software
Requirement Specifications [49.1574468325115]
This research focuses on finding an efficient machine learning algorithm to identify software weaknesses from requirement specifications.
Keywords extracted using latent semantic analysis help map the CWE categories to PROMISE_exp. Naive Bayes, support vector machine (SVM), decision trees, neural network, and convolutional neural network (CNN) algorithms were tested.
arXiv Detail & Related papers (2023-08-10T13:19:10Z) - YMIR: A Rapid Data-centric Development Platform for Vision Applications [82.67319997259622]
This paper introduces an open source platform for rapid development of computer vision applications.
The platform puts the efficient data development at the center of the machine learning development process.
arXiv Detail & Related papers (2021-11-19T05:02:55Z) - Using Machine Learning to Predict Engineering Technology Students'
Success with Computer Aided Design [50.591267188664666]
We show how data combined with machine learning techniques can predict how well a particular student will perform in a design task.
We found that our models using early design sequence actions are particularly valuable for prediction.
Further improvements to these models could lead to earlier predictions and thus provide students feedback sooner to enhance their learning.
arXiv Detail & Related papers (2021-08-12T20:24:54Z) - A Survey of Knowledge Tracing: Models, Variants, and Applications [70.69281873057619]
Knowledge Tracing is one of the fundamental tasks for student behavioral data analysis.
We present three types of fundamental KT models with distinct technical routes.
We discuss potential directions for future research in this rapidly growing field.
arXiv Detail & Related papers (2021-05-06T13:05:55Z) - Incentive Mechanism Design for Resource Sharing in Collaborative Edge
Learning [106.51930957941433]
In 5G and Beyond networks, Artificial Intelligence applications are expected to be increasingly ubiquitous.
This necessitates a paradigm shift from the current cloud-centric model training approach to the Edge Computing based collaborative learning scheme known as edge learning.
arXiv Detail & Related papers (2020-05-31T12:45:06Z) - Knowledge Integration of Collaborative Product Design Using Cloud
Computing Infrastructure [65.2157099438235]
The main focus of this paper is the concept of ongoing research in providing the knowledge integration service for collaborative product design and development using cloud computing infrastructure.
Proposed knowledge integration services support users by giving real-time access to knowledge resources.
arXiv Detail & Related papers (2020-01-16T18:44:27Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.