Ten Simple Rules for Catalyzing Collaborations and Building Bridges between Research Software Engineers and Software Engineering Researchers

• URL: http://arxiv.org/abs/2506.03012v1
• Date: Tue, 03 Jun 2025 15:51:17 GMT
• Title: Ten Simple Rules for Catalyzing Collaborations and Building Bridges between Research Software Engineers and Software Engineering Researchers
• Authors: Nasir U. Eisty, Jeffrey C. Carver, Johanna Cohoon, Ian A. Cosden, Carole Goble, Samuel Grayson,
• Abstract summary: This paper presents ten strategic guidelines aimed at fostering productive partnerships between Research Software Engineers (RSEs) and Software Engineering Researchers (SERs)<n>The guidelines emphasize the importance of recognizing and respecting the cultural and operational differences between RSEs and SERs.<n>They advocate for identifying shared challenges, maintaining openness to emerging problems, ensuring mutual benefits, and serving as advocates for one another.
• Score: 3.2667114928245646
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In the evolving landscape of scientific and scholarly research, effective collaboration between Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) is pivotal for advancing innovation and ensuring the integrity of computational methodologies. This paper presents ten strategic guidelines aimed at fostering productive partnerships between these two distinct yet complementary communities. The guidelines emphasize the importance of recognizing and respecting the cultural and operational differences between RSEs and SERs, proactively initiating and nurturing collaborations, and engaging within each other's professional environments. They advocate for identifying shared challenges, maintaining openness to emerging problems, ensuring mutual benefits, and serving as advocates for one another. Additionally, the guidelines highlight the necessity of vigilance in monitoring collaboration dynamics, securing institutional support, and defining clear, shared objectives. By adhering to these principles, RSEs and SERs can build synergistic relationships that enhance the quality and impact of research outcomes.

Related papers

• Bridging Boundaries: How to Foster Effective Research Collaborations Across Affiliations in the Field of Trust and Safety [0.5300037515002964]
  This paper examines how cross-affiliation research partnerships can be structured to overcome misaligned incentives, timelines and constraints.<n>We propose a practical, step-by-step framework for initiating and managing effective collaborations.
  arXiv  Detail & Related papers  (2025-07-17T11:27:32Z)
• Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games [87.5673042805229]
  How large language models balance self-interest and collective well-being is a critical challenge for ensuring alignment, robustness, and safe deployment.<n>We adapt a public goods game with institutional choice from behavioral economics, allowing us to observe how different LLMs navigate social dilemmas.<n>Surprisingly, we find that reasoning LLMs, such as the o1 series, struggle significantly with cooperation.
  arXiv  Detail & Related papers  (2025-06-29T15:02:47Z)
• Bridging the Gap: Integrating Ethics and Environmental Sustainability in AI Research and Practice [57.94036023167952]
  We argue that the efforts aiming to study AI's ethical ramifications should be made in tandem with those evaluating its impacts on the environment.<n>We propose best practices to better integrate AI ethics and sustainability in AI research and practice.
  arXiv  Detail & Related papers  (2025-04-01T13:53:11Z)
• Enhancing Cooperation through Selective Interaction and Long-term Experiences in Multi-Agent Reinforcement Learning [10.932974027102619]
  This study introduces a computational framework based on multi-agent reinforcement learning in the spatial Prisoner's Dilemma game. By modelling each agent using two distinct Q-networks, we disentangle the coevolutionary dynamics between cooperation and interaction.
  arXiv  Detail & Related papers  (2024-05-04T12:42:55Z)
• Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View [60.80731090755224]
  This paper probes the collaboration mechanisms among contemporary NLP systems by practical experiments with theoretical insights. We fabricate four unique societies' comprised of LLM agents, where each agent is characterized by a specific trait' (easy-going or overconfident) and engages in collaboration with a distinct thinking pattern' (debate or reflection) Our results further illustrate that LLM agents manifest human-like social behaviors, such as conformity and consensus reaching, mirroring social psychology theories.
  arXiv  Detail & Related papers  (2023-10-03T15:05:52Z)
• The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice [64.29355073494125]
  This article aims to ground what we dub the "participatory turn" in AI design by synthesizing existing theoretical literature on participation. We articulate empirical findings concerning the current state of participatory practice in AI design based on an analysis of recently published research and semi-structured interviews with 12 AI researchers and practitioners.
  arXiv  Detail & Related papers  (2023-10-02T05:30:42Z)
• Understanding the Application of Utility Theory in Robotics and Artificial Intelligence: A Survey [5.168741399695988]
  The utility is a unifying concept in economics, game theory, and operations research, even in the Robotics and AI field. This paper introduces a utility-orient needs paradigm to describe and evaluate inter and outer relationships among agents' interactions.
  arXiv  Detail & Related papers  (2023-06-15T18:55:48Z)
• Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice [10.979734542685447]
  An emerging body of research indicates that ineffective cross-functional collaboration represents a major barrier to addressing issues of fairness in AI design and development. We conducted a series of interviews and design workshops with 23 industry practitioners spanning various roles from 17 companies. We found that practitioners engaged in bridging work to overcome frictions in understanding, contextualization, and evaluation around AI fairness across roles.
  arXiv  Detail & Related papers  (2023-06-10T23:42:26Z)
• The Equitable AI Research Roundtable (EARR): Towards Community-Based Decision Making in Responsible AI Development [4.1986677342209004]
  The paper reports on our initial evaluation of The Equitable AI Research Roundtable. EARR was created in collaboration among a large tech firm, nonprofits, NGO research institutions, and universities. We outline three principles in practice of how EARR has operated thus far that are especially relevant to the concerns of the FAccT community.
  arXiv  Detail & Related papers  (2023-03-14T18:57:20Z)
• Learning Roles with Emergent Social Value Orientations [49.16026283952117]
  This paper introduces the typical "division of labor or roles" mechanism in human society. We provide a promising solution for intertemporal social dilemmas (ISD) with social value orientations (SVO) A novel learning framework, called Learning Roles with Emergent SVOs (RESVO), is proposed to transform the learning of roles into the social value orientation emergence.
  arXiv  Detail & Related papers  (2023-01-31T17:54:09Z)
• Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper [50.25428141435537]
  Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between machine learning, big data, streaming analytics, and the management of IT operations. Main aim of the AIOPS workshop is to bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field.
  arXiv  Detail & Related papers  (2021-01-15T10:43:10Z)

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.