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Dialog systems (e.g., chatbots) have been widely studied, yet related research that leverages artificial intelligence (AI) and natural language processing (NLP) is constantly evolving. These systems have typically been developed to interact with humans in the form of speech, visual, or text conversation. As humans continue to adopt dialog systems for various objectives, there is a need to involve humans in every facet of the dialog development life cycle for synergistic augmentation of both the humans and the dialog system actors in real-world settings. We provide a holistic literature survey on the recent advancements inhuman-centered dialog systems(HCDS). Specifically, we provide background context surrounding the recent advancements in machine learning-based dialog systems and human-centered AI. We then bridge the gap between the two AI sub-fields and organize the research works on HCDS under three major categories (i.e., Human-Chatbot Collaboration, Human-Chatbot Alignment, Human-Centered Chatbot Design & Governance). In addition, we discuss the applicability and accessibility of the HCDS implementations through benchmark datasets, application scenarios, and downstream NLP tasks. 

How to Position Your Gateway for Failure:The Ten Don’ts of Gateway DesignAbstractScience gateways are accelerators for science and education, providing user-friendly access to powerful computational resources and data analysis tools. Sustained science gateways frameworks such as Hubzero, Tapis, and Galaxy demonstrate the potential for gateways to revolutionize scientific exploration.However, despite initial promise, many gateway projects struggle to transition from prototypes to sustainable, long-term services. Well-intentioned, yet ultimately unsuccessful, gateways are part of the scientific landscape. This raises a critical question: what factors contribute to the demise of science gateways, and how can we avoid these pitfalls to ensure the success of future endeavors?This paper delves into the ten most common pitfalls that lead to science gateway failure. By analyzing these roadblocks, we aim to equip new and developing gateway initiatives with suggestions for long-term success. Our research draws on the collective experiences of numerous gateway projects.We identified critical areas where focused attention and strategic planning are essential. This knowledge will enable the development of good practices that nurture vibrant gateway communities and ensure the long-term sustainability of these valuable research tools. 

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This study provides statistical validation of three composite scales designed to calculate metrics for gateway user competence in terms of domain knowledge, technical skills, and problem-solving orientation. Based on an online survey (N = 365) fielded by an online panel company (Centiment.co) with US based participants, analyses using SPSS software demonstrated that technical competence varied between age groups (lower scores for participants aged 60 and higher) and educational levels (lower scores for participants without a bachelor’s degree) at a statistically significant level (at 95% confidence interval). These findings suggest that gateway developers may need to provide more technical support to users who are senior researchers and when gateways are being introduced into high school classrooms. Conversely, ethnicity and gender were found to be non-predictors of technical competence. These findings suggest the stereotype of white males being more tech-savvy than other ethnic and gender groups may not hold true anymore. 

Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, we present in this paper ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway. 

Science gateways have been a crucial tool that lowers the barriers of computer language proficiency for researchers and scientists alike to implement digital tools to further their research agendas. However, gateways remain somewhat esoteric and difficult to use for many potential users. A chatbot has been proposed as a solution to aid gateway users and for the improvement of gateway usability. Via in-depth interviews with 10 medical professionals, we investigated the challenges they faced when extracting data, namely, slow speed, limited scope, and mixed quality of data. We suggest future gateway developments to address the issues that medical professionals face when searching for publications and data. Findings suggest that gateways could serve practitioners (i.e., clinicians, healthcare providers in this case), beyond the original vision for research and education. Moreover, gateway projects could consider conducting similar market research interviews to better understand the work context (including challenges) faced by the intended users of specific gateways. 

Research Computing and Data (RCD) professionals play a crucial role in supporting and advancing research that involve data and/or computing, however, there is a critical shortage of RCD workforce, and organizations face challenges in recruiting and retaining RCD professional staff. It is not obvious to people outside of RCD how their skills and experience map to the RCD profession, and staff currently in RCD roles lack resources to create a professional development plan. To address these gaps, the CaRCC RCD Career Arcs working group has embarked upon an effort to gain a deeper understanding of the paths that RCD professionals follow across their careers. An important step in that effort is a recent survey the working group conducted of RCD professionals on key factors that influence decisions in the course of their careers. This survey gathered responses from over 200 respondents at institutions across the United States. This paper presents our initial findings and analyses of the data gathered. We describe how various genders, career stages, and types of RCD roles impact the ranking of these factors, and note that while there are differences across these groups, respondents were broadly consistent in their assessment of the importance of these factors. In some cases, the responses clearly distinguish RCD professionals from the broader workforce, and even other Information Technology professionals.