Big Data Infrastructure at the Crossroads 3 perceptions that much data is either derivative, low quality, or gathered from sources that are inappropriate for open sharing. ▪ Ethical Challenges. The ethical dimensions of big data research remain contested, and some researchers are uncertain about best practices for ethical research conduct. Although IRB guidance is valued, some researchers expressed concerns that IRB regulations are not well adapted to new or evolving research methods. ▪ Support and Training. Researchers tend to favor informal training methods, such as internet tutorials, over formal training in big data methods. While such methods work well for solving immediate problems, they are less well suited to acquiring foundational knowledge, leaving the potential for blind spots in academic research.

A wide array of existing metrics quantifies a scientific paper's prominence or the author's prestige. Many who use these metrics make assumptions that higher citation counts or more public attention must indicate more reliable, better quality science. While current metrics offer valuable insight into scientific publications, they are an inadequate proxy for measuring the quality, transparency, and trustworthiness of published research. Three essential elements to establishing trust in a work include: trust in the paper, trust in the author, and trust in the data. To address these elements in a systematic and automated way, we propose the ripetaScore as a direct measurement of a paper's research practices, professionalism, and reproducibility. Using a sample of our current corpus of academic papers, we demonstrate the ripetaScore's efficacy in determining the quality, transparency, and trustworthiness of an academic work. In this paper, we aim to provide a metric to evaluate scientific reporting quality in terms of transparency and trustworthiness of the research, professionalism, and reproducibility.

Emerging technologies are revolutionizing the field of scholarly communication. Because of this, scholars increasingly need specialized support during all stages of the research process. With the academic library as the unit of analysis, two concepts from Rogers' Diffusion of Innovation theory and organizational innovation literature are drawn upon to assess the sustainability of scholarly communication work in libraries. These concepts are organizational restructuring and formalization. Data on Association of Research Libraries (ARL) employees with relevant job titles and three digital curation competencies documents are analysed. Study findings suggest that ARL information agencies have restructured to provide added research support and that skills associated with scholarly communication positions are becoming more uniform. We conclude that scholarly communication information professionals are part of a sustainable area of practice within ARL information agencies, that has matured over the past decade, and this trend is likely to continue in at least the short term.the study of how scholars in any field (e.g., physical, biological, social and behavioural sciences, humanities and technology) use and disseminate information through formal and informal channels. The study of scholarly communication includes the growth of scholarly information, the relationships among research areas and disciplines, the information needs and uses of individual user groups, and the relationships among formal and informal methods of communication (Borgman, 1990, pp. 13-4).Scholarly communication enables the work of researchers at universities and organizations that are dedicated to creating new knowledge. In the United States (U.S.), over half of all federal research dollars are granted to university-affiliated researchers (Regazzi, 2015) making universities a hub for the creation of new knowledge. Supporting ScholarsSupporting scholarly communication on university campuses in an age of emerging technologies has naturally fallen to information professionals based in information agencies, such as academic libraries. Traditionally, academic libraries have divided the expertise they provide into technical services and public services, but given the complexity of technologies combined with the increasingly sophisticated needs of users, a new breed of information professional must emerge (e.g., Kowalski, 2017). In the case of scholarly communication questions, not only must the information professional curate and supply access to scholarship, but he/she must also work with scholars to organize, provide access to, save, and share their work. Providing specialized support to scholars (e.g., Ketchum, 2017) during the research process has quickly become the purview of the academic library.As the needs of researchers and scholars have changed, the work of information professionals has evolved in parallel. Working to support the field of "scholarly communication today reflects a [need to master an ever-growing] constellation of tools, practices...

This chapter contributes to academic library institutions currently engaged in or formulating their strategy for engaging in data science. The chapter provides academic library institutions, and library and information science students, with a context in which to consider how they can collaborate locally and internationally to advance the use of data by scholars (students, researchers, and the public). Presented from the perspective of an association of research libraries, the chapter explores how, together, research libraries work with others to convene, inform, shape, and influence data science and data research policies and practices. The chapter provides examples of data and data science collaborations in teaching, learning, and research so the reader can identify specific skills and knowledge they may need or want to develop in order to collaborate, and they can learn about at least one existing or emerging type of collaboration they would like to explore further.