Measuring Impact (2017 Nebraska ACRL Scholarly Communication Roadshow, University of Nebraska-Lincoln)

Excerpt from the slides and presenter\u27s notes: Helps us see the lifecycle of research - why and how We have a lot of knowledge in this space because we know the resources and systems impact is based on -- we can act as thought leaders. Scholarly communication cycle involves “evaluating research and other scholarly writings for quality” (ARL, 2013). Librarians have always been part of the “impact” conversation from the perspective of the ways in which we help people. We provide budding researchers with access to seminal ideas in the field and help established researchers keep current with new information and ideas. We’ve provided recommendations to readers and developed magazines and services in order to promote particular books in particular genres. Awareness of impact in the scholarly impact can help: Strengthen the case for promotion or tenure / Quantify return on research investment for grant renewals and progress reports / Strengthen future funding requests by showing value of research / Understand an audience and learn how to appeal to them / Identify who is using the work and confirm that it is appropriately credited Identify collaborators within or outside of the subject area / Manage reputation

Impact & Assessment

In this session, we will discuss the increasing important role of impact and assessment, and how it affects everything from funding decisions, to the kind of services we offer, to what displays and exhibits we put on. We will discuss benefits and challenges of assessment, and offer ideas for next steps to implement or refine services related to impact and assessment

Understanding Scholarly Communication: Framing the Issues

This session will discuss the four pillars and the various actors in the scholarly communication system, identify current and historical disruptions in the research cycle, and help you to begin to visualize your role(s) in the scholarly communication cycle

Outreach & Programming

In this interactive session, we will talk about enriching opportunities for outreach and programming by understanding who your audience is, looking at aligning with other programming on campus, and designing a sample “pitch” for your services and programs

ADVISE: AI-accelerated Design of Evidence Synthesis for Global Development

When designing evidence-based policies and programs, decision-makers must distill key information from a vast and rapidly growing literature base. Identifying relevant literature from raw search results is time and resource intensive, and is often done by manual screening. In this study, we develop an AI agent based on a bidirectional encoder representations from transformers (BERT) model and incorporate it into a human team designing an evidence synthesis product for global development. We explore the effectiveness of the human-AI hybrid team in accelerating the evidence synthesis process. To further improve team efficiency, we enhance the human-AI hybrid team through active learning (AL). Specifically, we explore different sampling strategies, including random sampling, least confidence (LC) sampling, and highest priority (HP) sampling, to study their influence on the collaborative screening process. Results show that incorporating the BERT-based AI agent into the human team can reduce the human screening effort by 68.5% compared to the case of no AI assistance and by 16.8% compared to the case of using a support vector machine (SVM)-based AI agent for identifying 80% of all relevant documents. When we apply the HP sampling strategy for AL, the human screening effort can be reduced even more: by 78.3% for identifying 80% of all relevant documents compared to no AI assistance. We apply the AL-enhanced human-AI hybrid teaming workflow in the design process of three evidence gap maps (EGMs) for USAID and find it to be highly effective. These findings demonstrate how AI can accelerate the development of evidence synthesis products and promote timely evidence-based decision making in global development in a human-AI hybrid teaming context.Comment: 14 pages, 11 figures, to be published in the proceedings of IDETC-CIE 202

A scoping review of research funding for small-scale farmers in water scarce regions

Water scarcity is a global issue that disproportionately affects small-scale farmers in low- and middle-income countries (LMICs). Through geospatial analysis, we estimated that less than 37% of small-scale farms probably have irrigation in water scarce regions across LMICs, compared with 42% of non-small-scale farms. Through a literature synthesis assisted by machine learning, we then systematically mapped the existing research for on-farm interventions that improve the incomes or yields of small-scale farmers in water scarce regions. We mapped over 888 on-farm interventions used to combat water scarcity from 560 publications and showed a research bias towards yields rather than livelihoods. We found gaps in evidence for many commonly proposed solutions, including livestock management, digital technology and solutions to protect natural resources at the farm-level, such as buffer strips. Our findings can be used to set a funding agenda for research on the geographies that are most at risk of water scarcity and the interventions that most lack evidence

Vision for Adapted Crops and Soils (VACS) Research in Action: Opportunity Crops for Africa

The Vision for Adapted Crops and Soils (or “VACS”) brings together dedicated communities and individuals from research, advocacy, and policy to shine a light on opportunities that opportunity crops provide to build more resilient and food systems. Scaling up production and access to more diverse, climate-resilient crop varieties that support good nutrition and better livelihoods is a goal shared across national, regional, and international communities. VACS has gained important visibility, including from the U.S. Secretary of State, Antony Blinken, which has galvanized further international support. This report outlines the guiding concepts of the VACS approach, provides an overview of the research conducted as part of VACS through crop-modeling and evidence synthesis approaches, and recommends areas of focus for the movement going forward as well as ways to engage in VACS

Ceres2030 technical note: Evidence synthesis, machine learning and partnership

Food systems are complex, and as problems change and evolve, so will our understanding of their root causes and effective solutions. As donors mobilize to meet the targets set by UN Sustainable Development Goal 2 (SDG2): Zero Hunger by 2030, one of the most pervasive challenges they will face involves information: they need to know how much it will cost to fix these problems, what interventions have been researched, which are most effective in addressing them, and how those interventions will affect the rest of the economy. They must also be aware of potential synergies or trade-offs, where acting to achieve one objective can have strong impacts on achieving others, hampering attempts to establish a systematic approach to attaining the multiple objectives of SDG 2.Bill & Melinda Gates Foundation, BMZ German