Regional Aggregation and Discovery of Digital Collections: The Mountain West Digital Library

book chapterThe Mountain West Digital Library (MWDL) is a digital collaborative of over 180 partners from five states in the U.S. West, sharing free access to over 775 digital collections with over 950,000 resources. Partners of the MWDL work together on providing regional discovery via an online portal at mwdl.org and facilitating, on behalf of the region, the on-ramp to national discovery via the Digital Public Library of America (DPLA) portal at dp .la. MWDL was organized around these common goals: • Establish a distributed digitization and hosting infrastructure to support memory institutions in sharing their digital collections • Increase public access to digital collections materials through aggregation and discovery via open search portals • Promote interoperability of metadata via common standards and enhancements • Share expertise and training This chapter describes how these goals have been met for MWDL partners, through a coordinated network of distributed repositories supporting collections and a central harvesting system for searching. Key to the success of regional discovery has been the establishment of common standards and practices, along with the development of useful data enhancement practices, also described below. How MWDL has adapted over its years of growth and adoption of changing technologies, and particularly how it has served the emergence of the new national digital library, are also discussed. Finally, future directions for collaborative discovery are suggested, with notes about the challenges ahead

Stings from The Hive: Challenges of launching the University of Utah Data Repository

posterA series of challenges are described during the launching of The Hive, the data repository of the University of Utah

From Digital Library to Open Datasets

This article discusses the burgeoning “collections as data” movement within the fields of digital libraries and digital humanities. Faculty at the University of Utah’s Marriott Library are developing a collections as data strategy by leveraging existing Digital Library and Digital Matters programs. By selecting various digital collections, small- and large-scale approaches to developing open datasets are explored. Five case studies chronicling this strategy are reviewed, along with testing the datasets using various digital humanities methods, such as text mining, topic modeling, and GIS (geographic information system)

But Were We Successful? Using Online Asynchronous Focus Groups to Evaluate Library Services

USU launched a program in 2016 to connect researchers seeking federal funding with librarians to assist them with data management. This program assisted over 100 researchers, but was it successful? Our presentation will discuss how we evaluated the success of this program using online asynchronous focus groups (OAFG) in conjunction with a traditional survey. Our cross-institutional research team will share our findings as well as the challenges and successes of using OAFGs to assess library services

Assessing Research Compliance for Federally Funded Projects: The Good, the Bad, and the Publicly Accessible

In 2016, Utah State University launched a program to ensure their campus’ federal grant recipients were in compliance with funder mandates to share any data or publications produced as a result of the award. This paper discusses how a cross-institutional team of librarians and administrators evaluated the success of this program using online asynchronous focus groups (OAFG) in conjunction with a traditional survey. The challenges and successes of using OAFGs to assess library services are also examined. An OAFG gave participants greater convenience, flexibility, participation, and time to craft answers, eliminating some of the hurdles to traditional focus group participation

The Importance of Teaching Vocabulary: The Whys and Hows

This article focuses on providing teachers with the whys and hows to implement tier-two vocabulary instruction in PK-12 grade classrooms. The article examines what is meant by tier-two vocabulary words and the need for increased vocabulary instruction to gain word knowledge. It also offers teachers applicable texts and activities to be used when they become teachers and ways to incorporate a school-to-home connection in support of students\u27 learning of new vocabulary words. The texts and activities are divided into three grade levels: K-2, 3-5, and 6-12. In addition, the article is divided into two sections which outlines the whys and how for increasing student\u27s vocabulary knowledge

What lies beneath?: Knowledge infrastructures in the subseafloor biosphere and beyond

We present preliminary findings from a three-year research project comprised of longitudinal qualitative case studies of data practices in four large, distributed, highly multidisciplinary scientific collaborations. This project follows a 2 ×× 2 research design: two of the collaborations are big science while two are little science, two have completed data collection activities while two are ramping up data collection. This paper is centered on one of these collaborations, a project bringing together scientists to study subseafloor microbial life. This collaboration is little science, characterized by small teams, using small amounts of data, to address specific questions. Our case study employs participant observation in a laboratory, interviews ( n=49n=49 to date) with scientists in the collaboration, and document analysis. We present a data workflow that is typical for many of the scientists working in the observed laboratory. In particular, we show that, although this workflow results in datasets apparently similar in form, nevertheless a large degree of heterogeneity exists across scientists in this laboratory in terms of the methods they employ to produce these datasets—even between scientists working on adjacent benches. To date, most studies of data in little science focus on heterogeneity in terms of the types of data produced: this paper adds another dimension of heterogeneity to existing knowledge about data in little science. This additional dimension makes more complex the task of management and curation of data for subsequent reuse. Furthermore, the nature of the factors that contribute to heterogeneity of methods suggest that this dimension of heterogeneity is a persistent and unavoidable feature of little science.Alfred P. Sloan Foundation (#20113194)Ope

Data Management in the Long Tail: Science, Software, and Service

Scientists in all fields face challenges in managing and sustaining access to their research data. The larger and longer term the research project, the more likely that scientists are to have resources and dedicated staff to manage their technology and data, leaving those scientists whose work is based on smaller and shorter term projects at a disadvantage. The volume and variety of data to be managed varies by many factors, only two of which are the number of collaborators and length of the project. As part of an NSF project to conceptualize the Institute for Empowering Long Tail Research, we explored opportunities offered by Software as a Service (SaaS). These cloud-based services are popular in business because they reduce costs and labor for technology management, and are gaining ground in scientific environments for similar reasons. We studied three settings where scientists conduct research in small and medium-sized laboratories. Two were NSF Science and Technology Centers (CENS and C-DEBI) and the third was a workshop of natural reserve scientists and managers. These laboratories have highly diverse data and practices, make minimal use of standards for data or metadata, and lack resources for data management or sustaining access to their data, despite recognizing the need. We found that SaaS could address technical needs for basic document creation, analysis, and storage, but did not support the diverse and rapidly changing needs for sophisticated domain-specific tools and services. These are much more challenging knowledge infrastructure requirements that require long-term investments by multiple stakeholders.

Prediction of Dengue Incidence Using Search Query Surveillance

Improvements in surveillance, prediction of outbreaks and the monitoring of the epidemiology of dengue virus in countries with underdeveloped surveillance systems are of great importance to ministries of health and other public health decision makers who are often constrained by budget or man-power. Google Flu Trends has proven successful in providing an early warning system for outbreaks of influenza weeks before case data are reported. We believe that there is greater potential for this technique for dengue, as the incidence of this pathogen can vary by a factor of ten in some settings, making prediction all the more important in public health planning. In this paper, we demonstrate the utility of Google search terms in predicting dengue incidence in Singapore and Bangkok, Thailand using several regression techniques. Incidence data were provided by the Singapore Ministry of Health and the Thailand Bureau of Epidemiology. We find our models predict incident cases well (correlation greater than 0.8) and periods of high incidence equally well (AUC greater than 0.95). All data and analysis code used in our study are available free online and can be adapted to other settings

Spatial Dimensions of Dengue Virus Transmission across Interepidemic and Epidemic Periods in Iquitos, Peru (1999–2003)

To target prevention and control strategies for dengue fever, it is essential to understand how the virus travels through the city. We report spatial analyses of dengue infections from a study monitoring school children and adult family members for dengue infection at six-month intervals from 1999–2003, in the Amazonian city of Iquitos, Peru. At the beginning of the study, only DENV serotypes 1 and 2 were circulating. Clusters of infections of these two viruses were concentrated in the northern region of the city, where mosquito indices and previous DENV infection were both high. In 2002, DENV-3 invaded the city, replacing DENV-1 and -2 as the dominant strain. During the invasion process, the virus spread rapidly across the city, at low levels. After this initial phase, clusters of infection appeared first in the northern region of the city, where clusters of DENV-1 and DENV-2 had occurred in prior years. Most of the clusters we identified had radii >100 meters, indicating that targeted or reactive treatment of these high-risk areas might be an effective proactive intervention strategy. Our results also help explain why vector control within 100 m of a dengue case is often not successful for large-scale disease prevention