Letters to the Editor

Letters to the Edito

What Do We Know About The Stewardship Gap?

In the 21st century, digital data drive innovation and decision-making in nearly every field. However, little is known about the total size, characteristics, and sustainability of these data. In the scholarly sphere, it is widely suspected that there is a gap between the amount of valuable digital data that is produced and the amount that is effectively stewarded and made accessible. The Stewardship Gap Project (http://bit.ly/stewardshipgap) seeks to investigate characteristics of and measure the stewardship gap for sponsored scholarly activity in the United States. This paper presents a preliminary definition of the stewardship gap based on a review of relevant literature and investigates areas of the stewardship gap for which metrics have been developed and measurements made, and where work to measure the stewardship gap is yet to be done. The main findings presented are 1) there is not one stewardship gap but rather multiple “gaps” that contribute to whether data is responsibly stewarded; 2) there are relationships between the gaps that can be used to guide strategies for addressing the stewardship gap; and 3) there are imbalances in the types and depths of studies that have been conducted to measure the stewardship gap.Alfred P. Sloan Foundationhttp://deepblue.lib.umich.edu/bitstream/2027.42/122726/1/StewardshipGap_Final.pdfDescription of StewardshipGap_Final.pdf : Main articl

The Stewardship Gap: A Challenge in Long-Term Access to Data

Despite broad consensus among many in the scientific research, data, and policy communities about the importance of preserving and sharing research data, there are significant concerns about the adequacy of measures being taken today to enable these activities. The difference between current activities and best or ideal policies and practices constitutes a gap that this article describes: the stewardship gap—a gap that will require innovative strategies by researchers, research organizations, and research sponsors to address. The authors interviewed 46 active researchers, drawn from a variety of scientific domains, to understand their perspectives on the value of their research data, the length of time their data would remain valuable, and the kind and extent of commitments in place to ensure ongoing preservation of valuable data. In all, the researchers provided descriptions, valuations, and prospective plans for 120 datasets produced in 46 projects. Four concepts are valuable for understanding our findings: the kinds of commitment researchers receive from data stewards; who takes responsibility for stewardship; the value of the data as perceived by the researcher and others; and the length of time over which data are valuable and commitments exist. Based on this study as a representation of the larger cohort of data created with federal and foundation R&D support, research data are "at risk." This is especially so when data are valuable and the length of time for which there is a preservation commitment is less than the length of time that the data will have value. Closing gaps in commitment and responsibility is essential if valuable data are to be effectively preserved. This calls for clear policy directives from government agencies and other research sponsors in partnership with research-performing institutions, designation and acceptance of responsibility, and supporting human and financial investments for the research data the community deems as valuable.Alfred P. Sloan Foundation; Rensselaer Polytechnic Institute; University of Colorado Boulderhttps://deepblue.lib.umich.edu/bitstream/2027.42/146759/6/Stewardship Gap Article for deep blue-updated January 2019.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146759/1/Stewardship Gap Article for Deep Blue.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146759/2/Stewardship Gap Supplemental Materials for Deep Blue.pdf1517137Description of Stewardship Gap Article for deep blue-updated January 2019.pdf : Main Article (January 2019)Description of Stewardship Gap Article for Deep Blue.pdf : Previous VersionDescription of Stewardship Gap Supplemental Materials for Deep Blue.pdf : Supplemental Material

Defining and distributing longitudinal historical data in a general way through an intermediate structure

'Der Beitrag diskutiert am Beispiel von demographischen Mikrodaten methodologische Probleme von Längsschnittdaten. Die Herausforderungen bestehen darin, 1. Lebensverläufe in kartesische Datenformate zu transformieren, die mit den Erfordernissen gängiger statistischer Analysesysteme kompatibel sind, und 2. Datensätze für interlokale und interkulturelle Studien vergleichbar zu machen. Um dieses Ziel zu erreichen wird eine intermediäre Datenstruktur (IDS) vorgeschlagen, die auf alle Datenbanken übertragen kann. Die Autoren erläutern den Vorteil des IDS-Ansatzes und die Maßnahmen, die zur Umsetzung des Konzeptes führen werden.' (Autorenreferat)'In recent years, studies of historical populations have shifted from tracing large-scale processes to analyzing longitudinal micro data in the form of 'life histories'. This approach expands the scope of social history by integrating data on a range of life course events. The complexity of life-course analysis, however, has limited most researchers to working with one specific database. The authors discuss methodological problems raised by longitudinal historical data and the challenge of converting life histories into rectangular datasets compatible with statistical analysis systems. The logical next step is comparing life courses across local and national databases, and they propose a strategy for sharing historical longitudinal data based on an intermediate data structure (IDS) that can be adopted by all databases. They describe the benefits of the IDS approach and activities that will advance the goals of simplifying and promoting research with longitudinal historical data.' (author's abstract

Blowin' Down the Road: Investigating Bilateral Causality Between Dust Storms and Population in the Great Plains

Recently, the National Academy of Sciences concluded “it is clear thatpopulation and the environment are usually interrelated . . . ”. This paper directlytests the expected interrelationship using annual county-level population estimatesprovided by the U.S. Census Bureau and annual counts of dust storms from the1960s, '70s, and '80s at weather stations situated throughout the U.S. GreatPlains. In doing so, it implements a research design that extends methods (farremoved from conventional demography) for pure time series analysis withmultilevel regression models. The result is a method for causal modeling in paneldata that produces, in this application, evidence of bilateral causality betweenpopulation size and deleterious environmental conditions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43522/1/11113_2004_Article_5144455.pd

Building Partnerships Among Social Science Researchers, Institution-based Repositories and Domain Specific Data Archives

In developing and debating digital repositories, the digital library world has devoted more attention to their missions and roles in supporting access to and stewardship of academic research output than to discussing discipline, or domain, specific digital repositories. This is especially interesting, given that in social science these domain-specific repositories have been in existence for many decades. The goal of this paper is to juxtapose these two kinds of repositories and to suggest ways that they can help build partnerships between themselves and with the research community. It is based on the fundamental idea that all the parties involved share important goals, and that by working together these goals can be advanced successfully. The paper begins by characterizing the life cycle of social science research, before turning to key elements of the two different kinds of repositories, and our recommendation that researchers and the two different kinds of repositories can forge partnerships. The paper’s key message is that by visualizing the role of repositories explicitly in the life cycle of the social science research enterprise, the ways that the partnerships work will be clear. These workings can be seen as a sequence of reciprocal information flows between parties to the process, triggers that signal that one party or another has a task to perform, and hand-offs of information from one party to another that take place at crucial moments. This approach envisions both cooperation and specialization. The researcher produces the scientific product, both data and publications; the institutional repository has specialized knowledge of campus conditions and the opportunity to interact frequently with the researcher; and the domain-specific repository has specialized knowledge of approaches to data in a specific scientific field, for example domain-specific metadata standards, as well as the ability to give high-impact exposure to research products.http://deepblue.lib.umich.edu/bitstream/2027.42/41214/1/dig-repositories-green-gutmann-072006.pd

Dustbowl Legacies: Long Term Change and Resilience in the Shortgrass Steppe

http://deepblue.lib.umich.edu/bitstream/2027.42/61279/1/Sylvester.Gutmann.dustbowl legacies.pd

Will Today’s Data Be Here Tomorrow? Measuring The Stewardship Gap

Stakeholders in scholarly research are paying increased attention to stewardship of digital research data¹ for the purposes of advancing scientific discovery, driving innovation, and promoting trust in science and scholarship. However, little is known about the total amounts, characteristics, and sustainability of data that could be used for these purposes. The Stewardship Gap is an 18-month project funded by the Alfred P. Sloan Foundation to understand issues in defining metrics for and measuring the stewardship gap: the potential gap between the amount of valuable data produced through sponsored projects in the United States and the amount that is effectively stewarded and made accessible. This paper reports on the first phase of the project, which sought to develop an instrument to gather information about research data sustainability from a broad variety of researchers and research disciplines and make progress toward the ultimate goals of 1) shedding light on the size, characteristics, and sustainability of valuable sponsored research data and creative work in the United States, and 2) recommending actions stakeholders can take to address the stewardship gap if one is found to exist

Changing Agrarian Landscapes Across America: A Comparative Perspective

http://deepblue.lib.umich.edu/bitstream/2027.42/60436/1/Sylvester.changing landscapes.pd

A Reconfiguration of Census Tabulations: Maintaining Historical Consistency of Aggregate Industrial Categories at the County-Level

Consistent measures are imperative for conducting valid historical analyses. Collected in the long-form survey of the decennial census, employment data has traditionally been tabulated by aggregate industrial category for all counties. Starting in 2000, the industrial coding scheme drastically changed. In response, we develop a methodology to formulate “geographically-sensitive” conversion factors that reconfigure NAISC-based tabulations into long-established SIC categories.This research has been supported by Grant Number P01 HD045753 from the National Institute of Child Health and Human Development.http://deepblue.lib.umich.edu/bitstream/2027.42/57739/1/ICPSR-WP-No1-Witkowksi-Gutmann.pd