More Data, Less Process? The Applicability of MPLP to Research Data

Lafferty-Hess, Sophia; Christian, Thu-Mai Lewis

doi:10.29173/iq907

Cited by 3 publications

(2 citation statements)

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“…Increasingly, MPLP is used not only for paper archives and digitized archives but also for research data and other born-digital archives. 52 In a 2014 article, Cyndi Shein points out that the literature on born-digital stewardship has often come from well-funded institutions with high-profile humanities collections (such as the Salman Rushdie archive at Emory University). These privileged organizations can afford to implement expensive access models, such as emulation or item-level description.…”

Section: Applying Mplp To Digital Archivesmentioning

confidence: 99%

More Data, Less Process: A User-Centered Approach to Email and Born-Digital Archives

Jaillant

2022

The American Archivist

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The overall aim of this article is to push for access to born-digital archives, including email archives. It argues that the digital revolution has led to huge changes, but it also brought us back to an earlier situation. The world of big (digital) data is not so different from the world of big (paper) data. There is a danger of repeating the mistakes that were made in the twentieth century with large paper archives, which have often remained uncataloged, hidden, and inaccessible to users. The first section looks at the impact of the More Product, Less Process (MPLP) movement on archival repositories over the past fifteen years. Originally conceived as a response to the huge increase in paper records and uncataloged collections, MPLP has been increasingly applied to digitized collections to increase access. However, few institutions have applied MPLP to born-digital collections, and accessibility remains a huge problem. In the next section, this article presents the kind of research that can be done once access to these born-digital collections is achieved. The final section examines the MPLP approach in relation to artificial intelligence/machine learning.

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Section: Applying Mplp To Digital Archivesmentioning

confidence: 99%

More Data, Less Process: A User-Centered Approach to Email and Born-Digital Archives

Jaillant

2022

The American Archivist

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“…Similarly, a recent study by Lafia et al [14] classified and defined a schema of data curation actions to examine the actions most frequently performed by ICPSR curators including "initial review and planning, data transformation, metadata, documentation, quality checks, communication, other, and noncuration work." A number of repositories have published case studies of their data curation pipelines, workflows, and services [5,[15][16][17][18][19] and in some cases proposed curation models to support the sharing of quality data [19,20]. While this work lays a firm foundation for understanding potential data curation workflows and practices, in many ways current data curation practices remain mostly opaque to those outside the curation process with significant variation in scope and implementation of data curation activities across repositories.…”

Section: Introductionmentioning

confidence: 99%

Understanding the value of curation: A survey of US data repository curation practices and perceptions

Johnston,

Curty,

Braxton

et al. 2024

PLoS ONE

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Data curators play an important role in assessing data quality and take actions that may ultimately lead to better, more valuable data products. This study explores the curation practices of data curators working within US-based data repositories. We performed a survey in January 2021 to benchmark the levels of curation performed by repositories and assess the perceived value and impact of curation on the data sharing process. Our analysis included 95 responses from 59 unique data repositories. Respondents primarily were professionals working within repositories and examined curation performed within a repository setting. A majority 72.6% of respondents reported that “data-level” curation was performed by their repository and around half reported their repository took steps to ensure interoperability and reproducibility of their repository’s datasets. Curation actions most frequently reported include checking for duplicate files, reviewing documentation, reviewing metadata, minting persistent identifiers, and checking for corrupt/broken files. The most “value-add” curation action across generalist, institutional, and disciplinary repository respondents was related to reviewing and enhancing documentation. Respondents reported high perceived impact of curation by their repositories on specific data sharing outcomes including usability, findability, understandability, and accessibility of deposited datasets; respondents associated with disciplinary repositories tended to perceive higher impact on most outcomes. Most survey participants strongly agreed that data curation by the repository adds value to the data sharing process and that it outweighs the effort and cost. We found some differences between institutional and disciplinary repositories, both in the reported frequency of specific curation actions as well as the perceived impact of data curation. Interestingly, we also found variation in the perceptions of those working within the same repository regarding the level and frequency of curation actions performed, which exemplifies the complexity of a repository curation work. Our results suggest data curation may be better understood in terms of specific curation actions and outcomes than broadly defined curation levels and that more research is needed to understand the resource implications of performing these activities. We share these results to provide a more nuanced view of curation, and how curation impacts the broader data lifecycle and data sharing behaviors.

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