Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment

Louise H. Patterton; Theo J. D. Bothma; Martie J. van Deventer

doi:10.5334/dsj-2024-011

Figures & Tables

Table 1

Documented factors leading to at-risk data.

RISK FACTORS	DOCUMENTED INSTANCES
Deterioration of the record	Hachileka 2015; Arrouays et al. 2017
Catastrophic loss of records	Levitus 2012; Arrouays et al. 2017
Loss of human knowledge and skills	Wyborn et al. 2015; Mavraki et al. 2016
Outdated format and media	Muller 2015; Research Data Alliance 2019
Substandard quality	Brunet & Jones 2011; Mavraki et al. 2016
Missing or displaced data	Levitus 2012; Wyborn et al. 2015
Perceived data value	Nordling 2010; Griffin 2015
Lack of awareness	Griffin 2015; Schumacher & VandeCreek 2015
Changing priorities	Muller 2015; Arrouays et al. 2017
Metadata and documentation issues	Thompson, Davenport Robertson & Greenberg 2014; Wyborn et al. 2015; Mavraki et al. 2016
Government funding/administrative policy	Gaudin 2017; University of Nevada 2017
Non-digital formats	Levitus 2012; Thompson, Davenport Robertson & Greenberg 2014
Archiving/preservation policy	Downs & Chen 2017; Griffin 2015
Data in one location only	Murillo 2014; Gaudin 2017
Substandard data management practices	Levitus 2012; Muller 2015
Non-trustworthy copy	Guest Blogger 2017

Table 2

Nature and number of data rescue activities.

DATA RESCUE ACTIVITIES EXECUTED	NUMBER
Uploaded data to a repository	n = 3
Added metadata to data	n = 3
Ensured data have backups	n = 2
Ensured digital storage space is sufficient	n = 1
Created and adhered to a data management plan	n = 1
Retrieved data after document management system failure	n = 1
Kept sensitive data offline	n = 1
Outsourced data rescue	n = 1
Retrieved data after data breach/ransomware incident	n = 1

[i] ‘n’ refers to the number of interviewed RGLs who had stated during their interview that the group had performed the indicated data rescue activities.

Table 3

Data rescue stages and accompanying activities.

DATA RESCUE STAGE	ACTIVITIES
Preparing for data rescue	Locate at-risk data Create data inventory Assess at-risk data Assess data rescue resources Make data rescue decision
Planning for data rescue	Select data rescue team Draft data rescue project plan Draft data management plan for the data
Storing and preserving the data	Clean the at-risk data Prepare and clean the storage area Lable and store the at-risk data accordingly
Digitising/converting the data	Create digitisation inventory Create predetermined files and folders Image, scan, key, or convert the data Quality control and validate
Describing the data	Select applicable repository, and examine its metadata standard Draft metadata template Complete metadata document Complete data documentation document
Sharing the data	Upload data to selected repository Ensure metadata and data documentation accompany the data Add DOI information to all relevant documents
Archiving the data	Select secure and stable preservation location Ensure data are in preservation format Upload data Ensure regular monitoring takes place
Project closure	Thank all parties involved Create awareness of rescued data Share data rescue learnings Implement changes to data rescue model if required Draft and distribute final project report

Risky Business: Data-At-Risk in a Dynamic and Evolving Multidisciplinary Research Environment

Figures & Tables

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Paradigm

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