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D-CRAFT can offer strategies to digital library practitioners interested in collecting data for a digital object reuse assessment. But what exactly is digital object reuse? How would a practitioner recognize it? To inform the development of D-CRAFT, the project team constructed a definition for digital object reuse – and, conversely, for digital object use. This page outlines the project team’s current definitions and provides examples of digital object use and reuse.
Members of the D-CRAFT project team first identified the need to establish digital object reuse recommended practices after completing a white paper on digital library user studies. That group compiled resources, conducted research, and drafted literature to assist those who are interested in evaluating users of digital repositories and their needs. The group released Surveying the Landscape: Use and Usability Assessment of Digital Libraries in December 2015. Members of the project team first derived digital object use and reuse definitions from research conducted during a subsequent research study, the Measuring Reuse project. During this study, organizers held focus groups with digital library practitioners to discuss assessment strategies and characteristics of digital object use and reuse. These results formed the foundation for the current definitions and identified examples. Practitioners can learn more about the development and complexities of these definitions by reading the project team’s 2022 publication “Toward a definition of digital object reuse”, which is openly accessible in an issue of Digital Library Perspectives.
The project team defines:
The project team also identified different examples of digital object use and reuse.
In “Toward a definition of digital object reuse,” the project team provides two broad digital object interactions that frequently indicate reuse: “any action [performed] outside of the initial repository or exposure point” and “a transformative act, either involving the object directly or its surroundings” (p. 384).
They organized the examples into varying levels of engagement between a user and a digital object. These levels of engagement span a spectrum, from simple to complex (what the project team termed as the “Use-Reuse Matrix”).
Examples of digital object use are frequently positioned among simple engagement categories. These have been deemed “passive interactions” by the project team because they can only indicate potential interest or value to the user. Typical examples include clicking on a link from a search result or viewing a digital object. Institutions collect these kinds of interactions as page views or clicks when they do assessment. While easy to gather, these simple engagement metrics lack the context for user engagement with digital objects. For example, “use” metrics cannot tell the difference between a user finding a digital object that they were searching for and a digital object that is accidentally clicked on or one that matches their search terms but not their need. Using only simple engagement metrics make it difficult to tell stories of impact or make informed collection development or digitization decisions.
Digital object reuse, on the other hand, provides more context for determining the impact of the digital object. The project team has called these “active interactions” because there is evidence that the user has an interest and/or finds value in the object. Examples of reuse frequently fall within the complex engagement categories and often are indicated by a user reproducing, enhancing, recontextualizing, or transforming a digital object. In these examples, users have taken additional steps beyond the digital repository to share the object with others or try to recreate or add context to a digital object. Metrics for “reuse” actions are harder to gather and assess because they take place outside the scope of the digital repository, but they make it easier to explain why the user found the object valuable. This toolkit was developed to provide digital repository practitioners with options for trying to gather this external evidence.
Digital library practitioners can see specific examples, as well as the detailed engagement categories, in the detailed Use-Reuse Matrix below. Practitioners can learn more about the matrix and its development in “Toward a definition of digital object reuse.”
|Use and Reuse Spectrum|
Passive interaction with a digital object that indicates potential interest and/or value to an external user
Active interaction with a digital object(s) that demonstrates an interest or value to an external user
To come into contact with a digital object
– Browsing digital repositories for content
– Clicking a link for a digital object
– Downloading digital objects
– Accessing a web archive
To view, read, listen, or expose oneself to the intellectual content of a digital object
– Watching a video online
– Reading an article
– Viewing a photograph
– Listening to a song
To change the medium or delivery of a digital object without changing the content itself
– Printing digital objects
– Scanning a document
To expose others to the intellectual content of a digital object by distributing a means of display or access, such as a link or DOI
– Displaying digital collection materials on social media or email
– Citing a digital object in a scholarly article without adding interpretation
– Citing a digital object in a Wikipedia article without adding interpretation
– Publishing/reposting content in online or print publication without adding interpretation
– Incorporating digital images into documentaries or movies without adding interpretation
To draw upon a digital object or dataset to validate or verify a previous study’s methods and/or results
– Confirming a journal article’s results by using an existing data set to reproduce its methods and conclusions
– Verifying a research study’s methodology by replicating its process using a different dataset
To add functionality or accessibility to a digital object
– Annotating an image or document
– Translating the text of a digital object from one language to another
– Transcribing a digital object
– Adjusting lighting or coloring of digital items in order to faithfully represent the original object
– Charting a dataset in a graph or infographic to communicate with others
To alter the surroundings or space that affect the meaning, purpose, or intent of a digital object
|– Aggregating metadata in a discovery tool|
– Curating sets of digital material, such as People of Color in Medieval European Art History
– Curriculum planning K-12 education, e.g. DocTeachs, LOC Teaching with Primary Sources, etc.
– Creating a Pinterest board of digital objects
– Citing a digital object in a scholarly article and adding interpretation
– Citing a digital object in a Wikipedia article and adding interpretation
– Publishing/reposting content in online or print publication that adds interpretation
– Incorporating digital images into documentaries or movies while adding interpretation
To change or alter a digital object substantially, resulting in a new, distinct entity, including, but not limited to recreations, versions, and mashups.
– Creating “then and now” photographs for an exhibit
– Painting, drawing, or otherwise artistically representing a digital object
– Combining two or more datasets for analysis
– Creating a GIF or meme from digital objects
– Revising an existing OER object with new content
– Overlaying a map with data points
– Adding color to a black and white photo or video in order to add artistic value to the original object
– Combining datasets from multiple sources and disciplines to produce a new result, intellectual framework, or model
As can be seen from the examples in this grid, digital object reuse involves more time and labor on the part of the user and therefore is not going to be as common as digital object use, may be untraceable, and is more time consuming for practitioners to track and measure. Therefore reuse alone cannot be considered the sole source of information for assessment purposes. Telling stories of impact or making collection development/digitization decisions are best served when a broad range of data points are used. The project team recommends using both use and reuse data points when doing digital object assessment.