PlumX is an altmetrics service that allows automatic monitoring and reporting of online activity surrounding scholarly digital objects. While largely targeted at universities looking to measure impact of faculty research, it can be used to track impact of other digital library resources with DOIs, Handles, and other kinds of persistent identifiers.
Though PlumX is best known for its flagship PlumX Metrics dashboard product, the service is now offered through a PlumX integration into existing dashboards within Digital Commons institutional repository software and the research information management system, Pure. These integrated metrics are viewable, sortable, and exportable in a manner similar to the legacy PlumX Metrics dashboard product. A Digital Commons platform subscription is required for digital libraries interested in using PlumX data to assess their collections at scale; collections would need to be hosted on the Digital Commons platform.
Users interested in gathering “one-off” PlumX data for a digital object that has a DOI can use the free PlumX Metrics artifact widget1. The PlumX Metrics artifact widget is also freely available for objects that have a DOI and can be integrated into item record pages for digital objects, quickly and concisely showing the amount and type of attention a digital object has received.
PlumX metrics include news, blogs, social media, and Wikipedia mentions, citations, and usage statistics. Several PlumX metrics data sources are historical (e.g., EBSCO or CiteULike metrics) and/or offered only to past subscribers of the PlumX Metrics dashboard that had previously reported their data to PlumX (e.g., ePrints usage statistics).
There are 67 different types of digital objects that PlumX can gather metrics about including traditional scholarly outputs (articles, books, datasets) to audio files, images, maps, and much more.
PlumX requires that an output has three things:
For most data sources, PlumX works by monitoring the source for links to a specified domain name like a digital library website. Any time a link to said domain is shared in an PlumX data source, PlumX follows the link and looks for specific meta tags on the webpage. In some cases, PlumX attempts to match persistent identifiers found in an item record page to other known identifiers in their database, or perform string matching to identify persistent identifiers URLs that have been shared in a post. If the webpage meta tags include a persistent identifier like a Handle (among other metadata), PlumX can verify that the page shared contains a scholarly object. PlumX then indexes the mention of the scholarly object, associating it with other mentions to the same scholarly object.
Digital libraries interested in using PlumX Metrics artifact widgets to track engagement with their online content should have two key technologies in place for the service to work: persistent identifiers (ideally DOIs) minted for each item record to be tracked, and properly formatted site meta tags that share basic item record metadata in Dublin Core format. These requirements allow PlumX to accurately track engagement for online scholarly resources in a manner that is relatively immune to link rot and misattribution.
Practitioners should follow the practices laid out in the “Ethical considerations and guidelines for the assessment of use and reuse of digital content.” The Guidelines are meant both to inform practitioners in their decision-making, and to model for users what they can expect from those who steward digital collections.
According to Plum Analytics’ parent company (Elsevier) they can collect a wide range of user data based on direct user input, third-party sources, and through automated technologies. This data includes a) personally identifiable data about users such as name, email address, postal address, phone number, social media handle, usernames and passwords, password hints and similar security information, b) device and usage data, and c) profile information, such as “educational, professional and other background information, such as your field of study, current position, practice area and areas of interests, gender, ORCID ID and photo.” and d) payment information such as credit or debit card numbers and government-issued ID numbers.
Plum Analytics’ privacy policy also states that they may use and share personal information with a user’s institution, all of Elsevier’s companies and service providers, and to legal entities as necessary. Additionally, personal information “may be stored and processed in your region or another country where Elsevier companies and their service providers maintain servers and facilities, including Australia, China, France, Germany, India, Ireland, the Netherlands, the Philippines, Singapore, the United Kingdom, and the United States.” 2
Wright State University. (2021). Special Collections and Archives.
Konkiel, Stacy; Dalmau, Michelle; Scherer, David. “Altmetrics and Analytics for Digital Special Collections and Institutional Repositories.” Figshare (2015).
Metrics Toolkit. (2021). https://www.metrics-toolkit.org/
Wong, E. Y., & Vital, S. M. (2017). PlumX: A tool to showcase academic profile and distinction. Digital Library Perspectives, 33(4), 305–313.
Torres-Salinas, D., Gumpenberger, C., & Gorraiz, J. (2017). PlumX As a Potential Tool to Assess the Macroscopic Multidimensional Impact of Books. Frontiers in Research Metrics and Analytics, 2.
Elsevier privacy principles. (2021). Elsevier.
Jobmann, A., Hoffmann, C. P., Künne, S., Peters, I., Schmitz, J., & Wollnik-Korn, G. (2014). Altmetrics for large, multidisciplinary research groups: Comparison of current tools. Bibliometrie – Praxis und Forschung, 3(1), 1-19.
Helping digital collections measure impact
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