Persistence Statements: Describing Digital Stickiness

Kunze, John; Calvert, Scout; DeBarry, Jeremy D.; Hanlon, Matthew; Janée, Greg; Sweat, Sandra

doi:10.5334/dsj-2017-039

Cited by 3 publications

(3 citation statements)

References 11 publications

(8 reference statements)

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“…There has been some research in this area, but more is needed. For instance, Puente and Díaz [57] look at using mindmaps in wiki refactors; Greenberg et al, discuss the need for a "community-driven metadata vocabulary application" that would support collaborative definition negotiation and term selection [30]; and Kunze et al describe a system for supporting the evaluation of "digital stickiness" of a term or identifier -basically, a way of assessing the potential longevity of a resources [46]. These approaches are promising but further workflows and workbenches are needed that tie these processes and resources together, and thereby better support the articulation work of semantic refactoring.…”

Section: Implications For Other Cooperative Classification Workersmentioning

confidence: 99%

Transforming Taxonomic Interfaces

Thomer

Twidale

Yoder

2018

Proc. ACM Hum.-Comput. Interact.

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If scientific research can be described as "arm's length" cooperative work, then the sciences engaged in the creation and maintenance of cooperatively built classification systems might be said to require extremely long arms; workers must reach across great distances of time, space and awareness to independently contribute to the creation and maintenance of a conceptual infrastructure. This is particularly the case for the field of biological taxonomy, in which researchers across the globe have, for more than three hundred years, cooperatively developed a massive knowledge organization system describing all life on earth. As taxonomists move from paper-based workflows to born-digital, data-first modes of publishing, new tools and approaches are needed to support their work. In this paper, we present research conducted as part of the "Transforming Taxonomic Interfaces" project aimed at improving interfaces for taxonomic software. We describe biological taxonomy in the context of CSCW, and identify key strategies taxonomists deploy to facilitate loosely coupled cooperative work. We also contribute a discussion of semantic refactoring, a unique kind of "articulation work" entailed in developing, maintaining, and migrating classification systems. This work has implications for the design and study of knowledge organization systems and infrastructure, classification research, and for the development of general semantic web tools and software as well as those specifically for biological taxonomy. CCS Concepts: • Information systems → Collaborative and social computing systems and tools; • Human-centered computing → Computer supported cooperative work; Empirical studies in collaborative and social computing; • Applied computing → Life and medical sciences;

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Section: Implications For Other Cooperative Classification Workersmentioning

confidence: 99%

Transforming Taxonomic Interfaces

Thomer

Twidale

Yoder

2018

Proc. ACM Hum.-Comput. Interact.

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“…Research on metadata longevity Sugimoto et al, 2016) has resulted in a framework solution for preserving metadata. Additionally, Kunze et al (2016a;2016b) present complementary work developing a persistence vocabulary. These are significant initiatives that can help further formalize our understanding of preservation as a principle for smart metadata.…”

Section: Expert Reviewmentioning

confidence: 99%

Big Metadata, Smart Metadata, and Metadata Capital: Toward Greater Synergy Between Data Science and Metadata

Greenberg

2017

Journal of Data and Information Science

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Purpose: The purpose of the paper is to provide a framework for addressing the disconnect between metadata and data science. Data science cannot progress without metadata research. This paper takes steps toward advancing the synergy between metadata and data science, and identifies pathways for developing a more cohesive metadata research agenda in data science.Design/methodology/approach: This paper identifies factors that challenge metadata research in the digital ecosystem, defines metadata and data science, and presents the concepts big metadata, smart metadata, and metadata capital as part of a metadata lingua franca connecting to data science. Findings:The "utilitarian nature" and "historical and traditional views" of metadata are identified as two intersecting factors that have inhibited metadata research. Big metadata, smart metadata, and metadata capital are presented as part of a metadata lingua franca to help frame research in the data science research space. Research limitations:There are additional, intersecting factors to consider that likely inhibit metadata research, and other significant metadata concepts to explore. Practical implications:The immediate contribution of this work is that it may elicit response, critique, revision, or, more significantly, motivate research. The work presented can encourage more researchers to consider the significance of metadata as a research worthy topic within data science and the larger digital ecosystem.Originality/value: Although metadata research has not kept pace with other data science topics, there is little attention directed to this problem. This is surprising, given that metadata is essential for data science endeavors. This examination synthesizes original and prior scholarship to provide new grounding for metadata research in data science.

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“…Over time, unlike journal references in papers, which may have a collective stable 'marker' or persistent identifier (PID) like a digital object identifier (DOI), allowing them to be identified and traced even if the journal's uniform resource locator (URL) 1 changes, the URLs of web-based references might become dysfunctional (i.e., links may become broken), or the URL might disappear altogether if the website shuts down or ceases to exist, a phenomenon known as reference rot (Burnhill et al, 2015). Kunze et al (2017) suggested the establishment of a lexicon to describe PIDs that would allow a user, such as an academic, to evaluate the level of durability of an identifier, including of a provider, before deciding whether to cite it. Entities that issue PIDs can enhance the reliability of a PID by following several management principles (McMurry et al, 2017).…”

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confidence: 99%

Archiving website‐based references in academic papers: Problems caused by reference rot, potential solutions and limitations

Silva

Nazarovets

2023

Learned Publishing

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Key points Web‐based references form an integral part of academic culture and literature, as well as scientific communication. The preservation of web‐based references that are cited in‐text or in reference lists of academic papers is essential to ensure the integrity of knowledge preservation. When access or links to web‐based resources and references disappear, or if they are dysfunctional, these phenomena are collectively referred to as reference rot. Even though reference rot degrades the integrity of information in academic papers, no industry‐wide solutions currently exist. Given its prominence, we propose the Internet Archive as a possible solution to address reference rot, but also note its weaknesses and limitations.

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Persistence Statements: Describing Digital Stickiness

Cited by 3 publications

References 11 publications

Transforming Taxonomic Interfaces

Transforming Taxonomic Interfaces

Big Metadata, Smart Metadata, and Metadata Capital: Toward Greater Synergy Between Data Science and Metadata

Archiving website‐based references in academic papers: Problems caused by reference rot, potential solutions and limitations

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