The data‐index: An author‐level metric that values impactful data and incentivizes data sharing

Hood, Amelia S. C.; Sutherland, William J.

doi:10.1002/ece3.8126

Cited by 13 publications

(22 citation statements)

References 57 publications

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“…On the other side, it is possible that we only detected the final portion of a decline caused by processes occurring further in the past such as habitat modification, reproductive interference by R. dalmatina or stochastic events. This points out the importance of long‐term monitoring programmes to identify drivers of population decline in order to plan appropriate conservation measures (Falaschi et al, 2019; Hood & Sutherland, 2021).…”

Section: Discussionmentioning

confidence: 99%

Similar species, different fates: Abundance dynamics in spatially structured populations of common and threatened frogs

Dalpasso

Ficetola

Giachello

et al. 2022

Diversity and Distributions

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Aim Understanding which factors determine the variation in population size across space and time is crucial to plan sound conservation interventions. Amphibians are often characterized by large demographic changes, therefore a better understanding of factors driving these changes could help mitigate their global crisis. We investigated drivers of abundance dynamics of two similar frog species to understand why they met different fates in the same study area. Location Northern Italy. Methods In seven different years between 2004 and 2020, we performed repeated counts of egg masses of two similar frog species, the agile frog (Rana dalmatina) and the Italian agile frog (Rana latastei), in 31 wetlands, and used Bayesian models to estimate the relationships between frog abundance and candidate drivers acting at the scale of (i) site: wetland surface, shading percentage and the presence of the invasive red swamp crayfish (Procambarus clarkii); (ii) landscape: forest cover around wetlands; (iii) climate: yearly precipitation and (iv) spatially structured population (SSP): clutch incidence of the focal species and crayfish incidence in the surrounding landscape. Results The two species showed sharp differences in population size and trends: R. dalmatina was abundant and showed a stable trend throughout the entire study period; R. latastei showed low abundance in the first years and then almost disappeared. The abundance of R. dalmatina was positively related to forest cover, shading, wetland area and precipitation, while negatively related to the occurrence of invasive crayfish at both local and SSP level. R. latastei abundance increased with wetland area and precipitation, while models were not able to detect relationships with other factors. Main conclusions The high sensitivity to drought and demographic stochasticity could have contributed to the quasi‐extinction of R. latastei in the study area, highlighting that similar species can meet different fates even under the same environmental conditions.

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Section: Discussionmentioning

confidence: 99%

Similar species, different fates: Abundance dynamics in spatially structured populations of common and threatened frogs

Dalpasso

Ficetola

Giachello

et al. 2022

Diversity and Distributions

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“…There is also other work in assessing researchers while considering their data contributions. One example is the data-index which takes into account data publications and citations [15]. Other examples include the s-index [19] and Data Citation Index (DCI) [23,24].…”

Section: Improving Reputation-based Metricsmentioning

confidence: 99%

Assessing Scientific Contributions in Data Sharing Spaces

Adams

Spadea

Flynn

et al. 2023

Companion Proceedings of the ACM Web Conference 2023

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In the present academic landscape, the process of collecting data is slow, and the lax infrastructures for data collaborations lead to significant delays in coming up with and disseminating conclusive findings. Therefore, there is an increasing need for a secure, scalable, and trustworthy data-sharing ecosystem that promotes and rewards collaborative data-sharing efforts among researchers, and a robust incentive mechanism is required to achieve this objective. Reputation-based incentives, such as the h-index, have historically played a pivotal role in the academic community. However, the h-index suffers from several limitations. This paper introduces the SCIENCE-index, a blockchain-based metric measuring a researcher's scientific contributions. Utilizing the Microsoft Academic Graph and machine learning techniques, the SCIENCEindex predicts the progress made by a researcher over their career and provides a soft incentive for sharing their datasets with peer researchers. To incentivize researchers to share their data, the SCIENCE-index is augmented to include a data-sharing parameter. DataCite, a database of openly available datasets, proxies this parameter, which is further enhanced by including a researcher's data-sharing activity. Our model is evaluated by comparing the distribution of its output for geographically diverse researchers to that of the h-index. We observe that it results in a much more even spread of evaluations. The SCIENCE-index is a crucial component in constructing a decentralized protocol that promotes trust-based data sharing, addressing the current inequity in dataset sharing. The work outlined in this paper provides the foundation for assessing scientific contributions in future data-sharing spaces powered by decentralized applications.

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“…A more granular methodology of research evaluation can also benefit researchers with publications that may not see heavy citation activity, but whose overall contributions as data producers have significant impact across the community. Adopting a contributor evaluation model based on data citations (for example, the “data-index” proposed by Hood et al 13 ) thus offers improvements in equity and transparency over more traditional metrics grounded in the authorship of scientific publications.…”

Section: Introductionmentioning

confidence: 99%

Identifying genomic data use with the Data Citation Explorer

Byers,

Parker,

Beecroft

et al. 2024

Preprint

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Increases in sequencing capacity, combined with rapid accumulation of publications and associated data resources, have increased the complexity of maintaining associations between literature and genomic data. As the volume of literature and data have exceeded the capacity of manual curation, automated approaches to maintaining and confirming associations among these resources have become necessary. Here we present the Data Citation Explorer (DCE), which discovers literature incorporating genomic data whether or not provenance was clearly indicated. This service provides advantages over manual curation methods including consistent resource coverage, metadata enrichment, documentation of new use cases, and identification of conflicting metadata. The service reduces labor costs associated with manual review, improves the quality of genome metadata maintained by the U.S. Department of Energy Joint Genome Institute (JGI), and increases the number of known publications that incorporate its data products. The DCE facilitates an understanding of JGI impact, improves credit attribution for data generators, and can encourage data sharing by allowing scientists to see how reuse amplifies the impact of their original studies.

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The data‐index: An author‐level metric that values impactful data and incentivizes data sharing

Cited by 13 publications

References 57 publications

Similar species, different fates: Abundance dynamics in spatially structured populations of common and threatened frogs

Similar species, different fates: Abundance dynamics in spatially structured populations of common and threatened frogs

Assessing Scientific Contributions in Data Sharing Spaces

Identifying genomic data use with the Data Citation Explorer

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