Practical Application of a Data Stewardship Maturity Matrix for the NOAA &lt;i&gt;OneStop&lt;/i&gt; Project

Peng, Ge; Milan, A.; Ritchey, N. A.; Partee, Robert P.; Zinn, Sonny; McQuinn, Evan; Casey, Kenneth S.; Lemieux, Paul; Ionin, Raisa; Jones, P. R.; Jakositz, Arianna; Collins, D. R.

doi:10.5334/dsj-2019-041

Cited by 13 publications

(14 citation statements)

References 4 publications

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“…While traditional altmetrics have focused on journal articles as the primary research object of interest, the same approach may not be effective for data and software. Data system altmetrics should include already established input variables such as social media shares but should also explore other variables of interest, including measures of data stewardship such as metadata quality scores or data stewardship maturity matrix assessment scores (Peng et al, 2019). Similarly, software usage should be assessed by how widely a piece of code is supported by the community through measures such as forks on Github and incorporation into other tools and workflows.…”

Section: Understanding Scientific Impact Through Data System Measurementsmentioning

confidence: 99%

From Open Data to Open Science

Ramachandran

Bugbee

Murphy³

2021

Earth and Space Science

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Open science, as both a concept and a term, is increasing in popularity and usage. However, definitions, interpretations, and perceptions as to what the term "open science" means varies. Some definitions are fairly narrow and only focus on providing more open access to science as a body of knowledge. These narrow definitions place an emphasis on openly sharing scientific knowledge as early as possible in the research process (University of Cambridge, 2020). On the other hand, broader definitions of open science acknowledge that science is both a body of knowledge and a systematic method for thinking. Broad definitions place an emphasis on encouraging a culture of openness (Bartling & Friesike, 2014) that includes the entire process of conducting science (National Academies of Sciences, Engineering, & Medicine, 2018a, 2018b) and encourages open collaboration and access to knowledge (Vicente-Saez & Martinez-Fuentes, 2018). In its broadest definition, the term "open science" refers to a paradigm shift in how the methods of science are conducted. This expansive vision of open science acknowledges that rapid technology changes, primarily driven by the Internet, may enable a second scientific revolution that fundamentally changes research methods and standards across science. To complicate matters, the term "open science" is sometimes used interchangeably to represent various principles that support the broader idea of open science itself. These principles include ideas such as open data, open source software, open journal access, and reproducibility. For example, reproducibility, or the ability to verify another scientist's results, is enabled by the principles of open data, open code, and transparent methodologies, yet reproducibility itself is not equivalent to open science.While open science definitions are variable and ambiguous, the value of open science as both a concept and a paradigm change is accepted by the majority of the scientific community. Open science not only benefits the scientific endeavor itself but has also been shown to benefit individual researchers through increased citations and media attention, a larger collaborative network, and exposure to new career and funding opportunities (

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Section: Understanding Scientific Impact Through Data System Measurementsmentioning

confidence: 99%

From Open Data to Open Science

Ramachandran

Bugbee

Murphy³

2021

Earth and Space Science

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“…The concept of the data maturity matrix is to evaluate the basic characteristics of a dataset initiated by the World Meteorological Organization (WMO) to develop technical guidance and standards for collecting, processing, and managing datasets. The assessment of the maturity of the individual dataset is essential to guarantee and further improve the documentation, storage, and dissemination of datasets that are applicable for users (Peng et al 2019).…”

Section: Data Maturity Matrixmentioning

confidence: 99%

Sea Surface Temperature Intercomparison in the Framework of the Copernicus Climate Change Service (C3S)

et al. 2021

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A joint effort between the Copernicus Climate Change Service (C3S) and the Group for High Resolution Sea Surface Temperature (GHRSST) has been dedicated to an intercomparison study of eight global gap-free Sea Surface Temperature (SST) products to assess their accurate representation of the SST relevant to climate analysis. In general, all SST products show consistent spatial patterns and temporal variability during the overlapping time period (2003-2018). The main differences between each product are located in western boundary current and Antarctic Circumpolar Current regions. Linear trends display consistent SST spatial patterns among all products and exhibit a strong warming trend from 2012 to 2018 with the Pacific Ocean basin as the main contributor. SST discrepancy between all SST products is very small compared to the significant warming trend. Spatial power spectral density shows that the interpolation into 1° spatial resolution has negligible impacts on our results. The global mean SST time series reveals larger differences among all SST products during the early period of the satellite era (1982-2002) when there were fewer observations, indicating that the observation frequency is the main constraint of the SST climatology. The maturity matrix scores, which present the maturity of each product in terms of documentation, storage, and dissemination but not the scientific quality, demonstrate that ESA-CCI and OSTIA SST are well documented for users' convenience. Improvements could be made for MGDSST and BoM SST. Finally, we have recommended that these SST products can be used for fundamental climate applications and climate studies (e.g. El Nino).

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“…Figure3: A structural diagram and practices for capturing and representing dataset quality information for a given quality dimension, attribute, evaluation method and results, along with evaluation metadata. Adapted from Figure6inPeng et al (2019a).…”

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confidence: 99%

International Community Guidelines for Sharing and Reusing Quality Information of Individual Earth Science Datasets

Peng¹,

Lacagnina²,

Downs³

et al. 2021

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Under the auspices of the Earth Science Information Partners (ESIP) and with collaboration among the ESIP Information Quality Cluster (IQC), the Barcelona Supercomputing Center (BSC) Evaluation and Quality Control (EQC) team, and the Australia/New Zealand Data Quality Interest Group (AU/NZ DQIG), a community effort has been undertaken by international Earth Science domain experts. The objective of this effort is to develop global community guidelines with practical recommendations to promote sharing and reusing of quality information at the dataset level, leveraging the experiences and expertise of a team of interdisciplinary domain experts and community best practices. The community guidelines aim to help stakeholders such as science data centers, repositories, data producers and publishers, data managers and stewards, etc., i) to capture and represent quality information of their datasets in a way that is in line with the FAIR guiding principles; ii) to allow for the maximum trust, sharing, reuse and value of their datasets; and iii) to enable global access to and integration of dataset quality information. The vision of developing these guidelines is to promote the creation and use of freely and openly shared dataset quality information that is consistently described, readily available in community standardized formats, and capable of being integrated across commonly-used Earth science systems and tools for search and access with explicitly expressed usage licenses.

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Practical Application of a Data Stewardship Maturity Matrix for the NOAA <i>OneStop</i> Project

Cited by 13 publications

References 4 publications

From Open Data to Open Science

From Open Data to Open Science

Sea Surface Temperature Intercomparison in the Framework of the Copernicus Climate Change Service (C3S)

International Community Guidelines for Sharing and Reusing Quality Information of Individual Earth Science Datasets

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