Assessing Stewardship Maturity of the Global Historical Climatology Network-Monthly (GHCN-M) Dataset: Use Case Study and Lessons Learned

Peng, Ge; Lawrimore, J. H.; Lief, Christina; Baldwin, Richard; Ritchey, N. A.; Brinegar, Danny; Greco, Stephen A. Del; Toner, Valerie

doi:10.1045/november2016-peng

Cited by 6 publications

(10 citation statements)

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“…A previous pilot NCEI DSMM use case study revealed that it is very beneficial to carry out assessment and review by a team -consisting of members from the Integrated Product Team (IPT), the Data Steward, and the DSMM SME (Peng et al 2016). Within NCEI, an IPT usually consists of a data product SME or POC (Point-Of-Contact), an archive specialist, and an operation or access specialist.…”

Section: Review and Baseline Processmentioning

confidence: 99%

“…As a part of the vetting process, the DSMM has been applied to various different types of datasets managed by various different projects or different organizations (e.g., Ritchey and Peng 2015;Hou et al 2015;Peng et al 2016). These use case studies have improved the maturity of the DSMM.…”

Section: Introductionmentioning

confidence: 99%

“…These use case studies have improved the maturity of the DSMM. They have also helped identify gaps in organizational procedures or systems (e.g., Peng et al 2016;Grace Peng, personal communication).…”

Section: Introductionmentioning

confidence: 99%

“…For example, if a project needs its data product to be at Level 3 for the Usability key component, making the product documents and source code publicly available should be one of the project requirements and on the product checklist. Due to the progressive and actionable nature of the criteria, the DSMM can also help create a roadmap for improving the stewardship maturity on a data set level (e.g., Peng et al 2016).…”

Section: Introductionmentioning

confidence: 99%

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

Peng

Milan

Ritchey

et al. 2019

CODATA

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Assessing the stewardship maturity of individual datasets is an essential part of ensuring and improving the way datasets are documented, preserved, and disseminated to users. It is a critical step towards meeting U.S. federal regulations, organizational requirements, and user needs. However, it is challenging to do so consistently and quantifiably. The Data Stewardship Maturity Matrix (DSMM), developed jointly by NOAA's National Centers for Environmental Information (NCEI) and the Cooperative Institute for Climate and Satellites-North Carolina (CICS-NC), provides a uniform framework for consistently rating stewardship maturity of individual datasets in nine key components: preservability, accessibility, usability, production sustainability, data quality assurance, data quality control/monitoring, data quality assessment, transparency/traceability, and data integrity. So far, the DSMM has been applied to over 800 individual datasets that are archived and/or managed by NCEI, in support of the NOAA's OneStop Data Discovery and Access Framework Project. As a part of the OneStop-ready process, tools, implementation guidance, workflows, and best practices are developed to assist the application of the DSMM and described in this paper. The DSMM ratings are also consistently captured in the ISO standard-based dataset-level quality metadata and citable quality descriptive information documents, which serve as interoperable quality information to both machine and human end-users. These DSMM implementation and integration workflows and best practices could be adopted by other data management and stewardship projects or adapted for applications of other maturity assessment models.

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Section: Review and Baseline Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Peng

Milan

Ritchey

et al. 2019

CODATA

Self Cite

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“…Over 700 + Earth Science data products were assessed utilizing MM-Stew, with most of the work done manually by NOAA OneStop Metadata Content Editors as a part of the OneStop-ready process (e.g., Ritchey et al 2016, Hou et al 2015Peng et al 2016b). The OneStop Metadata team, working with the NOAA Metadata Working Group, has developed a workflow and best practices to implement MM-Stew assessment ratings into ISO 19115 collection-level metadata records (Ritchey et al 2016;Peng et al 2017).…”

Section: D) Data Product Lifecycle-stages-based Maturity Assessment Mmentioning

confidence: 99%

The State of Assessing Data Stewardship Maturity – An Overview

Peng¹

2017

Preprint

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Data stewardship encompasses all activities that preserve and improve the information content, accessibility, and usability of data and metadata. Recent regulations, mandates, policies, and guidelines set forth by the U.S. government, federal other, and funding agencies, scientific societies and scholarly publishers, have levied stewardship requirements on digital scientific data. This elevated level of requirements has increased the need for a formal approach to stewardship activities that supports compliance verification and reporting. Meeting or verifying compliance with stewardship requirements requires assessing the current state, identifying gaps, and, if necessary, defining a roadmap for improvement. This, however, touches on standards and best practices in multiple knowledge domains. Therefore, data stewardship practitioners, especially these at data repositories or data service centers or associated with data stewardship programs, can benefit from knowledge of existing maturity assessment models. This article provides an overview of the current state of assessing stewardship maturity for federally funded digital scientific data. A brief description of existing maturity assessment models and related application(s) is provided. This helps stewardship practitioners to readily obtain basic information about these models. It allows them to evaluate each model's suitability for their unique verification and improvement needs.

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Monthly potential evapotranspiration estimated using the Thornthwaite method with gridded climate datasets in Southeastern Brazil

Santos,

Abreu

et al. 2024

Theor Appl Climatol

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Assessing Stewardship Maturity of the Global Historical Climatology Network-Monthly (GHCN-M) Dataset: Use Case Study and Lessons Learned

Cited by 6 publications

References 0 publications

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

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

The State of Assessing Data Stewardship Maturity – An Overview

Monthly potential evapotranspiration estimated using the Thornthwaite method with gridded climate datasets in Southeastern Brazil

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