Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision-and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper GE PENG

High quality and well-managed climate data are the cornerstone of all climate services. Consistently assessing how well the data are managed is one way to establish or demonstrate the trustworthiness of the data. This paper presents the World Meteorological Organization's (WMO) Stewardship Maturity Matrix for Climate Data (SMM-CD) and the subsidiary SMM-CD for National and Regional Purposes (SMM-CD_NRP). Both these matrices have been developed with the support of the WMO and its High-Quality Global Data Management Framework for Climate (HQ-GDMFC). These self-assessment tools enable data managers to discover WMO recommended data stewardship practices, determine a roadmap for future development and improvement, as well as compare their process against other data providers. Datasets which have been maturity assessed are included in the WMO Climate Data Catalogue, where users can include the results of these maturity assessments into their decisionmaking process. The SMM-CD contains four categories (data access, usability and usage, quality management, and data management) each of which has a number of aspects, with scores assigned to one of five levels. A smaller number of categories in the SMM-CD_NRP are assigned to four levels appropriate for operationally produced datasets which are national or regional in scope. We explore a number of case studies where these matrices have been applied, as well as supply links to where the Guidance Documents and Assessment Templates (which may be updated) can be found.

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The Global Observing Systems Information Center (GOSIC), initiated in 1997 at the request of the Global Climate Observing System (GCOS) Steering Committee (see http://www.wmo.int/pages/prog/gcos/ Publications/gcos‐39.pdf), responds to a need identified by the global climate observing community for easier and more effective access to observational climate data and information. GOSIC manages an online portal providing an entry point for users of climate‐related global observing systems data and information systems. Following its initial development and implementation at the University of Delaware from 1997 to 2006, the U.S. National Oceanic and Atmospheric Administration's National Climatic Data Center (NCDC) assumed operational responsibility for GOSIC on behalf of the international climate observing and data user communities. The goal of GOSIC is to provide basic user services, including a description of the systems and their data as well as a tailored search capability that facilitates access to a worldwide set of observations and derived products. GOSIC's unique value is its ability to quickly link users, via a consistent and user‐friendly interface, to a wide range of data sets that reside at multiple data centers; the GOSIC portal (http://GOSIC.org) provides users with links to data, metadata, other search tools, and related climate‐observing information.

Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data and need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision- and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Community practical guidelines will allow for global access and harmonization of quality information at the level of individual Earth science datasets and support open science.