Science Data Infrastructure for Preservation - Earth Science

The proper preservation of both current and historical scientific data will underpin a multitude of ecological, economic and political decisions in the future of our society. The SCIDIP-ES project addresses the long-term persistent storage, access and management needs of scientific data by providing preservation infrastructure services. Taking exemplars from the Earth Science domain we highlight the key preservation challenges and barriers to be overcome by the SCIDIP-ES infrastructure. SCIDIP-ES augments existing science data e-infrastructures by adding specific services and toolkits, which implement core preservation concepts, thus guaranteeing the long-term access to data assets across and beyond their designated communities.European Space Agency ESA-ESRIN, Italy, Alliance for Permanent Access, The Netherlands, Science and Technology Facility Council, United Kingdom

Long-Term Data Preservation Data Lifecycle, Standardisation Process, Implementation and Lessons Learned

Science and Earth Observation data represent today a unique and valuable asset for humankind that should be preserved without time constraints and kept accessible and exploitable by current and future generations. In Earth Science, knowledge of the past and tracking of the evolution are at the basis of our capability to effectively respond to the global changes that are putting increasing pressure on the environment, and on human society. This can only be achieved if long time series of data are properly preserved and made accessible to support international initiatives. Within ESA Member States and beyond, Earth Science data holders are increasingly coordinating data preservation efforts to ensure that the valuable data are safeguarded against loss and kept accessible and useable for current and future generations. This task becomes increasingly challenging in view of the existing 40 years’ worth of Earth Science data stored in archives around the world and the massive increase of data volumes expected over the next years from e.g., the European Copernicus Sentinel missions. Long Term Data Preservation (LTDP) aims at maintaining information discoverable and accessible in an independent and understandable way, with supporting information, which helps ensuring authenticity, over the long term. A focal aspect of LTDP is data Curation. Data Curation refers to the management of data throughout its life cycle. Data Curation activities enable data discovery and retrieval, maintain its quality, add value, and allow data re-use over time. It includes all the processes that involve data management, such as pre-ingest initiatives, ingest functions, archival storage and preservation, dissemination, and provision of access for a designated community. The paper presents specific aspects, of importance during the entire Earth observation data lifecycle, with respect to evolving data volumes and application scenarios. These particular issues are introduced in the section on 'Big Data' and LTDP. The Data Stewardship Reference lifecycle section describes how the data stewardship activities can be efficiently organised, while the following section addresses the overall preservation workflow and shows the technical steps to be taken during Data Curation. Earth Science Data Curation and preservation should be addressed during all mission stages - from the initial mission planning, throughout the entire mission lifetime, and during the post- mission phase. The Data Stewardship Reference Lifecycle gives a high-level overview of the steps useful for implementing Curation and preservation rules on mission data sets from initial conceptualisation or receipt through the iterative Curation cycle

CEOS Virtual Data Repositories for WGISS Data Assets

The Committee on Earth Observation Satellites (CEOS), established in 1984 to coordinate civil space-borne observations of the Earth, through its Working Group on Information Systems and Services (WGISS) has been working towards aligning data repositories held by each of the member international agencies. The CEOS agencies hold a vast amount of earth observation data across science domains. WGISS has been working to agree on community standards for data and information discovery and to increase the interoperability and alignment among the member data repositories

CEOS WGISS Common Data Framework for WGISS Connected Data Assets

This session will explore the benefits of having such a policy framework and future steps both domestically and internationally. Speakers can highlight current work being done to improve data interoperability, how the Common Framework is relevant for other data types, other countries and multinational organizations, and considerations for data management that have yet to be addressed in the Common Framework

Enabling FAIR research in Earth Science through research objects

Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement, research objects contain and describe scientific information and resources in a way compliant with the FAIR principles and sustain the development of key infrastructure and tools. This paper provides an account of the challenges, experiences and solutions involved in the adoption of FAIR around research objects over several Earth Science disciplines. During this journey, our work has been comprehensive, with outcomes including: an extended research object model adapted to the needs of earth scientists; the provisioning of digital object identifiers (DOI) to enable persistent identification and to give due credit to authors; the generation of content-based, semantically rich, research object metadata through natural language processing, enhancing visibility and reuse through recommendation systems and third-party search engines; and various types of checklists that provide a compact representation of research object quality as a key enabler of scientific reuse. All these results have been integrated in ROHub, a platform that provides research object management functionality to a wealth of applications and interfaces across different scientific communities. To monitor and quantify the community uptake of research objects, we have defined indicators and obtained measures via ROHub that are also discussed herein.Published550-5645IT. Osservazioni satellitariJCR Journa

EVER-EST: the platform allowing scientists to cross-fertilize and cross-validate data

Over recent decades large amounts of data about our Planet have become available. If this information could be easily discoverable, accessible and properly exploited, preserved and shared, it would potentially represent a wealth of information for a whole spectrum of stakeholders: from scientists and researchers to the highest level of decision and policy makers. By creating a Virtual Research Environment (VRE) tailored to the needs of Earth Science (ES) communities, the EVER-EST (http://ever-est.eu) project provides a range of both generic and domain specific data analysis and management services to support a dynamic approach to collaborative research. EVER-EST provides the means to overcome existing barriers to sharing of Earth Science data and information allowing research teams to discover, access, share and process heterogeneous data, algorithms, results and experiences within and across their communities, including those domains beyond Earth Science. EVER-EST is funded by the European Commission H2020 programme for three years starting in October 2015. The project is led by the European Space Agency (ESA) and involves some of the major European Earth Science data providers/users including NERC, DLR, INGV, CNR and SatCEN . The paper presents specific aspects of this collaboration platform in terms of infrastructure and implemented paradigms. Some case studies on cross-fertilization analysis are documented in order to show the process for creating knowledge and new data starting from collected data from different sources (e.g. from remote and social sensing). The paper concludes with few future outcomes

Call to action for global access to and harmonization of quality information of individual earth science datasets

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 describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science

Call to action for global access to and harmonization of quality information of individual earth science datasets

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 describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries