Shaping digital earth applications through open innovation – setting the scene for a digital earth living lab

Science and policy increasingly request for sustainable development and growth. Similarly, Digital Earth undergoes a paradigm shift to an open platform that actively supports user engagement. While the public becomes able to contribute new content, we recognize a gap in user-driven validation, feedback and requirements capture, and innovative application development. Rather than defining Digital Earth applications top down, we see a need for methods and tools that will help building applications bottom up and driven by community needs. These should include a technology toolbox of geospatial and environmental enablers, which allow to access functional building blocks and content in multiple ways, but – equally important – enable the collaboration within partially unknown stakeholder networks. The validation and testing in real-life scenarios will be a central requirement when approaching the Digital Earth 2020 goals, which were articulated recently. We particularly argue to follow a Living Lab approach for co-creation and awareness rising in relation to environmental and geospatial matters. We explain why and how such a Digital Earth Living Lab could lead to a sustainable approach for developing, deploying, and using Digital Earth applications and suggest a paradigm shift for Virtual Globes becoming forums for research and innovation

PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches

PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches

PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches

PaCTS 1.0: a crowdsourced reporting standard for paleoclimate data

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate datasets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new vs. legacy datasets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate datasets. Since such goals are at odds with present practices, we discuss a transparent path towards implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches

Destination Earth: Survey on “Digital Twins” technologies and activities, in the Green Deal area

Digital Twins have been around for decades, especially in industrial processes. However, with the recent advent of transformative digital technologies (i.e. IoT, AI, ML, Big Data analytics, and ubiquitous connectivity) Digital Twins are changing most of the society sectors, providing the most advance pattern to make the physical and the digital worlds interact. Naturally, this is also true for the scientific sector, and in particular those disciplines that are engaged in understanding and addressing the Global Change effects. Thanks to the Digital Twins growing development, for the first time, it is possible to envision a digital replica of important natural and social phenomena and processes, trying to anticipate their behaviour. There exist diverse definitions of Digital Twins, reflecting the diverse concerns of the industrial, scientific, and standardization sectors (in particular IEEE and ISO/IEC), which have been working on their description and realization. The main interaction features characterizing a Digital Twin are: - Interoperability; - Information Model; - Data Exchange; - Administration; - Synchronization; - Push mode (Publish Subscribe). According the scientific research, there is still the need to address the following challenges to push Digital Twins implementation and effective use: - Unify data and model standards; - Share data and models; - Innovate on services; - Establish forums. In industry, Digital Twins are well used in “vertical” sectors/application areas, including: manufacturing, energy, smart cities, farming, building, healthcare. For the applied scientific and research areas, this preliminary study recognized several areas.JRC.B.6-Digital Econom

Report on the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3)

This report records and discusses the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3). The report includes a description of the keynote presentation of the workshop, which served as an overview of sustainable scientific software. It also summarizes a set of lightning talks in which speakers highlighted to-the-point lessons and challenges pertaining to sustaining scientific software. The final and main contribution of the report is a summary of the discussions, future steps, and future organization for a set of self-organized working groups on topics including developing pathways to funding scientific software; constructing useful common metrics for crediting software stakeholders; identifying principles for sustainable software engineering design; reaching out to research software organizations around the world; and building communities for software sustainability. For each group, we include a point of contact and a landing page that can be used by those who want to join that group's future activities. The main challenge left by the workshop is to see if the groups will execute these activities that they have scheduled, and how the WSSSPE community can encourage this to happen

StraboSpot data system for structural geology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.StraboSpot is a geologic data system that allows researchers to digitally collect, store, and share both field and laboratory data. StraboSpot is based on how geologists actually work to collect field data; although initially developed for the structural geology research community, the approach is easily extensible to other disciplines. The data system uses two main concepts to organize data: spots and tags. A spot is any observation that characterizes a specific area, a concept applicable at any spatial scale from regional to microscopic. Spots are related in a purely spatial manner, and consequently, one spot can enclose multiple other spots that themselves contain other spots. In contrast, tags provide conceptual grouping of spots, allowing linkages between spots that are independent of their spatial position. The StraboSpot data system uses a graph database, rather than a relational database approach, to increase flexibility and to track geologically complex relationships. StraboSpot operates on two different platform types: (1) a fieldbased application that runs on iOS and Android mobile devices, which can function in either Internet-connected or disconnected environments; and (2) a web application that runs only in Internet-connected settings. We are presently engaged in incorporating microstructural data into StraboSpot, as well as expanding to include additional field-based (sedimentology, petrology) and lab-based (experimental rock deformation) data. The StraboSpot database will be linked to other existing and future databases in order to provide integration with other digital efforts in the geological sciences and allow researchers to do types of science that were not possible without easy access to digital data