Data Summary. The main categories of data foreseen to be collected or generated by MULTI-STR3AM are: • Underlying research data: This category encompasses the data, including associated metadata, forming the basis of results and conclusions presented in scientific articles and in any potential patents arising from the project. To remove any limitations to review and validation of results by the scientific community, green open access (self-archiving) will be the preferred model of publication for scientific articles. Additionally, the underlying data will be deposited in an open repository (independent of the project), which will be linked to in the resulting article. • Operational data: This includes raw or curated data arising from the operation of equipment, for example associated with biomass cultivation, fractionation and purification of microalgae components, and routine analyses of the resultant products (e.g., compositional analyses). Data related to the production process will be used to produce guidelines for optimal performances, quality checks and confirmation checks, which will be of use in the project and in future planned production of algae. This category of data is likely to contain commercially sensitive data; careful consideration will be given to which information can be published openly (e.g., for dissemination purposes) and which should be consideration non-open. Some of this data is also of value for scientific or other publications and presentations and will be treated accordingly. • Impact monitoring data: Primarily in WP5, data will be gathered to assess the social, environmental and economic impact of MULTI-STR3AM and to track the performance of the project against the KPIs set out in the proposal. These data include biorefinery process modelling and data gathered on e.g., feedstock, raw materials, energy, waste and emissions to complete life cycle and social life cycle assessments. Such assessments will be performed according to methodology as defined by ISO 14040/44 and the project impacts measured with the help of computer-based tools such as SimaPro v9 (with Ecoinvent v3.5 database, and others). • Documentation relating to instruments and methods: This category covers documentation needed to implement the project and reproduce its results, including SOPs from each partner for their respective processes and details of tools, methods, instruments and software. This section will describe the kinds of data that each work package will be handli...
Data Summary. The main purpose of the Data Management Plan (DMP) is to describe the data management life cycle for the data to be collected, processed and/or generated by the ORP project. It also aims to provide a framework to support the European Commission’s goals for Open Access regarding publications, scientific and technical results and raw data resulting from activity supported by the XX Xxxxx Agreement. It is a requirement of Horizon 2020 grants that publications resulting from the grant should be made in an Open Access journal unless there are compelling reasons why this should not be done. Outputs from the ORP activities may be grouped into a number of different types: 1/ Scientific data resulting from the Transnational Access programme 2/ Scientific publications resulting from the Transnational Access programme 3/ Technological or software research and development. 4/ Technical data and publications resulting from Management and JA 1-2-3-4 5/ Technical and personal data resulting from the CTAC As part of making research data findable, accessible, interoperable and re-usable (FAIR), the DMP will identify for each category: ● Data set reference and name: identification of what data will be collected, processed and/or generated ● Data set description: description of the data set ● Standards and metadata: explanation of the methodology and standards that will be applied ● Data sharing: specify whether data will be shared/made open access or not. How will data be exploited and/or shared/made accessible for verification and re-use? If data cannot be made available, explain why. ● Archiving and preservation (including storage and backup): explanation of how data will be curated and preserved (including after the end of the project) The data collected and generated by the ORP project will be useful for astronomers, universities, science students, etc. By sharing the data, the project will contribute to additional scientific discoveries by re-use of data taken for other purposes.
Data Summary. The following references furnish data to be incorporated in the specified Sections of this Lease and shall be construed to incorporate the entire Section:
Data Summary. In summary, we see that the existence of patterns in which a single conjunct controls (some) agree- ment processes considerably complicates the array of possible strategies for syntactic agreement with (nominal) coordinate structures. In addition to (18-1) and (18-2) we must accommodate a number of further patterns.
Data Summary. The main format of the data deposits generated in the INTUITIVE project will be in form of text- based spreadsheet data files and an associated header document file. The text-based spreadsheet format makes the data more widely importable to a large range of software and the origin of the data is hence made transparent to the user. In order to further facilitate the access, in addition to the spreadsheet data a descriptive text will be created for each set of spreadsheets datafiles, which describes the structure of the data. This descriptive text will also state under which recording conditions/settings the data was obtained, pointers to the datafiles and the purpose of the data as well as its relationship to the objectives of the INTUITIVE project. In cases where binary spreadsheet data format is instead used, the program used to create the data must be specified in order to increase reusability. The descriptive text will also include links to the published paper, to which the reader will be referred for a more detailed account of how the data was generated. The data can be expected to be useful for neuroscientists, roboticists, psychophysicists and electronic engineers that want to test the validity of alternative hypotheses explaining the data.
Data Summary. Purpose of the data collection/generation and its relation to the objectives of the project Data collection will be generated in the frame of the research cruises funded through the ARICE project on board the six ARICE Research Icebreakers: Types and formats of data the project will generate/collect In this frame, the cruises funded through ARICE will generate a variety of data which could include:
Data Summary. 2.1. State the purpose of the data collection/generation The data being used in the RESOLVD project will be oriented to improve knowledge on how power flow behaves in the low voltage in presence of distributed renewable generation and high variability on demand. The general purpose of the project RESOLVD is to act (schedule and control) on the low voltage grid in order to increase efficiency. With this aim, data will serve in the following purposes:
Data Summary. The main purpose for the data collection/generation of the CarE-Service project is for the description of new circular economy business models in innovative hybrid and electric mobility through advanced reuse and remanufacturing technologies and services. The CarE-Service project will produce several datasets during the lifetime of the project. All the data which will be collected will be relevant to the purposes of the projects, such as the establishment of circular economy business models, the development of the Smart Mobile Modules, the creation of customer-driven products and the development and validation of technical solutions for reused, remanufactured and recycled components and the evaluation of these business models through demonstration and life cycle assessment (LCA). All the collected or generated data will be analyzed and evaluated from a range of methodological perspectives for project development and engineering and scientific purposes. A range of data will be created during the project. These will be available in a variety of easily accessible formats, including Documents (Word) (DOCX), Spreadsheets (Excel) (XLSX, CSV), Presentation files (Power Point) (PPT), PostScript (PDF, XPS), images, audio and video files (JPEG, PNG, GIF, TIFF, WAV, MPEG, AIFF, OGG, AVI, MP4), Technical CAD drawings (DWG), Origin (OPJ), compressed formats (TAR.GZ, MTZ), Program database (PDB, DBS, MDF, NDF), etc. (see Table 5-1). As no comparable data are available for secondary analysis at the moment, it is planned to make our dataset publicly available in a research data repository. Apart from the research team, the dataset will be useful for other research groups working on eco-innovative circular economy business models on large scale demonstration projects. The following table contains all the datasets that will be generated during the project. The expected size of the datasets produced will be between 5MB and 1GB. For every dataset which will be generated for a task, the leading partner of the task will be the Master of Data. The Master of Data will be responsible for the collection of the data from the other partners, the file and sharing actions among the consortium, the creation of the linked metadata files and also the activities for the publish of the data, e.g. on Zenodo platform. Table 5-1: Potential Datasets Potential datasets – Description Format Dissemi- nation level Master of Data WP1 - Requirements for new business models, services, demonstrators an...
Data Summary. The overall objective of CIRCuIT is to demonstrate innovative solutions for closing the loop of urban materials and resource flows in the built environment sector. The aim is that these solutions will support a transformation of cities into centres of circular innovation, and support and increase the regenerative capacity of each city. In CIRCuIT the work packages generate data for different purposes: • Map flows of building materials in the four cities using mass-scanning approaches and blockchain technology, alongside existing building datasets to support digital pre- demolition audits and matching of supply and demand, and to overcome the barriers of data interoperability and availability (WP3). • Implement a cross-European and interdisciplinary Circularity Hub, as a data platform and one-stop-shop for evaluating progress of circular economy and regenerative capacity in urban and peri-urban areas of cities, including a range of indicators for monitoring this within the built environment (WP8). • The data from demonstrations generated in WP4-6 will be utilised in WP7 to analyse existing European, national and local regulations and procedures, to identify the room for manoeuvre that the four cities have for including requirements on the reuse and recycling of building products and materials, adaptive reuse and refurbishment, and design for disassembly in urban planning (spatial, municipal and local) and building permits. • Results are disseminated via WP9. Figure 1: Collection and use of data between WPs
Data Summary. The PULSE-COM project will produce data in a wide range of R&I activities that are summarized in Table 1. The DMP being a dynamic document, this list may be modified (addition or removal of datasets) depending on the project’s developments. All partners were asked to complete the DMP and provide datasets. Some however had no inputs at this point and will update the DMP at its next review (1st Periodic Report-Month 12), if relevant. Once generated or collected, the data will be stored in several formats: documents, images, data, etc.
