4 datasets found
  1. A Versatile and Secure Data Management System API facilitating the...

    • zenodo.org
    • data.niaid.nih.gov
    pdf
    Updated Jul 15, 2024
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    Angelos Amditis; Angelos Amditis; George Tsimiklis; George Tsimiklis; Aikaterini Karagiannopoulou; Aikaterini Karagiannopoulou; Konstantinos Routsis; Konstantinos Routsis (2024). A Versatile and Secure Data Management System API facilitating the Interconnection of any software component and Easy Data Access. [Dataset]. http://doi.org/10.5281/zenodo.7351723
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jul 15, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Angelos Amditis; Angelos Amditis; George Tsimiklis; George Tsimiklis; Aikaterini Karagiannopoulou; Aikaterini Karagiannopoulou; Konstantinos Routsis; Konstantinos Routsis
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In the context of the EU-funded project PILOTING (No. 871542), a versatile Data Management System (DMS) was deployed and facilitated the easy integration of nine different robotic systems and various payloads and the storing of all the data observations produced during the inspections. The DMS is designed under the DMS-Data Model (DMS-DM) and operates on top of a representational state transfer (REST) application programming interface (API) that provides a simplified way to exchange data through HTTP(S) requests from a client to the server. One of its key advantages is that it provides a great deal of flexibility so the model could accommodate extensions if needed. Data is not tied to resources or methods, so REST can handle multiple types of calls, return different data formats and even change structurally with the correct implementation of hypermedia.
    It supports CRUD operations via GET, POST, PUT, PATCH, and DELETE HTTP methods and stores the data on a PostgreSQL object-relational database system. The REST API has been created with Python's Django (web framework) and Django REST Framework, a powerful and flexible toolkit for building Web APIs.
    The constructed document presents the communication endpoints (DMS API’s Uniform Resource Identifiers (URIs)) under which an authorized user can have access to the DMS API and subsequently to the collected data.

  2. AuroraFlow Evaluation Data

    • zenodo.org
    xz
    Updated Mar 17, 2025
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    Gerrit Pape; Gerrit Pape; Bjarne Wintermann; Bjarne Wintermann (2025). AuroraFlow Evaluation Data [Dataset]. http://doi.org/10.5281/zenodo.15040440
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    xzAvailable download formats
    Dataset updated
    Mar 17, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Gerrit Pape; Gerrit Pape; Bjarne Wintermann; Bjarne Wintermann
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Evaluation data and artefacts for the publication "AuroraFlow, an Easy-to-Use, Low-Latency FPGA Communication Solution Demonstrated on Multi-FPGA Neural Network Inference" by Gerrit Pape, Bjarne Wintermann, Linus Jungemann, Michael Laß, Marius Meyer, Heinrich Riebler and Christian Plessl.

  3. I

    Global USB Temperature Data Logger Market Global Trade Dynamics 2025-2032

    • statsndata.org
    excel, pdf
    Updated May 2025
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    Stats N Data (2025). Global USB Temperature Data Logger Market Global Trade Dynamics 2025-2032 [Dataset]. https://www.statsndata.org/report/usb-temperature-data-logger-market-89640
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    excel, pdfAvailable download formats
    Dataset updated
    May 2025
    Dataset authored and provided by
    Stats N Data
    License

    https://www.statsndata.org/how-to-orderhttps://www.statsndata.org/how-to-order

    Area covered
    Global
    Description

    The USB Temperature Data Logger market has emerged as a critical component for industries that prioritize precise temperature monitoring and data integrity. These devices, designed for easy data transfer via USB, are widely utilized in sectors such as pharmaceuticals, food and beverage, healthcare, and logistics, wh

  4. Data from: Easy One-Pot Synthesis of Energy Transfer Cassettes

    • acs.figshare.com
    txt
    Updated May 30, 2023
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    W. G. Skene; Stéphane Dufresne (2023). Easy One-Pot Synthesis of Energy Transfer Cassettes [Dataset]. http://doi.org/10.1021/ol048977m.s001
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    txtAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    ACS Publications
    Authors
    W. G. Skene; Stéphane Dufresne
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    Novel cassettes suitable for energy transfer are presented involving simple and efficient condensation methods. The new rigid cassettes obtained by Schiff base formation are capable of undergoing energy transfer from a donor to an acceptor core both through space and through bonds.

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Angelos Amditis; Angelos Amditis; George Tsimiklis; George Tsimiklis; Aikaterini Karagiannopoulou; Aikaterini Karagiannopoulou; Konstantinos Routsis; Konstantinos Routsis (2024). A Versatile and Secure Data Management System API facilitating the Interconnection of any software component and Easy Data Access. [Dataset]. http://doi.org/10.5281/zenodo.7351723
Organization logo

A Versatile and Secure Data Management System API facilitating the Interconnection of any software component and Easy Data Access.

Explore at:
pdfAvailable download formats
Dataset updated
Jul 15, 2024
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Angelos Amditis; Angelos Amditis; George Tsimiklis; George Tsimiklis; Aikaterini Karagiannopoulou; Aikaterini Karagiannopoulou; Konstantinos Routsis; Konstantinos Routsis
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

In the context of the EU-funded project PILOTING (No. 871542), a versatile Data Management System (DMS) was deployed and facilitated the easy integration of nine different robotic systems and various payloads and the storing of all the data observations produced during the inspections. The DMS is designed under the DMS-Data Model (DMS-DM) and operates on top of a representational state transfer (REST) application programming interface (API) that provides a simplified way to exchange data through HTTP(S) requests from a client to the server. One of its key advantages is that it provides a great deal of flexibility so the model could accommodate extensions if needed. Data is not tied to resources or methods, so REST can handle multiple types of calls, return different data formats and even change structurally with the correct implementation of hypermedia.
It supports CRUD operations via GET, POST, PUT, PATCH, and DELETE HTTP methods and stores the data on a PostgreSQL object-relational database system. The REST API has been created with Python's Django (web framework) and Django REST Framework, a powerful and flexible toolkit for building Web APIs.
The constructed document presents the communication endpoints (DMS API’s Uniform Resource Identifiers (URIs)) under which an authorized user can have access to the DMS API and subsequently to the collected data.

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