Validation of Experimental Data Origins: A Swarm of DAQ devices able to Deliver Unique Experimental Data using Blockchain‐like Fingerprint ID to a Data Repository

Miguel Tomás(1)*, Kiera Tabatha(2)

(1,2) Department of Computer Sciences, Blekinge Tekniska Högskola, 371 79 Karlskrona

Abstract

This paper discusses an innovative experimental setup and procedure for the automation and management of collected experimental data in real-time compatible with any open environment. It was conceptualized and prototyped a Swarm Learning (SL) architecture (hardware and software) as a fully decentralized algorithm principle to improve data trustworthiness. Conceptually, SL is a decentralized approach to validate and maintain a trustworthy database of experimental data in real-time, publicly accessible, through data redundancy, validation, and authentication of datasets across multiple smart data acquisition devices (SDAD) connected locally or remotely. Every participating site is a node in the Swarm network with the purpose of performing data validation and authentication tasks by sharing local hardware resources. Data trustworthiness and sovereignty are ensured with a real-time generation of a Unique Data Fingerprint Identification (UDFID) of a single experimental data record. New SDADs can enter a Swarm Network via a blockchain smart contract, regulating access and operational conditions in a fully autonomous way. New Swarm nodes agree to the collaboration terms, obtain the model, and perform local validation and authentication until all tasks are completed. This allows the acquisition of much larger experimental datasets, validated and authenticated publicly, while at the same time made available for analysis from sources outside the primary scientific research of a given specific site, and offers new opportunities to overcome the limitations of collaborative work in science, by enabling any research site to easily connect and join a swarm network increasing experimental data trustworthiness from unknown sources.

Keywords: Live Experimental testing; Open Environments; Data Authenticity; Data Repository

Suggested Citation Miguel T., Validation of Experimental Data Origins: A Swarm of DAQ devices able to Deliver Unique Experimental Data using Blockchain-like Fingerprint ID to a Data Repository (September 5, 2022). Available at http://dx.doi.org/10.2139/ssrn.4210504

Status: work in progress document revision: 05-08-2023 Original document: MS Word docX with embedded 360 videos
*Corresponding author: +32 471 632 520 (WhatsApp only)

Index

1. Introduction

2. Open Scientific Data

3. Experimental Data Repositories

4. Sharing, Notification, and Diffusion of Experimental Data

5. Experimental Data Redundancy

6. Experimental Data Authenticity and Trustworthiness

7. Smart DAQ Autonomous Cooperation

8. Swarm Intelligence

9. Proposed PCB electronics hardware for Live Data Acquisition

10. Time Dependency when Automating Data Collection

11. Experimental Setup Concept and Prototype

12. Conclusions

13. References and Symbols used

CRediT Author Statement
Miguel Tomás (https://orcid.org/0000-0002-5910-5179) Conceptualization, Methodology, Hardware, Software, Data curation, Visualization, Investigation. Validation, Writing, Funding, Kiera Tabatha (https://orcid.org/0000-0003-2656-4798) Writing, Reviewing and Editing

Data Availability
Data used to support the findings of this study are available for anyone to download and use on the following dataverse: https://dataverse.harvard.edu/dataverse/MiguelTomasMainDataverse. PCB electronics hardware design KiCad files are available on GitHub with a Creative Commons License: https://github.com/aeonSolutions/openScienceResearch-Smart-DAQ-Device-able-to-Upload-Live-Experimental-Sensor-Data-to-a-Data-Repo

Declaration of generative AI and AI-assisted technologies in the writing process
During the preparation of this work the author(s) used the [Grammarly Extension for MS Word](References and Symbols used) in order to Mitigate possible plagiarism on copy and editing from the internet. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

Declaration of Competing Interest
To this date, the author declares to have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

About the Author
Miguel Tomás has been researching and implementing technology solutions for start-up businesses and public institutions for the past 20 years. To learn more about the author, connect to his LinkedIn profile page using the following web address: https://www.linkedin.com/in/migueltomas/

A final statement about Mental Health in Science
It is found recurrently on the internet news and comments about another scientific researcher, in particular junior and medior researchers, going through some kind of mental health difficulties in particular those associated with sensory overload events. Promoted by abusive usage of wireless devices, assembled or modified to actuate at a distance and invisible, causing harm to a victim’s neurobiology. This is an old area of knowledge, that now needs to be openly discussed and commented, in a peaceful constructive way towards identification of solutions to all abusive usages of wireless frequency waves (radiation or vibration) in electronic devices. Open solutions are the correct path toward safety in usage of all things related to such technologies. Be knowledgeable to stay safe.