Periodic Reporting for period 2 - RAISE (Research Analysis Identifier SystEm)
Berichtszeitraum: 2023-10-01 bis 2024-09-30
RAISE's mission is to establish the infrastructure for a decentralized crowdsourced data processing system, transitioning from open data to open-access data for processing. The key innovation lies in RAISE's capability to dispatch algorithms to datasets, as opposed to transferring the entire dataset to the algorithm. For the research community, the true value of open data lies not just in accessibility but in streamlined processing to enhance efficiency and productivity. RAISE is dedicated to fostering a transparent approach to sharing and processing data, empowering researchers to publish work with evidence-based authentication of data analysis while ensuring accreditation.
Adhering to the FAIR Guiding Principles (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship, RAISE fundamentally shifts the traditional approach. Rather than downloading large datasets to a computer housing the processing algorithm, RAISE takes a novel approach by bringing the processing algorithm (small in size) to the dataset (large in size). To bolster dataset repository processing capacities, RAISE adopts the crowdsourcing concept, allowing researchers to seamlessly integrate computers into existing workflows to serve both datasets and processing needs.
RAISE is poised to deliver several impactful outcomes, including:
1. Establishing a reliable crowdsourced network of RAI Certified nodes offering data storage and processing resources.
2. Introducing the RAI Cloud platform to manage data sharing, processing, and discovery.
3. Introducing the Research Analysis Identifier (RAI), a unique identifier for any result, accompanied by dataset information and processing scripts, all without revealing source code or raw data.
4. Providing services for dataset plagiarism identification and proof-of-origin, maximizing trust in the RAISE system.
5. Developing the RAI Synthetic Data Generator to further enhance the system's capabilities.
Adhering to the FAIR Guiding Principles (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship, RAISE fundamentally shifts the traditional approach. Rather than downloading large datasets to a computer housing the processing algorithm, RAISE takes a novel approach by bringing the processing algorithm (small in size) to the dataset (large in size). To bolster dataset repository processing capacities, RAISE adopts the crowdsourcing concept, allowing researchers to seamlessly integrate computers into existing workflows to serve both datasets and processing needs.
RAISE is poised to deliver several impactful outcomes, including:
1. Establishing a reliable crowdsourced network of RAI Certified nodes offering data storage and processing resources.
2. Introducing the RAI Cloud platform to manage data sharing, processing, and discovery.
3. Introducing the Research Analysis Identifier (RAI), a unique identifier for any result, accompanied by dataset information and processing scripts, all without revealing source code or raw data.
4. Providing services for dataset plagiarism identification and proof-of-origin, maximizing trust in the RAISE system.
5. Developing the RAI Synthetic Data Generator to further enhance the system's capabilities.
Based on the project’s objectives, the consortium has made significant progress towards delivering scientific impact where its key accomplishments are listed below:
1.The agile iterative methodology was refined, incorporating the technical advancements of the RAISE System, alongside feedback from the community and input from newly established dedicated UX testing groups.
2. A robust development and release environment was created to rigorously test new technical functionalities prior to public deployment.
3. The evaluation methodology for RAISE was enhanced through the introduction of three core assessments to measure its impact on academic research.4.
4. The RAI ID PID underwent a significant revision based on feedback from FAIRIMPACT’s “Creating EOSC Compliant PID Policies”, leading to the development of distinct PID formats for RAISE objects, including datasets, scripts, and experiments.
5. The technical team integrated RAISE with the OAI-PMH service to streamline metadata harvesting and interoperability.
6. The RAISE Certified Node architecture, a crowdsourced system of distributed Nodes, was developed, with AUTH, VICOM, and UOWM successfully establishing their own Nodes.
7. The RAISE Blockchain Server Architecture was upgraded to enhance efficiency and security.
8. The first release of RAISE has been deployed, offering core functionalities such as user registration, dataset and script uploads, dataset access management, experiment creation, script security analysis, and dataset usage analytics.
9. Communication and outreach efforts continued to raise awareness about the RAISE platform and its potential benefits within the EOSC community and beyond.
1.The agile iterative methodology was refined, incorporating the technical advancements of the RAISE System, alongside feedback from the community and input from newly established dedicated UX testing groups.
2. A robust development and release environment was created to rigorously test new technical functionalities prior to public deployment.
3. The evaluation methodology for RAISE was enhanced through the introduction of three core assessments to measure its impact on academic research.4.
4. The RAI ID PID underwent a significant revision based on feedback from FAIRIMPACT’s “Creating EOSC Compliant PID Policies”, leading to the development of distinct PID formats for RAISE objects, including datasets, scripts, and experiments.
5. The technical team integrated RAISE with the OAI-PMH service to streamline metadata harvesting and interoperability.
6. The RAISE Certified Node architecture, a crowdsourced system of distributed Nodes, was developed, with AUTH, VICOM, and UOWM successfully establishing their own Nodes.
7. The RAISE Blockchain Server Architecture was upgraded to enhance efficiency and security.
8. The first release of RAISE has been deployed, offering core functionalities such as user registration, dataset and script uploads, dataset access management, experiment creation, script security analysis, and dataset usage analytics.
9. Communication and outreach efforts continued to raise awareness about the RAISE platform and its potential benefits within the EOSC community and beyond.
RAISE aims for cutting-edge advancements beyond the current state of the art, focusing on two key areas: technical innovations supporting open data processing and understanding the existing regulatory frameworks for FAIR data access. Recent technical progress includes:
1. Developing the RAISE blockchain server, integrating immutable identifiers for research components, and ongoing refinement of the RAI PID solution.
2. Advancing Metadata Standardization and Interoperability to capture project-specific data effectively.
3. Achieving strides in Synthetic Data Generation for enhanced privacy and machine learning performance.
4. Beginning development of a state-of-the-art Plagiarism Checker to safeguard researchers' work.
Additionally, RAISE has made headway in comprehending open science conditions:
1. Implementing Agile Methodology via the RAISE community for active researcher involvement.
2. Gaining insights into Researcher Needs for Open Science through interviews and pilots.
3. Initiating a Common Requirements Space, collaborating with EOSC projects and ensuring user-aligned solutions.
1. Developing the RAISE blockchain server, integrating immutable identifiers for research components, and ongoing refinement of the RAI PID solution.
2. Advancing Metadata Standardization and Interoperability to capture project-specific data effectively.
3. Achieving strides in Synthetic Data Generation for enhanced privacy and machine learning performance.
4. Beginning development of a state-of-the-art Plagiarism Checker to safeguard researchers' work.
Additionally, RAISE has made headway in comprehending open science conditions:
1. Implementing Agile Methodology via the RAISE community for active researcher involvement.
2. Gaining insights into Researcher Needs for Open Science through interviews and pilots.
3. Initiating a Common Requirements Space, collaborating with EOSC projects and ensuring user-aligned solutions.