Building Blocks
Prometheus-X building blocks make it easy to build Data spaces handling both personal and non-personal data. We are working on 20 building blocks which make it possible to set up a reliable data infrastructure.
4 categories
Prometheus-X provides 4 categories of building blocks
Connector
Catalog
Data Accessibility with the Prometheus-X Catalog Service: Since the first quarter of 2023, an innovative initiative is set to transform how organizations access and manage data across the expansive Prometheus-X network. Visions, a key member of Prometheus-X, has led the development of a pioneering catalog service, with the first version that has just launched.
Contract
The digital age has changed the way companies manage and share data. Streamlined processes and compliance are more important than ever. In this context, the core Building Block “Contract” service plays an essential role. This tool is part of a comprehensive suite designed to simplify and secure the complexities of data management and sharing, particularly within large data spaces. As organizations become increasingly reliant on big data, the need for efficient and secure data sharing agreements becomes more pressing.
Consent
The capacity to manage and share data responsibly is essential for preserving user trust and ensuring compliance with global data protection regulations. Core Building Block Consent serves as a fundamental component in this landscape, offering a robust framework for managing data permissions within the digital space. As part of a larger data exchange ecosystem, this building block is not just a tool, but a foundational element that empowers users and strengthens the integrity of data transactions.
Empowering Data Sovereignty with the Consent/Contracts Negotiating Agent
The Consent/Contracts Negotiating Agent represents a significant advancement in managing the complexity of data consent and contractual agreements within diverse dataspace ecosystems. This innovative technological framework is specifically designed to streamline the setting of consent preferences, automate responses to consent requests, and facilitate the management of contractual agreements between individuals and organizations. With features that are aligned with modern data standards and legal requirements, the tool not only simplifies the management of consent but also ensures personal data is utilized in a manner that respects user preferences and compliance mandates.
Identity
Coming soon
Billing and Monitoring
Coming soon
Decentralized AI Training: Entering a New Era with Prometheus X
In our digital age, data protection is not just a priority, it is a right. Prometheus X’s decentralized AI training approach redefines AI development by prioritizing confidentiality while democratizing access. This method not only ensures data privacy, but also paves the way for innovation in areas such as healthcare and education. By keeping data at the source, Prometheus X improves model accuracy and diversity, promoting a more equitable technology landscape. Join us as we explore this innovative initiative, where every step forward is a step towards a more inclusive and secure digital future.
Pioneering AI Processing via Edge Computing
Against a backdrop of increasing privacy concerns and the growing need for efficient data management, Prometheus-X is introducing AI processing through edge computing. This groundbreaking initiative places processing power right at the edge of the data, preserving privacy and improving operational efficiency within a distributed infrastructure. By placing processing functions close to the source — using Functions as a Service (FaaS) and Container as a Service (CaaS) — this approach minimizes data transfer, optimizes resource utilization and protects sensitive information. This strategy not only supports data integrity, but also contributes to the different requirements and promotes a scalable and sustainable approach to data processing. Dive into the intricacies of this transformative technology and discover its profound impact on areas such as education, where it enables secure, decentralized learning and the development of skills essential for today’s dynamic job market. Join us on the journey to a smarter and safer digital future.
Trustworthy AI Assessment: Ensuring Transparency and Trust
In the dynamic world of AI, LORIA and AffectLog’s Trustworthy AI Assessment initiative is central to fostering trust and transparency. This program integrates two sophisticated platforms — LORIA’s audit platform for data and algorithms and AffectLog’s risk assessment tools and services. Together, they provide a robust framework for the ethical evaluation and monitoring of AI algorithms.
These platforms improve the transparency, fairness, and safety of AI technologies, which are critical for stakeholders in the education, healthcare and technology sectors.
By providing detailed insights and safety assessments, they set new standards for AI trustworthiness and facilitate ethical AI use. Discover how these platforms and services can change the landscape of AI trustworthiness.
This approach is supplemented by an implementation of automated analysis of software models and AI trustworthiness indicators with respect to the aspects explainability, data security, privacy, and fairness developed by Fraunhofer ISST and University of Koblenz.
Learning Records Converter
Learning Records are available in many formats, either standardized (xAPI, SCORM, IMS Caliper, cmi5) or proprietary (Google Classroom, MS Teams, csv, etc). This wide vairety of format is a barrier to many use cases of learning records as this prevent the easy combination and sharing of learning records datasets from multiple sources or organizations.
The objective of this building block is to specify and develop APIs type “parser” to convert educational traces from one standard to another. Depending on the software and tools used in the field of education and training (LMS, LXP, ENT, etc.) several standards coexist in terms of data model of learning traces: SCORM, xAPI, cmi5, IMS Caliper, etc. This task will allow to combine learning traces data sets expressed in different standards.
Edge Translator: Bridging the Data Divide
Edge Translator revolutionizes the interoperability of data by seamlessly translating different ontologies into a unified format. This technology ensures the alignment of data formats and languages in real time, improving cross-platform data exchange. The flexibility and efficiency of the system, supported by the integration of external services, make it indispensable for ensuring a seamless flow of data. Whether it’s facilitating applications across language barriers or enabling consistent data interaction across different systems, Edge Translator is a dynamic solution to the challenges of global data communication. Discover the potential of Edge Translator in transforming digital interactions.
Revolutionizing Education: The Future of Distributed Learning Analytics Management
In this rapidly evolving educational landscape, the upcoming Distributed Learning Analytics Management Services offer an adaptive approach to lifelong learning. Set to launch on January 1, 2025, these services integrate the Personal Learning Record Store (PLRS) and Learning Object Metadata Crowd Tagging (LOMCT), crafting personalized and accessible learning experiences. But how can these components work together to benefit learners and teachers alike?
On the next page, you will find out more about the special features of these innovative services. You will learn how they collect, manage and enhance learning data to support the individual educational journey. The discussion also extends to their transformative potential to democratize education, ensuring that learning is not only tailored, but also continuously enriched through community collaboration. Join us as we explore how these services are redefining personalized education and making it a practical reality for all.
Refining Personalized Learning Through VR and Learning Analytics: A Vision for Democratized Education
Virtual Reality has a very interesting potential. This is even truer in the context of training, because it enables situations that are difficult to reproduce in the normal way. This enables the learner to work in a safe, low-cost environment. VR also enables the trainer to monitor the learner’s level. Sensors provide precise data that is difficult to measure in a real environment. This data can be fed into an artificial intelligence system, enabling individualized teaching. This makes it easier to make decisions and choose the best course of action for students. The creation of individualized learning paths, adapted to each student, is greatly facilitated by VR.
Data Alignment, Aggregation and Vectorisation (DAAV)
At a time when education and training are rapidly evolving to meet the individual needs of learners, two groundbreaking concepts are leading the way towards a more inclusive and efficient learning landscape: Data Alignment, Aggregation and Vectorization (DAAV) and Distributed Learning Analytics. These initiatives not only promise to transform the way learning data is managed and used, but also aim to democratize personalized learning across Europe.
The Data Value Chain Tracker: Illuminating Paths for Data Exchange
Prometheus-X’s introduction of the Data Value Chain Tracker represents a major leap in data sharing, strengthening connections between organizations and individuals while revaluing and accelerating the sharing process. At the heart of this innovation is a robust system that not only tracks data usage, but also rewards it, fostering a data-driven ecosystem of transparency and equity.
The following section shows how this tool goes beyond traditional data sharing mechanisms to include a strategic layer that aligns with Prometheus-X’s overall goals of improving EU competitiveness and strengthening educational infrastructures.
On the next page you will find a detailed account of the multiple benefits and profound impact of this ground-breaking tracker.
Elevating Data Integrity through Data Veracity Assurance
In the interconnected world of digital exchange, Data Veracity Assurance is a cornerstone of trust and accountability. This initiative is crucial for anyone dealing with the intricacies of data exchange and wanting to ensure the integrity and reliability of data between the various parties involved. In the following pages, we explore the mechanisms and benefits of this framework and highlight its central role in building a transparent data ecosystem.
By explaining the principle of veracity agreements and innovative verification models, we invite readers to explore how these strategies strengthen the authenticity of data. Discover how this new paradigm can transform your understanding and management of data quality.
Enhancing Insight with Distributed Data Visualization: A Tool for Educational and Professional Growth
Distributed data visualization is at the forefront, transforming how we interact with educational and professional development data. This sophisticated framework enables seamless management across multiple platforms and champions privacy and user control. It’s not just about displaying data, but revolutionizing its application by ensuring easy integration into different user interfaces.