News & Events

SEDIMARK does not focus on one particular domain but intends to design and prototype a secure decentralised and intelligent data and services marketplace that bridges remote data platforms and allows the efficient and privacy-preserving sharing of vast amounts of heterogeneous, high-quality, certified data and services supporting the common EU data spaces. Four use cases are […]

In the modern digital age, ensuring seamless data management, storage, and retrieval is of utmost importance. Enter Distributed Storage Solutions (DSS), the backbone for businesses aiming for consistent data access, elasticity, and robustness. At the core of leveraging the full prowess of DSS is an element often overlooked - the orchestrator pipeline. Let’s dive deeper […]

In this information age, data-driven business decision making has become a key factor for the success of organizations. If you are looking to access valuable information that allows you to make informed strategic decisions, Data Marketplaces are a powerful tool to consider. What is a Data Marketplace? Data Marketplaces are digital platforms designed to collect, manage […]

SEDIMARK recently participated in Data Week 2023 in Lulea, Sweden, which was organised by the Big Data Value Association (BDVA), a European initiative promoting data-driven digital transformation of society and the economy. Sedimark presented their work at a session organised by the Data Spaces Business Alliance (DSBA), an organisation promoting business transformation in the data […]

SEDIMARK partners: University of Surrey, INRIA and University College of Dublin published a new work at the 2022 8th #IEEE World Forum on IoT Conference in Yokohama, Japan, on a privacy-preserving ontology inspired by #GDPR requirements, for semantically interoperable #IoT data value chains. Check out the paper here. Abstract Testing and experimentation are crucial for promoting innovation and building […]

This document provides the initial detailed description of the project use cases (UCs) and the initial requirements. As far as it concerns the use cases, the goal is to define them with specific details about their implementation and how they will use the project tools, and especially aiming to combine data from different data sources […]

Automated Machine Learning (Auto-ML) is an emerging technology that automates the tasks involved in building, training, and deploying machine learning models [1]. With the increasing ubiquity of machine learning, there is an ever-growing demand for specialized data scientists and machine learning experts. However, not all organizations have the resources to hire these experts. Auto-ML software […]

In the digital age, streaming data - information that is generated and processed in real-time - is abundant. Applying Artificial Intelligence (AI) to mine this data holds immense value.  It enables real-time decision-making and provides immediate insights, which is particularly beneficial for industries like finance, healthcare, and transportation, where instant responses can make a significant […]

In today's world, Artificial Intelligence (AI) is widespread and used in many different areas, such as the tech industry, financial services, health care, retail and manufacturing to name just a few. The main drive behind the surge of AI applications is its ability to extract useful information from very large data. Despite the incredible positives […]