EU Project
Graph-Massivizer
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PRESS RELEASE
Graph-Massivizer promotes climate-neutral and sustainable economic sectors boosted by graph data processing.
EU Project
Graph Massivizer
About the Project
Graph-Massivizer
Graph-Massivizer researches and develops a high-performance, scalable, and sustainable platform for information processing and reasoning based on the massive graph representation of extreme data. It delivers a toolkit of five open-source software tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as massive graphs. The tools focus on holistic usability (from extreme data ingestion and massive graph creation), automated intelligence (through analytics and reasoning), performance modelling, and environmental sustainability tradeoffs, supported by credible data-driven evidence across the computing continuum.
Consortium
Graph-Massivizer gathers a consortium of twelve partners from eight countries, covering four academic universities, two applied research centres, one HPC centre, two SMEs and two large enterprises. It leverages the world-leading roles of European researchers in graph processing and serverless computing and uses leadership-class European infrastructure in the computing continuum.
Graph-Massivizer Software Tools
The project delivers the Graph-Massivizer toolkit of five open-source software (OSS) tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as MG.
The tools focus on holistic
1. Usability
2. Automated intelligence
3. Performance modelling
4. Environmental sustainability tradeoffs supported by credible data-driven evidence
5. Across HPC systems and computing continuum
Graph-Massivizer Software Tools
The project delivers the Graph-Massivizer toolkit of five open-source software (OSS) tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as MG.
The tools focus on holistic
1. Usability
2. Automated intelligence
3. Performance modelling
4. Environmental sustainability tradeoffs supported by credible data-driven evidence
5. Across HPC systems and computing continuum
Use Cases
News
Blog
Synthetic Data Powered Investment and Trading
Author: Laurentiu Vasiliu Peracton Ltd. In the ever-evolving world of finance, Synthetic Data Driven Investment and Trading is emerging as hybrid approach, where financial algorithms are not only powered by traditional financial data (historic and live), but also by...
Trading in the Matrix
Author: Laurentiu Vasiliu Peracton Ltd. Imagine a scenario where extreme quantities of synthetic data are continuously generated and used to train multiple generations of AI enhanced financial algorithms. In this scenario, financial algorithms train on making...
Building massive knowledge graphs using automated ETL pipelines
In this blog post, written by our colleagues Wolfgang Schell and Pauline Lencio at metaphacts , the Graph-Massivizer team explains how to build a massive knowledge graph from existing information or external sources in a repeatable and scalable manner. The post...
From Big Data to Green Data: Reducing the Environmental Impact of Data Science with Graph Massivizer
Data analysis and data processing are technologies that are increasingly prevalent in everyday life, with applications in research, industry, commerce, and public administration. However, they also have a significant environmental impact, both direct and indirect, due...
The importance of the semantic knowledge graph
This article is the first in a series of two where we discuss our perspective on what is considered a semantic knowledge graph, why it’s important, and share how they can drive your enterprise goals forward.
Unleashing the Power of Graph-Massivizer: Transforming Data Analysis
The Webinar, held on November 29th 2023 is now on line on the Graph-Massivizer YouTube Channel. Have a look at the full recording to know more about the potential of the Graph-Massivizer project to boost the impact of extreme and sustainable graph processing for...
Unveiling The Future: How Event Registry Utilizes Graph-Massivizer to Fuel UN Sustainable Development Goals
EVENTREGISTRY Unveiling The Future: How Event Registry Utilizes Graph-Massivizer to Fuel UN Sustainable Development Goals The Pioneering Spirit of Graph-Massivizer Project In a world drowning in data, the need for advanced processing capabilities has never been more...
Why Current Financial Historic Data is Neither Enough nor Truly Useful for Testing Financial Trading and Investment Models in the AI Era (part 2)
Why Current Financial Historic Data is Neither Enough nor Truly Useful for Testing Financial Trading and Investment Models in the AI Era (part 2)The preceding blog (part 1) highlighted the challenges posed by historical data, encompassing limitations related to data...
