Today, we released a new version of our HighQSoft Query Language. This version provides the following features
Detailed release information can be found in our Confluence products space at https://highqsoft.atlassian.net/ which requires a log-in.
The GAIA-X 4 AI project started in June 2021 under the coordination of DLR and Conti Temic. Fourteen partners from industry and research are collaborating in the GAIA-X 4 AI project to build a data and services ecosystem for training and validating artificial intelligence (AI) applications based on Gaia-X. After about half of the project duration, the mid-term meeting on 01. and 02.03.2023 in Ingolstadt.
Half-time in the GAIA-X 4 AI project. On the first day of the event, the developments of the past 18 months will be looked at with anticipation. This includes the progress and results from the areas of services, infrastructure and the data space and thus the connection to Gaia-X, as well as the first demonstrations of use cases from the area of automotive production and automated and connected driving. On the first day of the event, in addition to representatives of the GAIA-X 4 AI consortium, invited guests from the BMWK, the project sponsor (TÜV Rheinland), the GAIA-X 4 Future Mobility project family led by DLR and the affiliated sister projects are expected. In addition to the pure demonstrations, the intensive exchange and networking within the project and the project family should not be neglected. Selected content and presentations from the first day of the event will be made available at a later date.
On 02/03/2023, the group of participants will be reduced to the GAIA-X 4 AI Consortium. Internal project topics and further project planning are then on the agenda.
The GAIA-X 4 AI project is part of the GAIA-X 4 AI Future Mobility Family and runs until May 31, 2024, has a budget of 18 million euros and is funded by the German Federal Ministry of Economics and Climate Protection (BMWK).
GAIA-X4AI Consortium: German Aerospace Center e. V., Altran Deutschland S.A.S. & Co. KG, Conti Temic microelectronic GmbH, Conweaver GmbH, Fraunhofer Gesellschaft e.V. HighQSoft GmbH, IAV GmbH Ingenieurgesellschaft Auto und Verkehr, Offenburg University of Applied Sciences - Institute for Machine Learning and Analytics, Intel Deutschland GmbH, Leibniz Universität Hannover, Reusch Rechtsanwaltsgesellschaft mbH, STTech GmbH, T-Systems International GmbH, Ingolstadt Technical University.
The GAIA-X 4 AI project is conducting research to build a data and services ecosystem for training and validating artificial intelligence (AI) applications. It focuses on two use cases from the automotive industry, aiming to advance automated and connected driving as well as innovative networked production processes. Data plays a central role here. The basis for this is the open IT infrastructure Gaia-X, which is currently being established throughout Europe. Their decentralized organization forms the basis for different providers to join forces and work together flexibly while maintaining data protection, transparency and compatibility.
Today, we released a new version of our HighQSoft Query Language. This version provides the following features
Detailed release information can be found in our Confluence products space at https://highqsoft.atlassian.net/ which requires a log-in.
Today, we released a new version of our HighQSoft Query Language.
This version fixes a problem that occurs with inconsistent unit tables. Units should be unique and assigned to a physical dimension. If this is not the case HQL could not resolve the mapping between unit and unit ID. But this is necessary, because the ASAM ODS server for attribute values and mass data always provides a unit ID, which then has to be mapped by HQL to the corresponding string presentation.
Also, HQL now contains an experimental Performance Analyzer that can be used to obtain information and statistical data about HQL commands and execution times
HQL is available as
HQL is a versatile and easy-to-learn query language to access measurement data in ASAM ODS solutions. The HQL library assists data analysts and engineers in their daily work to evaluate data and helps developers to integrate new tools and processes into the enterprise test data management solution.
Today, we released a new version of our HighQSoft Query Language.
This version fixes a problem that occurs with inconsistent unit tables. Units should be unique and assigned to a physical dimension. If this is not the case HQL could not resolve the mapping between unit and unit ID. But this is necessary, because the ASAM ODS server for attribute values and mass data always provides a unit ID, which then has to be mapped by HQL to the corresponding string presentation.
Also, HQL now contains an experimental Performance Analyzer that can be used to obtain information and statistical data about HQL commands and execution times
HQL is available as
HQL is a versatile and easy-to-learn query language to access measurement data in ASAM ODS solutions. The HQL library assists data analysts and engineers in their daily work to evaluate data and helps developers to integrate new tools and processes into the enterprise test data management solution.
Today, we released a new version of our HighQSoft Query Language.
This version fixes a problem that occurs with inconsistent unit tables. Units should be unique and assigned to a physical dimension. If this is not the case HQL could not resolve the mapping between unit and unit ID. But this is necessary, because the ASAM ODS server for attribute values and mass data always provides a unit ID, which then has to be mapped by HQL to the corresponding string presentation.
Also, HQL now contains an experimental Performance Analyzer that can be used to obtain information and statistical data about HQL commands and execution times
HQL is available as
HQL is a versatile and easy-to-learn query language to access measurement data in ASAM ODS solutions. The HQL library assists data analysts and engineers in their daily work to evaluate data and helps developers to integrate new tools and processes into the enterprise test data management solution.
Today, we released a new version of our HighQSoft Query Language.
This version fixes a problem that occurs with inconsistent unit tables. Units should be unique and assigned to a physical dimension. If this is not the case HQL could not resolve the mapping between unit and unit ID. But this is necessary, because the ASAM ODS server for attribute values and mass data always provides a unit ID, which then has to be mapped by HQL to the corresponding string presentation.
Also, HQL now contains an experimental Performance Analyzer that can be used to obtain information and statistical data about HQL commands and execution times
HQL is available as
HQL is a versatile and easy-to-learn query language to access measurement data in ASAM ODS solutions. The HQL library assists data analysts and engineers in their daily work to evaluate data and helps developers to integrate new tools and processes into the enterprise test data management solution.
Containers are a common way to bundle and run applications. In production environments, a key aspect is ensuring that there are no system downtimes. With growing systems and many applications not only that but also resource management becomes more difficult.
This is where Kubernetes helps out. Kubernetes provides a framework to run distributed systems resiliently. It is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. Thus, Kubernetes takes care of scaling and failover for system application, provides deployment patterns, and more:
At HighQSoft, we migrated the following products to Kubernetes:
As a next step, HQL and AReS Gateway will be enhanced with advanced Monitoring and Logging features.
Today, we released a new version of our HighQSoft Query Language.
This version fixes a problem that occurs with inconsistent unit tables. Units should be unique and assigned to a physical dimension. If this is not the case HQL could not resolve the mapping between unit and unit ID. But this is necessary, because the ASAM ODS server for attribute values and mass data always provides a unit ID, which then has to be mapped by HQL to the corresponding string presentation.
Also, HQL now contains an experimental Performance Analyzer that can be used to obtain information and statistical data about HQL commands and execution times
HQL is available as
HQL is a versatile and easy-to-learn query language to access measurement data in ASAM ODS solutions. The HQL library assists data analysts and engineers in their daily work to evaluate data and helps developers to integrate new tools and processes into the enterprise test data management solution.
HighQSoft GmbH is part of the federal project Gaia-X:4 AI and taking responsibility for data room design, data services, standardization, and integration of AI algorithms in the use-case "Autonomous driving". The project will run for 3 years. HighQSoft targets to provide its products and services as part of the Gaia-X ecosystem.
Gaia-X represents the next generation of data infrastructure: an open, transparent and secure digital ecosystem, where data and services can be made available, collated, and shared in an environment of trust.
The architecture of Gaia-X is based on the principle of decentralization. Gaia-X is the result of a multitude of individual platforms that all follow a common standard – the Gaia-X standard. Together, we are developing a data infrastructure based on the values of openness, transparency, and trust. So, what emerges is not a cloud, but a networked system that links many cloud service providers together.
Innovation through digital sovereignty – that’s the goal of Gaia-X. We achieve this by establishing an ecosystem in which data is made available, collated, and shared in a trustworthy environment. The users always retain sovereignty over their data. So, what emerges is not a cloud, but a federated system that links many cloud services providers and users together.
Representatives from business, politics, and science from Europe and around the globe are working together, hand in hand, to create a federated and secure data infrastructure. Companies and citizens will collate and share data – in such a way that they keep control over them. They should decide what happens to their data, where it is stored, and always retain data sovereignty.
Source: gaia-x.eu
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