Search Results for "open personal data"
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Showing 7 open source projects for "open personal data"
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Grafana
Leading open-source visualization and observability platform
Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. -
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rSIGNAL - ruby Simple Inter-Interface Generic Aggregation Layer. It allows external data sources to be aggregated, store the aggregated data and print the aggregated data out in a transformed format to a file (or integrated HTTP server) on demand.
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RubyMoss is a Web - Based Framework written with Ruby on Rails, intended to support all analysis and data processing for Mossbauer Spectroscopy. Written under BSD License.
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OpenBRR2 project focuses on the re-write of the original "OpenBRR - Data" (http://sourceforge.net/projects/openbrr) project. The aim is to develop a hosted data aggregation application for all F/LOSS projects.
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Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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Data mines the voting record and other actions of Members of the NZ Parliament. Extracts information from the parliament website and stores it in a database. Provides tools to analyse the information, producing statistics and tables about the MPs/parties
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FRIDA (flexible rapid interactive data analysis) is a generic program for manipulating, fitting, and plotting x,z,y data. It is primarily aimed at spectral analysis, especially in neutron scattering. Note: project has moved away from sf.net.
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CompLearn is a general-purpose compression-based machine learning system that uses data compression to learn or data mine patterns in arbitrary data.
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