Search Results for "desktop-based mca projects"

MentDB is an open-source platform driving research into next-generation AI and universal data exchange. Our architecture is built around the revolutionary Mentalese Query Language (MQL). MentDB Weak (Generalized Interoperability): A unified data layer enabling seamless data exchange and application integration (SOA, ETL, Data Quality). We eliminate data silos through a single, generalized data language. MentDB Strong (Strong AI / AGI): The framework for exploring and building Machine...

...It also had Hadoop ( Big data ) support to move files to/from Hadoop Grid, Create, Load and Profile Hive Tables. This project is also known as "Aggregate Profiler" Resful API for this project is getting built as (Beta Version) https://sourceforge.net/projects/restful-api-for-osdq/ apache spark based data quality is getting built at https://sourceforge.net/projects/apache-spark-osdq/

This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to run Unzip the zip file Windows : java -cp ....

(Beta Version) This is sister project for https://sourceforge.net/projects/dataquality/ . It provides Restful APIs for features for data quality and data preparation features. This project will help projects which want embed data quality and data preparation features in their project or UI using restful calls. Data Cleansing APIs Dockerfile: # Pull base image FROM frnde/jetty-9.4.2-jre8-alpine-cet ADD osdq-v0.0.1.war /var/lib/jetty/webapps/osdq.war EXPOSE 8080 Docker...

Arthropod Easy Capture (AEC) is an arthropod specific, open-source solution for handling specimen level host interactions. Developed in conjunction with the Plant Bugs Planetary Biodiversity, Tri-Tropic Interactions TCN, and Bee Database projects, AEC is designed for rapid, and accurate data capture, utilizing controlled vocabularies to maintain data quality. The application is Web-based, allowing for collaboration from multiple partners to a centralized, easily maintainable, database. The AEC community, as part of the Advancing Digitization of Biodiversity Collections (ADBC) program, is already tasked to develop the appropriate Web service for sharing data with the iDigBio data portal. ...