Download JAR files tagged by databases with all dependencies

To run all integration tests, you need to set up all the databases: 1) Derby: $ export DERBY_HOME=/path/to/db-derby-10.14.2.0-bin $ cd $DERBY_HOME $ mkdir databases; cd databases $ java -jar $DERBY_HOME/lib/derbyrun.jar server start 2) MS SQL Server (for official and jtds drivers): $ podman run -itd --name pax.jdbc.sqlserver -e 'ACCEPT_EULA=Y' -e 'SA_PASSWORD=PaxJdbc!(*67' -e 'MSSQL_PID=Express' \ -p 1433:1433 -d mcr.microsoft.com/mssql/server:2022-latest 3) MariaDB: $ podman run --name pax.jdbc.mariadb -p 3306:3306 -e MYSQL_ROOT_PASSWORD=paxjdbc -d mariadb 4) MySQL: $ podman run --name pax.jdbc.mysql -p 3307:3306 -e MYSQL_ROOT_PASSWORD=paxjdbc -d mysql 5) PostgreSQL: $ podman run --name pax.jdbc.postgresql -e POSTGRES_USER=paxjdbc -e POSTGRES_PASSWORD=paxjdbc -p 5432:5432 -d postgres:latest 6) Oracle (a bit unofficial): $ podman run -itd --name pax.jdbc.oracle -p 1521:1521 --privileged=true oracleinanutshell/oracle-xe-11g

This project has a lot of business classes to work with genes and related named entities. Genes are part of a GeneDocument and may have gold IDs as well as mapped/predicted IDs. Another large part are species because most (all?) gene ID databases are species specific. So there are also classes or members to represent species mentions and the assignment of species IDs (taxonomy IDs) to genes. There is little to no business logic herein. This project is only useful as building block in other projects dealing with species assignment, gene ID mapping or similar efforts.

Protempa supports the construction of software systems for querying clinical databases, summarizing patient data, detecting clinically significant data patterns in groups of patients or individual patients, and extract, transform and load (ETL). Its special feature, temporal abstraction, supports queries and summarization of data in terms of temporal patterns. Temporal patterns enable robust querying and extraction of clinical history. These patterns include frequencies (at least two, three, etc. of some event or observation); sequences (chemotherapy followed by surgery within 180 days, a hospital encounter followed by another hospital encounter within 30 days); and overlaps (falling platelet counts in the setting of HELLP syndrome).

The biblio transformation engine is a java framework developed by the Hellenic National Documentation Centre (EKT, www.ekt.gr) and consists of programmatic APIs for filtering and modifying records that are retrieved from various types of data sources (eg. databases, files, legacy data sources) as well as for outputing them in appropriate standards formats (eg. database files, txt, xml, Excel). The framework includes independent abstract modules that are executed seperately, offering in many cases alternative choices to the user depending of the input data set, the transformation workflow that needs to be executed and the output format that needs to be generated.

Reco4j is an open source project aims at developing a recommendation framework based on graph data sources. We choose graph databases for several reasons. They are NoSQL databases, so "schemaless". This means that it is possible to extend the basic data structure with intermediate information, i.e. similarity value between item and so on. Moreover, since every information is expressed with properties, nodes and relations, the recommendation process can be customized to work on every graph. Reco4j can be used on every graph where "user" and "item" is represented by node and the preferences are modelled as relationship between them. Current implementation leverage on Neo4j as first graph database integrated in our framework.

The biblio transformation engine is a java framework developed by the Hellenic National Documentation Centre (EKT, www.ekt.gr) and consists of programmatic APIs for filtering and modifying records that are retrieved from various types of data sources (eg. databases, files, legacy data sources) as well as for outputing them in appropriate standards formats (eg. database files, txt, xml, Excel). The framework includes independent abstract modules that are executed seperately, offering in many cases alternative choices to the user depending of the input data set, the transformation workflow that needs to be executed and the output format that needs to be generated.