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Stepping is a framework designed to ease the implementation of data processing solutions. In use cases where we need to implement data or data-streaming algorithms or any other processing on data, we need to first handle many different infrastructure issues. For example, we need to decide how to split the data processing logic into different steps, think about our threading policy, how to handle communication between the different steps, error handling etc. One of the most important subjects is the Threading Policy of our solution. For example, we need to think how many threads to open, have the option to distribute the processing of data to multiple 'executors' in parallel, have a thread-safe communication layer between the threads etc. On top of that we also care a lot about the performance of our solution, we want to make sure that the latency added by these infrastructures is minimal as possible. Stepping aims to handle many of these aspects so developers can spend their time on the business logic instead of solving these infrastructure and data flow issues issues over and over again.

HermiT is reasoner for ontologies written using the Web Ontology Language (OWL). Given an OWL file, HermiT can determine whether or not the ontology is consistent, identify subsumption relationships between classes, and much more. This is the maven build of HermiT and is designed for people who wish to use HermiT from within the OWL API. It is now versioned in the main HermiT version repository, although not officially supported by the HermiT developers. The version number of this package is a composite of the HermiT version and a value representing the OWLAPI release it is compatible with. Note that the group id for the upstream HermiT is com.hermit-reasoner, while this fork is released under net.sourceforge.owlapi. This fork exists to allow HermiT users to use newer OWLAPI versions than the ones supported by the original HermiT codebase. This package includes the Jautomata library (http://jautomata.sourceforge.net/), and builds with it directly. This library appears to be no longer under active development, and so a "fork" seems appropriate. No development is intended or anticipated on this code base.

relay-jdbc allows a JDBC connection to be relayed through an intermediate relay server: it is both a JDBC driver (client) and a JDBC relay server. It is a fork of https://github.com/AugeoSoftware/VJDBC project, where Aleksei Yu. Semenov has implemented a number of brilliant improvements of the orignal VJDBC project hosted on http://vjdbc.sourceforge.net Original Developers were: Hunter Payne ([email protected]) and Michael Link ([email protected]). For all pre-existing code, credits go to the original respective author. This product brings the original VJDBC concept further and (apart from code quality improvements and bug fixes) implements complete separation of the underlying transport mechanism, introducing support for connecting directly through a SSH pipe, where the relay server interacts with the client through standard I/O pipes. The re-designed transport architecture supports easy development of new transport implementations, allowing this JDBC relay to be quickly adapted to a variety of exotic environments.

RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy. If you wish to cite RuSH in a publication, please use: Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587. The full text can be found at: https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616 This version allows defining section scopes for sentence segmentation.

RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy. If you wish to cite RuSH in a publication, please use: Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587. The full text can be found at: https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616

HermiT is reasoner for ontologies written using the Web Ontology Language (OWL). Given an OWL file, HermiT can determine whether or not the ontology is consistent, identify subsumption relationships between classes, and much more. This is the maven build of HermiT and is designed for people who wish to use HermiT from within the OWL API. It is not officially supported by the HermiT development team, but was built initially for use with the Clojure-OWL library. It is built using the HermiT source tree without modification. There have been some additions to the test source tree to account for differences between the maven and ant environment; these are small and (hopefully) maintainable. The version number of this package is a composite of the HermiT version and an value representing releases of this packaged version. So, 1.3.7.1 is the first release of the mavenized version of HermiT based on the 1.3.7 release of HermiT. This package includes the Jautomata library (http://jautomata.sourceforge.net/), and builds with it directly. This library appears to be no longer under active development, and so a "fork" seems appropriate. No development is intended or anticipated on this code base.

ASV Toolbox is a modular collection of tools for the exploration of written language data. They work either on word lists or text and solve several linguistic classification and clustering tasks. The topics covered contain language detection, POS-tagging, base form reduction, named entity recognition, and terminology extraction. On a more abstract level, the algorithms deal with various kinds of word similarity, using pattern based and statistical approaches. The collection can be used to work on large real world data sets as well as for studying the underlying algorithms. The ASV Toolbox can work on plain text files and connect to a MySQL database. While it is especially designed to work with corpora of the Leipzig Corpora Collection, it can easily be adapted to other sources.

JSONXML project is library used to parse/format tree-like object structures in most popular text formats: XML and JSON. For parsing it accepts "java.io.Reader" and return java object. For formatting it accepts java object and "java.io.Writer". Object is generally structure that contains Map and/or List elements. Map is ordered set of named items. List is set of unnamed items. Reflection may be used to convert objects into set of maps/lists and vice versa. JSON parser is implemented explicitly. XML parser is based on SAX parser and applies only certain rules for result. Library is designed to allow various entry points for variable decisions depending on end use needs. 1. Formats - formats are used to enable locale-specific parsing/formatting of numbers and dates. 2. ReflectiveBuilder - enables reflection. Default implementation uses getters/setters only. 3. ObjectsRegistry - used to keep track of parsed or formatted objects and allow resolvable references in formatted (text) form.

[](https://drone.io/bitbucket.org/tidalwave/tidalwave-superpom-src/latest) The super POM for all Tidalwave projects. It is not designed for being used by others, as it contains some corporate-specific configurations, but its ancestor [TheseFooolishThings SuperPOM](http://bitbucket.org/tidalwave/thesefoolishthings-superpom-src) has been designed to be reusable. Please have a look at it. This super POM adds to its ancestor: + some Tidalwave variables that refers to the issue tracker, continuous integration system, etc...; + the definitions of versions of a number of commonly used libraries and their dependency management: * [AspectJ](https://www.eclipse.org/aspectj) * [Hamcrest Matchers](http://hamcrest.org/JavaHamcrest) * [JSR 330](https://github.com/google/guice/wiki/JSR330) * [Jakarta XML Binding (JAXB)](https://eclipse-ee4j.github.io/jaxb-ri/) * [Spotbugs annotations](https://spotbugs.readthedocs.io) * [JUnit](https://junit.org/junit5) * [Logback](http://logback.qos.ch) * [Lombok](https://projectlombok.org) * [SLF4J](slf4j.org) * [Spring 5](https://spring.io/projects/spring-framework) * [TestNG](https://testng.org) + the definition for Tidalwave 3rd party repository (stuff that is not available on Maven Central); + a profile for using the [TheseFoolishThings](http://tidalwave.it/projects/thesefoolishthings) Event Bus (```it.tidalwave-spring-messagebus-v1```); + profiles for the [Mycila License plugin](https://github.com/mycila/license-maven-plugin); + configuration of the UMLGraphDoc maven plugin; + the configuration for the TheseFoolishThings TestNG listener (which provides enhanced test logging); + definitions of some custom javadoc tags; + a blacklist for some old artifacts; + some other minor customisations.

JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extensible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.