doc. Ing. Jan Janoušek, Ph.D.

2015

With the vast amount of data needed to be archived, indexed and procesed, special data structures are required. The tree is a typical data structure which is used very often for hierarchically storing data. Specialized algorithms are needed for indexing tree data structures and also accessing, extracting and analyzing data stored in them. Another goal of this project is a design and implementation of novel methods of data compression and indexing in two areas: DNA sequence compression using dictionary methods and approximate pattern matching in genomes.

2014

With the vast amount of data needed to be archived, indexed and procesed, special data structures are required. The tree is a typical data structure which is used very often for hierarchically storing data. Specialized algorithms are needed for indexing tree data structures and also accessing, extracting and analyzing data stored in them. The aim of this research is to design efficient yet simple to understand algorithms dealing with tree pattern matching (both exact and approximate) and tree indexing, and provide a toolkit implementation. Another goal of this project is a design and implementation of novel methods of data compression in two areas: DNA sequence compression and difference compression of files.

2017 - 2019

With the vast amount of data needed to be archived, indexed and procesed, efficient data structures and algorithms are required. The tree is a typical data structure which is used very often for hierarchically storing data. Another goal of this project is to design and implement novel methods for data indexing combined with data compression and methods for various approximate pattern matching over the indexes. The indexes and pattern matching find applications in searching in DNA and RNA sequences. Another topic of our research is the area of algorithms for implementing dynamic programming languages.

2017 - 2019

The key trend in management has been to attempt to make all decisions data driven. A critical element in this effort has been the data warehouse or, more broadly, business intelligence (BI). Fast changes are forcing companies to develop faster, and fast development requires effective BI management, so-called data governance (DG). Without solid DG processes and rapid development in place, companies are not able to use their own data successfully. The ongoing big data revolution brings more issues to an already complex field and shows that current DG technologies are not ready for the future. The goal of this project is to create tools which will ensure effective DG in big data environments and thereby protect the billions of dollars invested into BI development worldwide.

2016

With the vast amount of data needed to be archived, indexed and procesed, efficient data structures and algorithms are required. The tree is a typical data structure which is used very often for hierarchically storing data. Another goal of this project is to design and implement novel methods for data indexing combined with data compression and methods for various approximate pattern matching over the indexes. The indexes and pattern matching find applications in searching in DNA and RNA sequences.

2013

With the vast amount of data needed to be archived, indexed and procesed, special data structures are required. The tree is a typical data structure which is used very often for hierarchically storing data. Specialized algorithms are needed for indexing tree data structures and also accessing, extracting and analyzing data stored in them. The aim of this research is to design efficient yet simple to understand algorithms dealing with tree pattern matching (both exact and approximate) and tree indexing, and provide a toolkit implementation. Another goal of this project is design and implementation of novel methods of data compression in two areas: first, music score compression; second, natural language compression.

2010 - 2011

With the vast amount of data needed to be archived, indexed and procesed, special data structures are required. The tree is a typical data structure which is used very often for hierarchically storing data. Specialized algorithms are needed for indexing tree data structures and also accessing, extracting and analyzing data stored in them. Examples of applications can be the optimization of abstract syntax trees in the process of compiling, term-rewriting, mechanical theorem proving, searching in phylogenic trees, indexing the secondary structure of RNA, searching in XML documents and evaluating the source code of functional programming languages. For this purpose we have introduced a new research discipline called Arbology, a generalization of Stringology, that deals with tree structures. We use the pushdown automaton as our computational model since the linear notions of trees, being generated by context-free grammars, are in fact context-free languages. The aim of this research is to

2013 - 2016

Environments of BI Systems and DWHs consist of thousands of program artefacts. An automatized management of a large amount of the artefacts requires highly powerful tools, which have been lacking in the market. Using recent theoretical results and long-term practical experiences with a maintenance of environments based on SQL and XML standards, we will create tools that will represent a revolutionary change in the area of the current tools of Quallity Assurance, wherein large financial means have been invested.

2012

With the vast amount of data needed to be archived, indexed and procesed, special data structures are required. The tree is a typical data structure which is used very often for hierarchically storing data. Specialized algorithms are needed for indexing tree data structures and also accessing, extracting and analyzing data stored in them. Examples of applications can be the optimization of abstract syntax trees in the process of compiling, term-rewriting, mechanical theorem proving, searching in phylogenic trees, indexing the secondary structure of RNA, searching in XML documents and evaluating the source code of functional programming languages. For this purpose we have introduced a new research discipline called Arbology, a generalization of Stringology, that deals with tree structures. We use the pushdown automaton as our computational model since the linear notions of trees, being generated by context-free grammars, are in fact context-free languages. The aim of this research is to

2012 - 2013

User interface part of software application development is considered time consuming (according to recent research up 50% of the total time is devoted to user interface). Code fragment of the interface part are often complex and hard to read. This is because the interface combines multiple cross-cutting concerns such as security, presentation, layout, validation or contextual help. Besides the presentation aspect itself are here captured information, that already exist elsewhere in the application. This makes the development and maintenance hard. The goal of our project is to minimize manual work that is related to user interface development. We suggest that machine driven code inspection is applied to transform the information to user interface. This allows us to separate cross-cutting interface concerns and manage these individually. All concerns can be combined and weaved together in the transformation process. Besides optimization of the interface code the interface can be generat