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Defining a dynamic user access rights data model and creating and analyzing an effective and safe full-text search algorithm based on the model

The Objective:

The research aims to explore the options provided by NoSQL technologies to create data search algorithms based on paradigm of flexible user access rights model and to develop safe and effective algorithm for information search, tuned for best use with Enterprise Content managent systems.

The Status:

The project started August 2016 and will continue until October 2017.

Analysis  of hybrid model of relational/NoSQL data persistency to enable effective and flexible access to both current and history data

The Objective:

The research targets a creation of hybrid model for data persistence spanning a relational data model to handle current data and NoSQL data model for handling of history data. The options for usage of the model in Enterprise Content Management systems are to be analysed and the prototype is to be created and evaluated.

The Status:

The project will start November 2017 and will continue until October 2018.

The research of the options for the automated analysis and compliance monitoring of regulatory documents and business processes

The Objective:

Options of the automated analysis of the regulatory documents are researched to create a methodology and a prototype for the automated analysis of the regulatory documents and compliance management of the business process descriptions against the requirements of the regulatory documents.

  • I. Buksa. Business processes and regulations compliance management technology. IEEE 22nd International Requirements Engineering Conference (RE), 2014, Karlskrona, 25-29.08.2014, p. 489-493. DOI: 10.1109/RE.2014.6912304.
  • Survilo, L., Bukša, I., Gaidukovs, A., Shendryk, V. Analysis of Questionnaire Results in the Use of BP and ND in Public Administration. Applied Computer Systems. Vol.16, 2014, pp.97-104. ISSN 2255-8683. e-ISSN 2255-8691. Available from: doi:10.1515/acss-2014-0019, skat.:

The research of Advanced Visualization methods for the analysis of linked Big data

The Objective:

The research intents to:

  • create visualization models effectively usable for data analysis;
  • define architecture for the components of advanced visualization system – clustering technology, cloud computing and schemaless  NoSQL data store;
  • benchmark the usage of the architecture and models created for a range of data volumes and data flow velocities. 
  • J. Rats. NoSQL document datastore as a backend of the visualization platform for ECM system. WSEAS 9th International Conference on Computer Engineering and Applications (CEA ’15), Dubai, United Arab Emirates, February 22-24, 2015, p. 354-359

The research of the automation problems of the business processes for effective management of Big Data

The Objective:

The research deals with creation of the architecture and  methodology for development of the mentioned architecture and user interface for Big data Enterprise content  management systems, featuring:

  • clustering technologies, cloud computing and NoSQL data stores, to provide interactive use of document-oriented software systems;
  • multi-agent systems for parallel processing of the data;
  • methods of ranked grouping of data.
  • J. Rats, G. Ernestsons. Using of Cloud Computing, Clustering and Document-oriented Database for Enterprise Content Management. The Second International Conference on Informatics & Applications (ICIA2013), Lodz University of Technology, Poland, September 23-25, 2013, p. 72-76.
  • Juris Rats, Gints Ernestsons. Clustering and Ranked Search for Enterprise Content Management. International Journal of E-Entrepreneurship and Innovation, Volume 4, Issue 4. Copyright © 2013. p. 20-31, skat.:

Research projects completes within IT Competence Centre projects.