Teresa Zawadzka

Terminological and assertional queries in KQL knowledge access language

One of the directions of development of information systems in recent years is the evolution of data-based systems into the knowledge-based systems. As a part of this process there is ongoing work on a whole range of languages for accessing knowledge bases. They can be used in a variety of applications, however their main drawback is the lack of clearly defined algebra representing a theoretical basis for them. For instance, such a basis is the relational algebra for SQL. The paper presents a new language for accessing knowledge bases that is built on a solid, theoretical foundation - the algebra of ontological modules.

Managing Data from Heterogeneous Data Sources Using Knowledge Layer

In the process of data integration using ontologies it is important to manage data from external data sources in the same way as data stored in the Knowledge Base. In previous papers [1], [2] the way of inference from data stored in the Knowledge Base, using Knowledge Cartography idea has been presented. However, this solution requires loading all data to the Knowledge Base. The solution presented in this paper shows how the Knowledge Cartography can be used to infer from data stored in external data sources, without loading them to the Knowledge Base. The presented solution is to enrich each data source with an additional layer that allows managing data using signatures. The paper additionally describes the results of tests comparing times of inference when data are loaded to the Knowledge Base and when data are fetched on demand.

Modularized Knowledge Bases Using Contexts, Conglomerates and a Query Language

The paper presents a novel approach to design and development of a modularized knowledge base. It is assumed that the knowledge base consists of a terminology (axioms) and a world description (assertions), both formulated in a Description Logics (DL) dialect. The approach is oriented towards decomposition of a knowledge base into logical components called contexts and further into semantic components called conglomerates. Both notions were elaborated separately elsewhere. The paper shows how contexts and conglomerates concepts can work in harmony to create a maintainable knowledge base. An architecture of a system that conforms to this approach, which additionally uses a query language called KQL (Knowledge Query Language), is presented. The approach is intended to be used to build a prototypical system that aims at integrating knowledge on cultural heritage coming from digital libraries, including user-defined libraries. The thorough discussion of related work is also given.

Processing and Querying Description Logic Ontologies Using Cartographic Approach

Description Logic (DL) is a formalism for knowledge representation that recently has gained widespread recognition among knowledge engineers. After a brief introduction to DL, the paper presents a DL reasoner developed at Gdansk University of Technology (GUT). The reasoner, called KaSeA, is based on an original idea called Knowledge Cartography. The paper presents basics of Knowledge Cartography, its potentials and limitations, and compares the solution with other DL reasoners.

Theoretical and Architectural Framework for Contextual Modular Knowledge Bases

The paper presents the approach aimed at building modularized knowledge bases in a systematic, context-aware way. The paper focuses on logical modeling of such knowledge bases, including an underlying SIM metamodel. The architecture of a comprehensive set of tools for knowledgebase systems engineering is presented. The tools enable an engineer to design, create and edit a knowledge base schema according to a novel context approach presented elsewhere by the authors. It is explained how a knowledge base built according to SIM (Structured-Interpretation Model) paradigm is processed by a prototypical reasoner Conglo-S, which is a custom version of widely known Pellet reasoner extended with support for modules of ontologies called tarsets (also introduced elsewhere under the name of conglomerates). The user interface of the system is a plug-in to Protege ontology editor that is a standard tool for development of Semantic Web ontologies. Possible applications of the presented framework to development of knowledge bases for culture heritage and scientific information dissemination are also discussed.

EvOLAP Graph - Evolution and OLAP-Aware Graph Data Model.

The objective of this paper is to propose a graph model that would be suitable for providing OLAP features on graph databases. The included features allow for a multidimensional and multilevel view on data and support analytical queries on operational and historical graph data.

DUABI - Business Intelligence Architecture for Dual Perspective Analytics

A significant expansion of Big Data and NoSQL databases made it necessary to develop new architectures for Business Intelligence systems based on data organized in a non-relational way. There are many novel solutions combining Big Data technologies with Data Warehousing. However, the proposed solutions are often not sufficient enough to meet the increasing business demands, such as low data latency while still maintaining high functionality, efficiency and reliability of Data Warehouses. In this paper we propose DUABI - the BI architecture that enables both traditional analytics over OLAP Cube as well as near real-time analytics over the data stored in the NoSQL database. The presented architecture leverages features of NoSQL databases for scalability and fault-tolerance with the use of mechanisms like sharding and replication.

SMAQ – A Semantic Model for Analytical Queries

While the Self-Service Business Intelligence (BI) becomes an important part of organizational BI solutions there is a great need for new tools allowing to construct ad-hoc queries by users with various responsibilities and skills. The paper presents a Semantic Model for Analytical Queries – SMAQ allowing to construct queries by users familiar with business events and terms, but being unaware of database or data warehouse concepts and query languages such as MDX or SQL. The key idea of SMAQ is to provide a reference model that allows building user interfaces, even those based on natural language, independently on data models and query languages.

Defining trustworthiness in Semantic Web by ontological assertions

The paper introduces the model of knowledge management system that handles some aspects of trustworthiness. A method of defining trustworthiness in semantic Web and reasoning over knowledge enriched with trust information is presented. The method provides a way of building trustworthiness information into the assertional part of an ontology. Defining trustworthiness is meant as assigning a set of features to unary and binary assertions. The model defines a ldquotrust ontologyrdquo - an ontology that allows for assigning some features to specified assertions. There is also explained how Semantic Web agents could express their requirements for trust while querying a knowledge management system. The paper concludes with some implementation aspects of a prototype system that incorporates the presented model.

Algorithms for query processing in a distributed knowledge integration system

The main goal of the paper is to introduce a framework of knowledge integration system. The framework is based on the ontology integration system described by Calvanese in [1], [2] and extends it to a multi-layer framework. The paper also shows how usage of cartographic representation of knowledge [3], [4] to store and process ontologies in knowledge sources and building mappings between ontologies allows for implementing efficient algorithms of query processing in a distributed environment of a knowledge integration system. A new method of creating mappings between different terminologies, called CMC, is described. Using the cartographic representation it is possible to map regions (that correspond to all satisfiable logical combinations of terms) defined in one ontology to regions of another one. Moreover, SPIDER - a query processing algorithm, based on cartographic mappings, is described. The paper ends with a presentation of the complexity of presented methods and algorithms.