Business processes represent an essential part of every business as they create the structure within which a company operates. In order to capture, understand, and improve these processes, business process models are created using various modeling notations such as BPMN. One of the key challenges is validating that these models reflect the reality of the business in a correct and accurate manner. Only then it is possible to develop information systems based on these models that truly support the workflow of their users. Based on our previous research, this paper presents a novel approach that enables the validation of business process models through simulation in graph databases. As a starting point for our approach, we propose a conversion of models expressed in BPMN into OntoUML, a modeling notation that provides a higher level of abstraction as well as unique integration of the process and structural perspectives on the problem domain. Conversion to OntoUML also enables us to utilize our tool for automated generation of integrity constraints for Neo4j graph databases, ensuring consistency and adherence to the defined rules. We are then able to validate these models by simulating object instantiation, progressively creating and modifying graph representations of entities and relationships to detect inconsistencies. This simulation not only reveals potential flaws in the original business process models but also offers actionable insights for their refinement. By shifting the focus to the underlying data and its lifecycle, our approach provides a novel perspective on business process model validation, also bridging the gap between models and their practical implementation.

The purpose of this paper is to analyze and implement incremental updates of data lineage storage in the software tool Manta Flow. The basis of this work is the study of current data lineage storage in Manta Flow, research of existing solutions of incremental updates in version control systems, research of incremental backups in databases, analysis and design of a new solution of incremental updates in Manta Flow and a subsequent prototype implementation and performance testing execution. The resulting prototype can be deployed into the existing Manta Flow product, reducing time complexity of updates in data lineage storage in orders of magnitude.

We propose a method for indexing graph patterns within a graph database. A graph database consists of a labelled property graph. The index is organized in a hash table and stored in the different database than the database graph. The method enables to create, use, and update indexes that are used to speed-up the process of matching graph patterns. The prototype implementing the method was analyzed for Neo4j graph database engine. Pattern indexes are stored in the embedded database MapDB. Three graph databases are used for experiments with pattern indexes. The paper provides a comparison between queries with and without using indexes.

International audience

Comparing graph databases with traditional, e.g., relational databases, some important database features are often missing there. Particularly, a graph database schema including integrity constraints is not explicitly defined, also a conceptual modelling is not used at all. It is hard to check a consistency of the graph database, because almost no integrity constraints are defined. In the paper, we discuss these issues and present current possibilities and challenges in graph database modelling. Also a conceptual level of a graph database design is considered. We propose a sufficient conceptual model and show its relationship to a graph database model. We focus also on integrity constraints modelling functional dependencies between entity types, which reminds modelling functional dependencies known from relational databases and extend them to conditional functional dependencies.

The paper presents shortly a history and development of database management tools in last decade. The movement towards a higher database performance and database scalability is discussed in the context to requirements of practice. These include Big Data and Big Analytics as driving forces that together with a progress in hardware development led to new DBMS architectures. We describe and evaluate them mainly in terms of their scalability. We focus also on a usability of these architectures which depends strongly on application environment. We also mention more complex software stacks containing tools for management of real-time analysis and intelligent processes.

Physicians are overwhelmed with many different drugs and the need to know a lot of information about all of them. That is, however, almost impossible in the fast evolving area of pharmaceutical industry. Although many data sources about drugs are published on the Web, structured or unstructured, it is very time consuming to search through them. In this paper we identify these data sources according to information needs of physicians. We show that they can be relatively easily integrated using the Linked Data principles and, in case of unstructured data, NLP methods. An application on the top of the integrated data sets is presented as a possible tool for clinical decision support.

Big Data, big number of users, and cloud computing are driving the adoption of new database architectures, particularly NoSQL databases. Both research and practice indicate that traditional universal DBMS architecture hardly satisfies new trends in data processing in such environment. NoSQL databases enable better application development productivity through a more flexible data model, greater ability to scale dynamically to support more users and data, an ability to develop highly responsive applications and more complex processing of data.

This paper describes the concept and some preliminary experiments of extension of the sitIT.cz portal – the social network of the ICT specialists in Czech Republic. SitIT.cz interconnects ICT specialists and offers effective search according to several types of structured – machine readable – profiles. It is intended to support technology transfer, sharing information, building teams and to enable discussions, especially targeted to increase of competitiveness of R&D in ICT. Main stimulus for sitIT.cz extension came from acquaintance with software development which often needs extensive testing – not only technological but also from users' point of view. Extension can make network more attractive for both developers and users. We propose new structured profiles that can be used for evaluating software and allowing developers obtain as valuable feedback as possible. One of main outcomes of this system is creating baseline knowledge by humans for further comparison and/or training.

This paper considers schemaless XML data stored in a column-oriented storage, particularly in C-store. A two-level model of C-store based on XML-enabled relational databases is supposed. The axes of XPath language in this environment have been studied in [3]. A low level memory system enables the estimation of the number of two abstract operations providing an interface to an external memory. The algorithms developed are mostly of logarithmic complexity in n, where n is the number of nodes of XML tree associated with an XML document. Here we extend the approach to the XPath fragment using only child and descendant axes and estimate the complexity of evaluating its queries.

The paper is focused on so called NoSQL databases. In context of cloud computing, architectures and basic features of these databases are studied, particularly their horizontal scalability and concurrency model, that is mostly weaker than ACID transactions in relational SQL-like database systems. Some characteristics like a data model and querying capabilities are discussed in more detail. The paper also contains an overview of some representatives of NoSQL databases.

In this paper we briefly describe a new conceptual model for XML called XSEM. It is a combination of several approaches in the area. It divides the conceptual modeling process to conceptual and structural level. At the conceptual level, we design an overall conceptual schema of a domain independently on the required hierarchical representations of the data in XML documents. At the structural level, we design required hierarchical representations of the modeled data in different types of XML documents. In this paper, we further extend XSEM for modeling IS-A hierarchies. We also show how conceptual XSEM schemes can be represented at the logical level in XML schemes specified in the XML Schema language.

We discuss models of user preferences in Web environment. We construct a model for user preference querying over a number of data sources and ordering of answers by a combination of particular attribute rankings. We generalize Fagin's algorithm in two directions - we develop some new heuristics for top-k search in the model without random access and propose a method of ordering lists of objects by user fuzzy function. To enable different user preferences our system does not require objects to be sorted - instead we use a B+- tree on each of the attribute domains. This leads to a more realistic model of Web services. We implement our methods and heuristics for search of top-k answers into Tokaf middleware framework prototype. We describe experiments with Tokaf and compare different performance measures with some other methods.

Multi-dimensional data structures are applied in many real index applications, i.e. data mining, indexing multimedia data, indexing of text documents and so on. Many index structures and algorithms have been proposed. There are two major approaches to multi-dimensional indexing: data structures to indexing metric and vector spaces. R-trees, R*-trees and (B)UB-trees are representatives of the vector data structures. These data structures provide efficient processing of many types of queries, i.e. point queries, range queries and so on. As far as the vector data structures are concerned, the range query retrieves all points in defined hyper box in an n-dimensional space. The narrow range query is an important type of the range query. Its processing is inefficient in vector data structures. Moreover, the efficiency decreases as the dimension of the indexed space increases. We depict an application of the signature for more efficient processing of narrow range queries. The approach puts the signature into the multi-dimensional data structures like R-tree or UB-tree but original functionalities are preserved, i.e. the range query algorithm for general range query. The novel data structure is called the signature data structure, e.g., Signature R-tree or Signature UB-tree.

We suppose collections of XML data described by Document Type Definitions (DTDs). This data has been generated by applications and plays a role of OLTP database(s). A star schema, a well-known technique used in data warehousing, can be applied. Then dimension information is supposed to be contained in XML data. We will use the notions of subDTD and view, and formulate referential integrity constraints in XML environment. We use simple pattern matching capabilities of current XML query languages for XML view specification and tree embedding algorithms for these purposes. A dimension hierarchy is defined as a set of logically connected collections of XML data. Facts may be also conceived as elements of an XML document. Due to the structural complexity of XML data the approach requires subtler formal model than it is done with conventional dimension and fact tables described by classical star schemes. In consequence, our approach captures more from heterogeneity of source databases than it is done in classical relational approaches to data warehousing.

The topic of the XML language is one of the most discussed in the IS/IT community today. The primary goal of XML is to provide marking text components and use such data for exchange among information sources. The goal of the paper is to present a database view on XML data. We formulate a type system powerful enough to describe XML data in a set- and function-oriented manner. A version of a typed /spl lambda/ calculus is used as a framework to manipulate typed XML data. Such a language called XML-/spl lambda/, has sound semantics and is extensible with various mathematical functions. Consequently, we can use it as a query language over XML objects. The results obtained by querying are either XML data or other data structures, e.g. relations, nested tables etc. We present a collection of examples of queries in XML-/spl lambda/ and compare them with XML-QL.

Summary form only given. We present a new compression method, called WLZW, which is a word-based modification of classic LZW. The algorithm is two-phase, it uses only one table for words and non-words (so called tokens), and a single data structure for the lexicon is usable as a text index. The length of words and non-words is restricted. This feature improves the compress ratio achieved. Tokens of unlimited length alternate, when they are read from the input stream. Because of restricted length of tokens alternating of tokens is corrupted, because some tokens are divided into several parts of same type. To save alternating of tokens two special tokens are created. They are empty word and empty non-word. They contain no character. Empty word is inserted between two non-words and empty non-word between two words. Alternating of tokens is saved for all sequences of tokens. The alternating of tokens is an important piece of information. With this knowledge the kind of the next token can be predicted. One selected (so-called victim) non-word can be deleted from input stream. An algorithm to search the victim is also presented. In the decompression phase, a deleted victim is recognized as an error in alternating of words and non-words in sequence. The algorithm was tested on many texts in different formats (ASCII, RTF). The Canterbury corpus, a large set, was used as a standard for publication results. The compression ratio achieved is fairly good, on average 25%-22%. Decompression is very fast. Moreover, the algorithm enables evaluation of database queries in given text. This supports the idea of leaving data in the compressed state as long as possible, and to decompress it when it is necessary.