Related papers: UDBMS: Road to Unification for Multi-model Data Ma…
Recent trends in information management involve the periodic transcription of data onto secondary devices in a networked environment, and the proper scheduling of these transcriptions is critical for efficient data management. To assist in…
Relational databases play a central role in many information systems. Their schema contains structural (e.g. tables and columns) and behavioral (e.g. stored procedures or views) entity descriptions. Then, just like for ``normal'' software,…
Query answering over probabilistic data is an important task but is generally intractable. However, a new approach for this problem has recently been proposed, based on structural decompositions of input databases, following, e.g., tree…
Mapping is a time-consuming process for deploying robotic systems to new environments. The handling of maps is also risk-adverse when not managed effectively. We propose here, a standardised approach to handling such maps in a manner which…
As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an urgent need to develop scalable and sustainable tools to simplify the process of data science, to make it easier to keep track of the analyses being…
The article deals with the problem which led to Big Data. Big Data information technology is the set of methods and means of processing different types of structured and unstructured dynamic large amounts of data for their analysis and use…
Blockchain technology is a Distributed Ledger Technology mainly used to store information in an immutable and secure way, but scalability and throughput issues are major challenges. Integration of the NoSQL paradigm within a Blockchain…
In today world, organizations like Google, Yahoo, Amazon, Facebook etc. are facing drastic increase in data. This leads to the problem of capturing, storing, managing and analyzing terabytes or petabytes of data, stored in multiple formats,…
Unimodality constitutes a key property indicating grouping behavior of the data around a single mode of its density. We propose a method that partitions univariate data into unimodal subsets through recursive splitting around valley points…
Knowledge management systems (KMS) are in high demand for industrial researchers, chemical or research enterprises, or evidence-based decision making. However, existing systems have limitations in categorizing and organizing paper insights…
This paper introduces Web3DB, a decentralized relational database management system (RDBMS) designed to align with the principles of Web 3.0, addressing critical shortcomings of traditional centralized DBMS, such as data privacy, security…
Databases are increasingly embracing AI to provide autonomous system optimization and intelligent in-database analytics, aiming to relieve end-user burdens across various industry sectors. Nonetheless, most existing approaches fail to…
In the paper a new approach to data representation and manipulation is described, which is called the concept-oriented data model (CODM). It is supposed that items represent data units, which are stored in concepts. A concept is a…
Large organizations today are being served by different types of data processing and informations systems, ranging from the operational (OLTP) systems, data warehouse systems, to data mining and business intelligence applications. It is…
In today's world data is being generated at a high rate due to which it has become inevitable to analyze and quickly get results from this data. Most of the relational databases primarily support SQL querying with a limited support for…
In the past few decades, the life sciences have experienced an unprecedented accumulation of data, ranging from genomic sequences and proteomic profiles to heavy-content imaging, clinical assays, and commercial biological products for…
Most research on data discovery has so far focused on improving individual discovery operators such as join, correlation, or union discovery. However, in practice, a combination of these techniques and their corresponding indexes may be…
This vision paper lays the preliminary foundations for Data Narrative Management Systems (DNMS), systems that enable the storage, sharing, and manipulation of data narratives. We motivate the need for such formal foundations and introduce a…
The advent of data-driven science in the 21st century brought about the need for well-organized structured data and associated infrastructure able to facilitate the applications of Artificial Intelligence and Machine Learning. We present an…
Scientific applications produce a huge amount of data, which imposes serious management and analysis challenges. In particular, limitations in current database management systems prevent their adoption in simulation applications, in which…