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OntoDB: An Ontology-Based Database for Data Intensive Applications
TLDR
This paper proposes a new representation of ontology-based data, called table per class, which consists in associating a table to each ontology class, where all property values of a class instance are represented in a same row.
A personalization framework for OLAP queries
TLDR
This paper proposes a framework for personalizing OLAP queries and computes the part of the answer that respects both the user preferences and the visualization constraint, and a personalized structure for the visualization is proposed.
An Evolutionary Approach to Schema Partitioning Selection in a Data Warehouse
TLDR
This paper presents a genetic algorithm for schema partitioning selection problem and shows that the proposed algorithm gives better solutions since the search space is constrained by the schema partitions.
Data warehousing and OLAP over big data: current challenges and future research directions
TLDR
Open problems and actual research trends in the field of Data Warehousing and OLAP over Big Data are highlighted and several novel research directions arising in this field are derived.
GPU-Accelerated Database Systems: Survey and Open Challenges
TLDR
A reference architecture is proposed, indicating how GPU acceleration can be integrated in existing DBMSs, and key properties, important trade-offs and typical challenges of GPU-aware database architectures are presented.
Selection and Pruning Algorithms for Bitmap Index Selection Problem Using Data Mining
TLDR
This work proposes an approach which first prunes the search space of this problem using data mining techniques, and then based on the new search space, it uses a greedy algorithm to select BJIs that minimize the cost of executing a set of queries and satisfy a storage constraint.
A Data Mining Approach for selecting Bitmap Join Indices
TLDR
A data mining driven approach to prune the search space of bitmap join index selection problem uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk.
OntoDB: It Is Time to Embed Your Domain Ontology in Your Database
TLDR
This demonstration illustrates three main functionalities of OntoDB: a storage of a domain ontology and database content in the same repository, the possibility of querying databases at ontology level, and an automatic integration of heterogeneous data sources referencing/extending the samedomain ontology.
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