Ontology-based end-user visual query formulation: Why, what, who, how, and which?

Value creation in an organisation is a time-sensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users’ understanding. However, on the one hand, today the most of world’s enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity—known as Big Data. This article presents and argues for ontology-based visual query formulation for end-users; discusses its feasibility in terms of ontology-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data; presents key conceptual aspects and dimensions, challenges, and requirements; and reviews, categorises, and discusses notable approaches and systems

PrefetchGuide: Capturing Navigational Access Patterns for Prefetching in Client/Server Object-Oriented/Object-Relational DBMSs

In prefetching, the objects that are expected to be accessed in the future are fetched from the server to the client in advance. Prefetching reduces the number of round-trips and increases the system performance. To prefetch object effectively, we need to correctly predict the future navigational patterns. In this paper, we propose the PrefetchGuide, a novel data structure that captures the navigational access patterns. We also formally define the notion of the attribute access log set and analyze the navigational access patterns that can be captured by the PrefetchGuide. We then present an prefetching algorithm using the PrefetchGuide. To show effectiveness of our algorithm, we have conducted extensive experiments in a prototype object-relational database management systems (DBMS). The results show that our method significantly outperforms the state-of-the-art prefetching method. These results indicate that our approach provides a practical method that can be implemented in commercial object-oriented/object-relationaI DBMSs. We believe our method is practically usable for object-oriented programmers and DBMS implementors. (C) 2002 Elsevier Science Inc. All rights reserved.X111014sciescopu

A tunable class hierarchy index for object-oriented databases using a multidimensional index structure

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Dynamic buffer allocation in video-on-demand systems

In video-on-demand (VOD) systems, as the size of the buffer allocated to user requests increases, initial latency and memory requirements increase. Hence, the buffer size must be minimized. The existing static buffer allocation scheme, however, determines the buffer size based on the assumption that the system is in the fully loaded state. Thus, when the system is in a partially loaded state, the scheme allocates a buffer larger than necessary to a user request. This paper proposes a dynamic buffer allocation scheme that allocates to user requests buffers of the minimum size in a partially loaded state, as well as in the fully loaded state. The inherent difficulty in determining the buffer size in the dynamic buffer allocation scheme is that the size of the buffer currently being allocated is dependent on the number of and the sizes of the buffers to be allocated in the next service period. We solve this problem by the predict, and-enforce strategy, where we predict the number and the sizes of future buffers based on inertia assumptions and enforce these assumptions at runtime. Any violation of these assumptions is resolved by deferring service to the violating new user request until the assumptions are satisfied. Since the,size of the current buffer is dependent on the sizes of the future buffers, it is represented by a recurrence equation. We provide a solution to this equation, which can be computed at the system initialization time for runtime efficiency. We have performed extensive analysis and simulation. The results show that the dynamic buffer allocation scheme reduces initial latency (averaged over the number of user requests in service from one to the maximum capacity) to (29.4)/(1) similar to (11.0)/(1) of that for the static one and, by reducing the memory requirement, increases the number of concurrent user requests to 2.36 similar to 3.25 times that of the static one when averaged over the amount of system memory available. These results demonstrate that the dynamic buffer allocation scheme significantly improves the performance and capacity of VOD systems.X1189sciescopu

DB-IR integration using tight-coupling in the Odysseus DBMS

As many recent applications require integration of structured data and text data, unifying database (DB) and information retrieval (IR) technologies has become one of major challenges in our field. There have been active discussions on the system architecture for DB-IR integration, but a clear agreement has not been reached yet. Along this direction, we have advocated the use of the tight-coupling architecture and developed a novel structure of the IR index as well as tightly-coupled query processing algorithms. In tight-coupling, the text data type is supported from the storage system just like a built-in data type so that the query processor can efficiently handle queries involving both structured data and text data. In this paper, for archival purposes, we consolidate our achievements reported at non-regular publications over the last ten years or so, extending them by adding greater details on the IR index and the query processing algorithms. All the features in this paper are fully implemented in the Odysseus DBMS that has been under development at KAIST for over 23 years. We show that Odysseus significantly outperforms two open-source DBMSs and one open-source search engine (with some exceptional cases) in processing DB-IR integration queries. These results indeed demonstrate superiority of the tight-coupling architecture for DB-IR integration.X110sciescopu

The clustering property of corner transformation for spatial database applications

Spatial access methods (SAMs) are often used as clustering indexes in spatial database systems. Therefore, a SAM should have the clustering property both in the index and in the data file. In this paper, we argue that corner transformation preserves the clustering property such that objects having similar sizes and positions in the original space tend to be placed in the same region in the transform space. We then show that SAMs based on corner transformation are able to maintain clustering both in the index and in the data file for storage systems with fixed object positions and propose the MBR-MLGF as an example to implement such an index. In the Storage systems with fixed object positions, the inserted objects never move during the operation of the system. Most storage systems currently available adopt this architecture. Extensive experiments comparing with the R-*-tree show that corner transformation indeed preserves the clustering property, and therefore, it can be used as a useful method for spatial query processing. This result reverses the common belief that transformation will adversely affect the clustering and shows that the transformation maintains as good clustering in the transform space as conventional techniques, such as the R*-tree, do in the original space. (C) 2002 Elsevier Science B.V. All rights reserved.X1188sciescopu

DB-IR integration using tight-coupling in the Odysseus DBMS

As many recent applications require integration of structured data and text data, unifying database (DB) and information retrieval (IR) technologies has become one of major challenges in our field. There have been active discussions on the system architecture for DB-IR integration, but a clear agreement has not been reached yet. Along this direction, we have advocated the use of the tight-coupling architecture and developed a novel structure of the IR index as well as tightly-coupled query processing algorithms. In tight-coupling, the text data type is supported from the storage system just like a built-in data type so that the query processor can efficiently handle queries involving both structured data and text data. In this paper, for archival purposes, we consolidate our achievements reported at non-regular publications over the last ten years or so, extending them by adding greater details on the IR index and the query processing algorithms. All the features in this paper are fully implemented in the Odysseus DBMS that has been under development at KAIST for over 23 years. We show that Odysseus significantly outperforms two open-source DBMSs and one open-source search engine (with some exceptional cases) in processing DB-IR integration queries. These results indeed demonstrate superiority of the tight-coupling architecture for DB-IR integration. © 2013, Springer Science+Business Media New York.

GDPR-Compliant Reputation System Based on Self-certifying Domain Signatures

Creating a distributed reputation system compliant with the GDPR Regulation faces a number of problems. Each record should be protected regarding its integrity and origin, while the record’s author should remain anonymous, as long as there is no justified legal reason to reveal his real identity. Thereby, the standard digital signatures cannot be applied to secure the records. In this paper we propose a Privacy Aware Distributed Reputation Evaluation system, where each subject of evaluation holds its recommendation record. By application of a novel technique of domain signatures we are able to guarantee that (a) integrity of each entry is strongly protected; in particular, the evaluation subject cannot modify it, (b) the author of each entry is anonymous, however all entries of the same author on the same subject appear under the same pseudonym (so the Sybil attacks are repelled), (c) the entries corresponding to the same author but for different evaluation subjects are unlinkable, (d) only registered users can create valid entries, (e) the real identity of the author of an entry can be revealed by relevant authorities by running a multi-party protocol, (f) for each entry one can create a pseudorandom key in a deterministic way. The first five features correspond directly to the requirements of the GDPR Regulation. In particular, they guard against profiling the users based on the entries created by them. In order to facilitate practical applications we propose to maintain a pseudorandom sample of all entries concerning a given evaluation subject. We show how to guarantee that the sample is fairly chosen despite the fact that the sample is kept by the evaluation subject. We present a few strategies enabling to mimic some important probability distributions for choosing the sample