The Experts below are selected from a list of 204300 Experts worldwide ranked by ideXlab platform
Kari Smolander - One of the best experts on this subject based on the ideXlab platform.
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where is current research on blockchain Technology a systematic review
PLOS ONE, 2016Co-Authors: Jesse Ylihuumo, Deokyoon Ko, Sujin Choi, Sooyong Park, Kari SmolanderAbstract:Blockchain is a decentralized transaction and Data Management Technology developed first for Bitcoin cryptocurrency. The interest in Blockchain Technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and Data integrity without any third party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain Technology. Our objective is to understand the current research topics, challenges and future directions regarding Blockchain Technology from the technical perspective. We have extracted 41 primary papers from scientific Databases. The results show that focus in over 80% of the papers is on Bitcoin system and less than 20% deals with other Blockchain applications including e.g. smart contracts and licensing. The majority of research is focusing on revealing and improving limitations of Blockchain from privacy and security perspectives, but many of the proposed solutions lack concrete evaluation on their effectiveness. Many other Blockchain scalability related challenges including throughput and latency have been left unstudied. On the basis of this study, recommendations on future research directions are provided for researchers.
Wang Guoren - One of the best experts on this subject based on the ideXlab platform.
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Study on real-time Data stream Management techniques
Computer Engineering, 2004Co-Authors: Wang GuorenAbstract:Data stream is an emerging novel Data Management Technology,which has been widely used in many mission-critical fields such as sensor network,real-time monitoring,real-time detection and analysis. The characteristics of real-time Data streams and their related key techniques were discussed,three typical Data stream systems were surveyed,the design ideas of a Data stream Management system——RealStream were presented.
Jesse Ylihuumo - One of the best experts on this subject based on the ideXlab platform.
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where is current research on blockchain Technology a systematic review
PLOS ONE, 2016Co-Authors: Jesse Ylihuumo, Deokyoon Ko, Sujin Choi, Sooyong Park, Kari SmolanderAbstract:Blockchain is a decentralized transaction and Data Management Technology developed first for Bitcoin cryptocurrency. The interest in Blockchain Technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and Data integrity without any third party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain Technology. Our objective is to understand the current research topics, challenges and future directions regarding Blockchain Technology from the technical perspective. We have extracted 41 primary papers from scientific Databases. The results show that focus in over 80% of the papers is on Bitcoin system and less than 20% deals with other Blockchain applications including e.g. smart contracts and licensing. The majority of research is focusing on revealing and improving limitations of Blockchain from privacy and security perspectives, but many of the proposed solutions lack concrete evaluation on their effectiveness. Many other Blockchain scalability related challenges including throughput and latency have been left unstudied. On the basis of this study, recommendations on future research directions are provided for researchers.
Yi-ping Phoebe Chen - One of the best experts on this subject based on the ideXlab platform.
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Content-Based Indexing and Retrieval Using MPEG-7 and X-Query in Video Data Management Systems
World Wide Web, 2002Co-Authors: Dian Tjondronegoro, Yi-ping Phoebe ChenAbstract:Current advances in multimedia Technology enable ease of capturing and encoding digital video. As a result, video Data is rapidly growing and becoming very important in our life. It is because video can transfer a large amount of knowledge by providing combination of text, graphics, or even images. Despite the vast growth of video, the effectiveness of its usage is very limited due to the lack of a complete Technology for the organization and retrieval of video Data. To date, there is no “perfect” solution for a complete video Data-Management Technology, which can fully capture the content of video and index the video parts according to the contents, so that users can intuitively retrieve specific video segments. We have found that successful content-based video Data-Management systems depend on three most important components: key-segments extraction, content descriptions and video retrieval. While it is almost impossible for current computer Technology to perceive the content of the video to identify correctly its key-segments, the system can understand more accurately the content of a specific video type by identifying the typical events that happens just before or after the key-segments (specific-domain-approach). Thus, we have proposed a concept of customisable video segmentation module, which integrates the suitable segmentation techniques for the current type of video. The identified key-segments are then described using standard video content descriptions to enable content-based retrievals. For retrieval, we have implemented XQuery, which currently is the most recent XML query language and the most powerful compared to older languages, such as XQL and XML-QL.
Carlos Scheidegger - One of the best experts on this subject based on the ideXlab platform.
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A Structured Review of Data Management Technology for Interactive Visualization and Analysis
IEEE transactions on visualization and computer graphics, 2021Co-Authors: Leilani Battle, Carlos ScheideggerAbstract:In the last two decades, interactive visualization and analysis have become a central tool in Data-driven decision making. Concurrently to the contributions in Data visualization, research in Data Management has produced Technology that directly benefits interactive analysis. Here, we contribute a systematic review of 30 years of work in this adjacent field, and highlight techniques and principles we believe to be underappreciated in visualization work. We structure our review along two axes. First, we use task taxonomies from the visualization literature to structure the space of interactions in usual systems. Second, we created a categorization of Data Management work that strikes a balance between specificity and generality. Concretely, we contribute a characterization of 131 research papers along these two axes. We find that five notions in Data Management venues fit interactive visualization systems well: materialized views, approximate query processing, user modeling and query prediction, muiti-query optimization, lineage techniques, and indexing techniques. In addition, we find a preponderance of work in materialized views and approximate query processing, most targeting a limited subset of the interaction tasks in the taxonomy we used. This suggests natural avenues of future research both in visualization and Data Management. Our categorization both changes how we visualization researchers design and build our systems, and highlights where future work is necessary.
