Knowledge-based out-of-core algorithms for data management in visualization

Journal ArticleData management is the very first issue in handling very large datasets. Many existing out-of-core algorithms used in visualization are closely coupled with application-specific logic. This paper presents two knowledgebased out-of-core prefetching algorithms that do not use hard-coded rendering-related logic. They acquire the knowledge of the access history and patterns dynamically, and adapt their prefetching strategies accordingly. We have compared the algorithms with a demand-based algorithm, as well as a more domain-specific out-of-core algorithm. We carried out our evaluation in conjunction with an example application where rendering multiple point sets in a volume scene graph put a great strain on the rendering algorithm in terms of memory management. Our results have shown that the knowledge-based approach offers a better cache-hit to disk-access trade-off. This work demonstrates that it is possible to build an out-of-core prefetching algorithm without depending on rendering-related application-specific logic. The knowledge based approach has the advantage of being generic, efficient, flexible and self-adaptive

Business Process Visualization - Use Cases, Challenges, Solutions

The proper visualization and monitoring of their (ongoing) business processes is crucial for any enterprise. Thus a broad spectrum of processes has to be visualized ranging from simple, short–running processes to complex long–running ones (consisting of up to hundreds of activities). In any case, users shall be able to quickly understand the logic behind a process and to get a quick overview of related tasks. One practical problem arises when different fragments of a business process are scattered over several systems where they are often modeled using different process meta models (e.g., High–Level Petri Nets). The challenge is to find an integrated and user–friendly visualization for these business processes. In this paper we discover use cases relevant in this context. Since existing graph layout approaches have focused on general graph drawing so far we further develop a specific approach for layouting business process graphs. The work presented in this paper is embedded within a larger project (Proviado) on the visualization of automotive processes

Curriculum Guidelines for Undergraduate Programs in Data Science

The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

VisIVOWeb: A WWW Environment for Large-Scale Astrophysical Visualization

This article presents a newly developed Web portal called VisIVOWeb that aims to provide the astrophysical community with powerful visualization tools for large-scale data sets in the context of Web 2.0. VisIVOWeb can effectively handle modern numerical simulations and real-world observations. Our open-source software is based on established visualization toolkits offering high-quality rendering algorithms. The underlying data management is discussed with the supported visualization interfaces and movie-making functionality. We introduce VisIVOWeb Network, a robust network of customized Web portals for visual discovery, and VisIVOWeb Connect, a lightweight and efficient solution for seamlessly connecting to existing astrophysical archives. A significant effort has been devoted for ensuring interoperability with existing tools by adhering to IVOA standards. We conclude with a summary of our work and a discussion on future developments

Intelligent Management and Efficient Operation of Big Data

This chapter details how Big Data can be used and implemented in networking and computing infrastructures. Specifically, it addresses three main aspects: the timely extraction of relevant knowledge from heterogeneous, and very often unstructured large data sources, the enhancement on the performance of processing and networking (cloud) infrastructures that are the most important foundational pillars of Big Data applications or services, and novel ways to efficiently manage network infrastructures with high-level composed policies for supporting the transmission of large amounts of data with distinct requisites (video vs. non-video). A case study involving an intelligent management solution to route data traffic with diverse requirements in a wide area Internet Exchange Point is presented, discussed in the context of Big Data, and evaluated.Comment: In book Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence, IGI Global, 201