Research Issues on Geovisual Analytics for Petroleum Data Management

2018 ◽  
pp. 185-187
Author(s):  
Rifaat Abdalla
Keyword(s):  
Data Management ◽  
Research Issues ◽  
Geovisual Analytics

Challenges and Research Issues of Data Management in IoT for Large-Scale Petrochemical Plants

2018 ◽  
Vol 12 (3) ◽  
pp. 2509-2523 ◽  
Author(s):  
Lei Shu ◽  
Mithun Mukherjee ◽  
Michael Pecht ◽  
Noel Crespi ◽  
Son N. Han
Keyword(s):  
Data Management ◽  
Large Scale ◽  
Research Issues

scholarly journals Sports Big Data: Management, Analysis, Applications, and Challenges

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhongbo Bai ◽  
Xiaomei Bai
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Data Management ◽  
Rapid Growth ◽  
Growth Trend ◽  
Research Directions ◽  
Research Issues ◽  
Big Data Applications ◽  
Rich Information ◽  
Sports Data

With the rapid growth of information technology and sports, analyzing sports information has become an increasingly challenging issue. Sports big data come from the Internet and show a rapid growth trend. Sports big data contain rich information such as athletes, coaches, athletics, and swimming. Nowadays, various sports data can be easily accessed, and amazing data analysis technologies have been developed, which enable us to further explore the value behind these data. In this paper, we first introduce the background of sports big data. Secondly, we review sports big data management such as sports big data acquisition, sports big data labeling, and improvement of existing data. Thirdly, we show sports data analysis methods, including statistical analysis, sports social network analysis, and sports big data analysis service platform. Furthermore, we describe the sports big data applications such as evaluation and prediction. Finally, we investigate representative research issues in sports big data areas, including predicting the athletes’ performance in the knowledge graph, finding a rising star of sports, unified sports big data platform, open sports big data, and privacy protections. This paper should help the researchers obtaining a broader understanding of sports big data and provide some potential research directions.

scholarly journals Use of Social Media Data in Disaster Management: A Survey

2021 ◽  
Vol 13 (2) ◽  
pp. 46
Author(s):  
Jedsada Phengsuwan ◽  
Tejal Shah ◽  
Nipun Balan Thekkummal ◽  
Zhenyu Wen ◽  
Rui Sun ◽  
...  
Keyword(s):  
Social Media ◽  
Data Management ◽  
Disaster Management ◽  
Research Issues ◽  
Social Media Data ◽  
Advantages And Disadvantages ◽  
Research Problems ◽  
Use Of Social Media ◽  
Temporal Information Extraction ◽  
Media Data

Social media has played a significant role in disaster management, as it enables the general public to contribute to the monitoring of disasters by reporting incidents related to disaster events. However, the vast volume and wide variety of generated social media data create an obstacle in disaster management by limiting the availability of actionable information from social media. Several approaches have therefore been proposed in the literature to cope with the challenges of social media data for disaster management. To the best of our knowledge, there is no published literature on social media data management and analysis that identifies the research problems and provides a research taxonomy for the classification of the common research issues. In this paper, we provide a survey of how social media data contribute to disaster management and the methodologies for social media data management and analysis in disaster management. This survey includes the methodologies for social media data classification and event detection as well as spatial and temporal information extraction. Furthermore, a taxonomy of the research dimensions of social media data management and analysis for disaster management is also proposed, which is then applied to a survey of existing literature and to discuss the core advantages and disadvantages of the various methodologies.

Next Generation Technologies for Improving Product Planning and Development: An Industry Perspective

2013 ◽  
Author(s):  
Anurag Jain ◽  
Sathish Kumar Thirugnanam ◽  
Atul Narsingpurkar ◽  
Jitesh H. Panchal
Keyword(s):  
Data Management ◽  
Academic Research ◽  
Product Lifecycle Management ◽  
Point Of View ◽  
Process Models ◽  
Product Portfolio ◽  
Next Generation ◽  
Research Issues ◽  
Product Planning ◽  
Traditional Technologies

Successful product planning and development revolves around great innovation, effective implementation of new ideas, cross-functional collaboration, and right decision making before translating ideas into a right product portfolio, features and technology roadmaps, and finally launching them as successful products. Managing the product planning processes offers multiple challenges in the absence of a healthy idea pipe line, a good visibility into market and competition dynamics, lack of cross functional collaboration and finally, absence of an integrated process and system to support the complex information interplay. Organizations have, in past, adopted different process models and technologies ranging from product data management (PDM), product lifecycle management (PLM), knowledge management and collaboration solutions to address above challenges. However, there is a significant opportunity to leverage next generation technologies such as digital social networking (DSN), cloud computing, and big data management in conjunction with the traditional technologies to improve the efficiency and effectiveness of product planning and development. This paper presents an industry perspective on the major potential areas where these next generation technologies can be leveraged in the early stages of design, particularly product planning. Specific examples from automotive design and manufacturing are used to illustrate the complementary nature of traditional technologies and the emerging web-based technologies. The paper discusses major industry trends and reviews academic research in this area, and concludes with the authors’ point of view on how the combination of these technologies can be leveraged for developing a profitable product portfolio. The paper also highlights specific research issues from technological and business process standpoint that need to be addressed for successful integration. The potential benefits of such integration include productivity improvements, improved product offerings, first time right & on time product launches.

Scanning tunneling microscopy of polymers: A status report

1989 ◽  
Vol 47 ◽  
pp. 330-331
Author(s):  
P.E. Russell ◽  
I.H. Musselman
Keyword(s):  
High Resolution ◽  
Scanning Tunneling Microscopy ◽  
Sample Surface ◽  
Atomic Scale ◽  
Constant Current ◽  
Scanning Tunneling ◽  
Status Report ◽  
Tunneling Microscopy ◽  
Research Issues ◽  
Wide Range

Scanning tunneling microscopy (STM) has evolved rapidly in the past few years. Major developments have occurred in instrumentation, theory, and in a wide range of applications. In this paper, an overview of the application of STM and related techniques to polymers will be given, followed by a discussion of current research issues and prospects for future developments. The application of STM to polymers can be conveniently divided into the following subject areas: atomic scale imaging of uncoated polymer structures; topographic imaging and metrology of man-made polymer structures; and modification of polymer structures. Since many polymers are poor electrical conductors and hence unsuitable for use as a tunneling electrode, the related atomic force microscopy (AFM) technique which is capable of imaging both conductors and insulators has also been applied to polymers.The STM is well known for its high resolution capabilities in the x, y and z axes (Å in x andy and sub-Å in z). In addition to high resolution capabilities, the STM technique provides true three dimensional information in the constant current mode. In this mode, the STM tip is held at a fixed tunneling current (and a fixed bias voltage) and hence a fixed height above the sample surface while scanning across the sample surface.

Research Issues in the Transition to Free Flight

2000 ◽  
Vol 24 (1) ◽  
pp. 21-29 ◽  
Author(s):  
S Kahne
Keyword(s):  
Free Flight ◽  
Research Issues
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