Related papers: PDM based I-SOAS Data Warehouse Design
Metadata management plays a critical role in data governance, resource discovery, and decision-making in the data-driven era. While traditional metadata approaches have primarily focused on organization, classification, and resource reuse,…
Presently, large enterprises rely on database systems to manage their data and information. These databases are useful for conducting daily business transactions. However, the tight competition in the marketplace has led to the concept of…
More and more enterprises recently intend to deploy data management systems in the cloud. Due to the professionalism of software development, it has still been difficult for non-programmers to develop this kind of systems, even a small one.…
As storage systems become increasingly heterogeneous and complex, it adds burdens on DBAs, causing suboptimal performance even after a lot of human efforts have been made. In addition, existing monitoring-based storage management by access…
Research in operations management has traditionally focused on models for understanding, mostly at a strategic level, how firms should operate. Spurred by the growing availability of data and recent advances in machine learning and…
Dynamic nature of the cloud environment has made distributed resource management process a challenge for cloud service providers. The importance of maintaining the quality of service in accordance with customer expectations as well as the…
The exponential increase of availability of digital data and the necessity to process it in business and scientific fields has literally forced upon us the need to analyze and mine useful knowledge from it. Traditionally data mining has…
The Cyber-Physical System (CPS) is considered to be the next generation of intelligent industrial automation systems that integrate computing, communication and control technologies. In CPS, the interoperability requirements between devices…
Deriving reliable conclusions and insights from environmental observational data urgently requires the enrichment with consistent and comprehensive metadata, including time-resolved context such as changing deployments, configurations, and…
Business Process Management Systems (BPMS) represent a technology that automates business processes, connecting users to their tasks. There are many business processes within the port activity that can be improved through the use of more…
In this paper we describe the architecture of a Platform as a Service (PaaS) oriented to computing and data analysis. In order to clarify the choices we made, we explain the features using practical examples, applied to several known usage…
The collection of time series data increases as more monitoring and automation are being deployed. These deployments range in scale from an Internet of things (IoT) device located in a household to enormous distributed Cyber-Physical…
SDAMS is the ensemble of database + software packages aimed to the archiving, quick-look analysis, off-line analysis, network accessibility and plotting of the SPOrt produced data. Many of the aspects related to data archiving, analysis and…
Modern intelligent urban mobility applications are underpinned by large-scale, multivariate, spatiotemporal data streams. Working with this data presents unique challenges of data management, processing and presentation that is often…
For some decision processes a significant added value is achieved when enterprises' internal Data Warehouse (DW) can be integrated and combined with external data gained from web sites of competitors and other relevant Web sources. In this…
Software as a service (SaaS) has recently enjoyed much attention as it makes the use of software more convenient and cost-effective. At the same time, the arising of users' expectation for high quality service such as real-time information…
Distributed Asynchronous Object Store (DAOS) is a novel software-defined object store leveraging Non-Volatile Memory (NVM) devices, designed for high performance. It provides a number of interfaces for applications to undertake I/O, ranging…
Software organizations are increasingly incorporating machine learning (ML) into their product offerings, driving a need for new data management tools. Many of these tools facilitate the initial development of ML applications, but…
The Operational Technology Platform as a Service (OTPaaS) initiative provides a structured framework for the efficient management and storage of data. It ensures excellent response times while improving security, reliability, data and…
In modern industrial settings, advanced acquisition systems allow for the collection of data in the form of profiles, that is, as functional relationships linking responses to explanatory variables. In this context, statistical process…