Data management

About: Data management is a research topic. Over the lifetime, 31574 publications have been published within this topic receiving 424326 citations.

Land information system: An interoperable framework for high resolution land surface modeling

Abstract: Knowledge of land surface water, energy, and carbon conditions are of critical importance due to their impact on many real world applications such as agricultural production, water resource management, and flood, weather, and climate prediction. Land Information System (LIS) is a software framework that integrates the use of satellite and ground-based observational data along with advanced land surface models and computing tools to accurately characterize land surface states and fluxes. LIS employs the use of scalable, high performance computing and data management technologies to deal with the computational challenges of high resolution land surface modeling. To make the LIS products transparently available to the end users, LIS includes a number of highly interactive visualization components as well. The LIS components are designed using object-oriented principles, with flexible, adaptable interfaces and modular structures for rapid prototyping and development. In addition, the interoperable features in LIS enable the definition, intercomparison, and validation of land surface modeling standards and the reuse of a high quality land surface modeling and computing system.

System and method for managing patient medical records

Abstract: A system and method for managing patient medical information to facilitate data management and improve physician access to and recordal of examination data is described. The method comprises a computer aided process including the steps of scheduling appointments, entering and displaying data to a physician, updating the patient data with progress notes concurrently with an examination, displaying allergy warnings and recording a diagnosis based on the progress notes. A common graphic user interface is also disclosed to facilitate operation of the preferred system and method. The system and method are implemented with a relational database operating on data tables which store information input into the user interface.

File server having snapshot application data groups

Abstract: This file server system appears to the host computer to be a plurality of data storage devices which are directly addressable by the host computer using the native data management and access structures of the host computer. The file server however is an intelligent data storage subsystem that defines, manages and accesses synchronized sets of data and maintains these synchronized sets of data external from the host computer system's data management facilities in a manner that is completely transparent to the host computer. This is accomplished by the use of the snapshot application data group that extends the traditional sequential data set processing concept of generation data groups.

Big data and cloud computing: current state and future opportunities

Abstract: Scalable database management systems (DBMS)---both for update intensive application workloads as well as decision support systems for descriptive and deep analytics---are a critical part of the cloud infrastructure and play an important role in ensuring the smooth transition of applications from the traditional enterprise infrastructures to next generation cloud infrastructures. Though scalable data management has been a vision for more than three decades and much research has focussed on large scale data management in traditional enterprise setting, cloud computing brings its own set of novel challenges that must be addressed to ensure the success of data management solutions in the cloud environment. This tutorial presents an organized picture of the challenges faced by application developers and DBMS designers in developing and deploying internet scale applications. Our background study encompasses both classes of systems: (i) for supporting update heavy applications, and (ii) for ad-hoc analytics and decision support. We then focus on providing an in-depth analysis of systems for supporting update intensive web-applications and provide a survey of the state-of-the-art in this domain. We crystallize the design choices made by some successful systems large scale database management systems, analyze the application demands and access patterns, and enumerate the desiderata for a cloud-bound DBMS.

Trio: A System for Integrated Management of Data, Accuracy, and Lineage

Abstract: Trio is a new database system that manages not only data, but also the accuracy and lineage of the data. Approximate (uncertain, probabilistic, incomplete, fuzzy, and imprecise!) databases have been proposed in the past, and the lineage problem also has been studied. The goals of the Trio project are to distill previous work into a simple and usable model, design a query language as an understandable extension to SQL, and most importantly build a working system---a system that augments conventional data management with both accuracy and lineage as an integral part of the data. This paper provides numerous motivating applications for Trio and lays out preliminary plans for the data model, query language, and prototype system.