Data Management Optimization Research Articles

Data infrastructure for multitemporal airborne LiDAR point cloud analysis – Examples from physical geography in high mountain environments

The application of multi-temporal topographic LiDAR data has become a standard for many mapping and monitoring applications in man-made and natural environments. With increasing availability of area-wide, high-resolution, multi-temporal datasets and the increasing interest in working with the original measured 3D topographic LiDAR point clouds, challenges regarding optimal data storage and management are gaining in importance. During the last decade, an unique LiDAR dataset, consisting of over 30 flight campaigns covering different areas in western Austria and northern Italy, has been acquired with the purpose to analyse surface changes in high mountain environments. The datasets from each flight campaign are stored and managed in a LiDAR specific information system (LIS, Laserdata Information System), which has a client–server architecture and a spatial relational database as a core. The system is integrated into an open source Geographical Information System, which allows a seamless integration into operational spatial data processing and analysis workflows. It enables multi-user access to 3D point cloud data and additional attributes, such as intensity, return number, global positioning system time, flight path trajectory information and fullwaveform attributes if available. In this paper we describe the available dataset, the approach to 3D point cloud storage and management and the structure of the database. The value of direct access to the stored 3D point cloud data is assessed as well as the importance of storing point cloud attributes. A further focus lies on the importance of the data management and infrastructure for the analysis of large areas and long time series of topographic LiDAR data.

The “BIM-sustain” experiment – simulation of BIM-supported multi-disciplinary design

Abstract Background The AEC practice using BIM technology in Central European (CE) context is still very young; the previous experiences demonstrated a number of upcoming problems with BIM implementation on technical- (heterogonous data, interfaces, large data volumes) but even more so on process-level (question of responsibilities and work-load distribution, lacking standards or conventions on building-representation and in general lack of experience and knowledge on integrated practice). The optimal data management, transfer and synchronization within inhomogeneous software context, as is often the case within inter-firm construction projects, require enormous organization, coordination and communication effort in the earliest design-phases. The BIM implementation implies therefore necessity of fundamental rethinking of the conventional design process, which in CE context is still predominantly based on sequential, segmented practice. Methods At the Vienna University of Technology a BIM-supported multi-disciplinary planning process with students of architecture, structural engineering and building physics, using several BIM-software tools was simulated. From the qualitative and quantitative evaluation of this BIM-supported multi-disciplinary collaboration will enable the compilation of guidelines for efficient use of BIM in design and planning process for the planners and standardization bodies. Results First insights on process-quality, such as team-, process- and technology satisfaction, as well as conflict- and stress levels will be presented in this paper. We were able to identify numerous technical problems related to the data transfer and inconsistencies in translation, which resulted in participant dissatisfaction and significant increasing of work-loads. Conclusion The first results imply at the importance of process-organization techniques such as face-to face communication, coordination and work-load allocation between the team-members in order to conduct the efficient BIM-supported process; as well as at urgent need for advancement of the tools in terms of data transfer and exchange. In the next step, using mandatory protocols and timesheets, a detailed statistical analysis of the people-process-technology issues will be conducted, as well as comparison of „Open-Platform-BIM“ to „One-Platform-BIM” model.

Note: Quasi-real-time analysis of dynamic near field scattering data using a graphics processing unit

We present an implementation of the analysis of dynamic near field scattering (NFS) data using a graphics processing unit. We introduce an optimized data management scheme thereby limiting the number of operations required. Overall, we reduce the processing time from hours to minutes, for typical experimental conditions. Previously the limiting step in such experiments, the processing time is now comparable to the data acquisition time. Our approach is applicable to various dynamic NFS methods, including shadowgraph, Schlieren and differential dynamic microscopy.

Ligand-Binding Assays in the 21st Century Laboratory: Recommendations for an Automated Data Interchange Process

With the ever increasing speed with which data are generated and the continual implementation of new instrumentation, maximizing the efficiency of data management for ligand-binding assays (LBAs) remains an increasing challenge. At the American Association of Pharmaceutical Scientists Workshop on the 21st Century Bioanalytical Laboratory: Maximizing Quality and Efficiency through Innovation, the attendees recognized the need to address the issue of data management. The eSolutions team, made up of end users and vendors, was formed with this challenge in mind, under the 21st Century Laboratory initiative. The eSolutions team has identified the need for a fully automated data interchange process as the first step to optimizing data management. This will require at least two major advances. First, for instruments capable of capturing raw data and metadata, a common open-source data standard is critical. Software independent of instruments will need to be compatible with the common data standard. Secondly, vendors must ensure that instruments and data analysis systems that process LBA data are enabled for direct bidirectional, file-less transfer of data between laboratory information management systems (LIMS), and instrument systems. In many laboratories conducting assays, LBA data systems and laboratory instruments are often islands of information, separated by an ocean of non-communication. Multiple applications within the laboratories generate reams of data that are stored in separate, non-connected silos of files. Data translation is required to share the data stored within these files with a LIMS or other analytical software. At best, this can be resolved using information technology (IT) resources. However, in the worst case scenario, this translation is performed manually leading to tedious error-prone tasks that require additional quality control (QC) oversight. In order to meet US FDA 21 CFR Part 11 (Electronic Records Electronic Signatures, ERES) regulations, data transfer through a file-based process requires assurance that the data imported into the LIMS are the same data exported from the data acquisition instrument. Therefore, one way to increase laboratory productivity would be through the use of a file-less automated process for data interchange tasks. Automation offers the performance of tasks in a secure, repeatable, and consistent manner without human intervention. Additional benefits of implementing an automated data interchange include: Facilitation of results and metadata transfer from source laboratory instruments (e.g., plate reader) to a data processing system (e.g., a LIMS) The ability to automate laboratory business processes where the format-consistent data can be programmed to be parsed and read by computer software Consistency of data formats between versions of the same software Data comparability between software applications even from different vendors avoiding the business risk of having to maintain legacy systems in order to retain the ability to read stored proprietary raw data in the future While many LBA laboratories clearly see a need for an automated data interchange process, these laboratories must raise awareness of this requirement by supporting the eSolutions team in establishing this process as well as supporting those vendors who choose to participate in the effort. It is absolutely necessary to have active vendor participation to be successful. There is a compelling reason for instrument and software vendors to participate in the creation of an automated data interchange process and to support its adoption. Innovative vendors of LIMS and analytical software will benefit from not having to keep up with the ever changing landscape of data formats. The automated data interchange process also allow new instrument vendors to more easily comply with data management requirements of LBA laboratories, thereby increasing the likelihood that innovative technologies will be adopted. On the other hand, LBA laboratories should be willing to accept an increase in cost for applications to account for costs incurred during adoption of the process and to patronize vendors that adopt the automated data interchange process. In this article, we provide perspectives on the benefit to the LBA community (vendors and users) and what is required to establish an automated data interchange process for LBA data.

Inequality in the utility of customer data: Implications for data management and usage

Customer data has long been recognized as a critical resource for supporting marketing efforts. With the rapidly increasing investments in the acquisition and the administration of customer data, the concern about cost-effective management of this important resource is growing. In this study, we explore the concept of inequality in the utility of data – the extent to which records in large data sets differ in their business-value contribution. The Lorenz curve and the associated Gini index, powerful tools for analyzing inequality, have been applied to a variety of social and economic disciplines. We adapt these tools for modeling and measuring inequality in the context of managing large customer data sets, and use them for analyzing utility/cost trade-offs and optimizing data management decisions. We demonstrate the application of these tools in the customer relationship management context of managing alumni relations, using large data samples from a real-world system. The results support our argument that understanding and measuring inequality in the utility of data may have important implications for better usage and administration of customer data.

Publishing Geospatial Data through Geospatial Web Service and XML Database System

Technically the spatial non-interoperability problem associated with current geospatial processing systems can be categorized as data and access non-interoperability. In GIS community, Open GIS Consortium (OGC) geospatial Web services have been introduced to overcome spatial noninteroperability problem associated with most geospatial processing systems. At the same time, in Information Technology (IT) world, the best solution for providing interoperability among heterogeneous systems is Web services technologies. Geospatial Web services and Web services technologies differ in the way that latter are composed of particular set of technologies and protocols but the former are comprised of defined set of interface implementation specifications which can be implemented with diverse technologies. This research describes and discusses that geospatial Web services which are developed using Web services technologies can provide access interoperability among various geospatial and non-geospatial processing systems. In addition to access interoperability, making use of open and platform independent data standards like Geography Markup Language (GML), data interoperability can be achieved. Meanwhile, proper management of geospatial data necessitates use of efficient and optimized data management systems. In this respect, the study also illustrates the practical evaluation of existing solution for storing and publishing geospatial data as GML. Based on the practical evaluation of this research, coupling native-XML database systems with Web services technologies proved to be an open, interoperable and efficient solution for developing geospatial Web services.

Economics-Driven Data Management: An Application to the Design of Tabular Data Sets

Organizational data repositories are recognized as critical resources for supporting a large variety of decision tasks and for enhancing business capabilities. As investments in data resources increase, there is also a growing concern about the economic aspects of data resources. While the technical aspects of data management are well examined, the contribution of data management to economic performance is not. Current design and implementation methodologies for data management are driven primarily by technical and functional requirements, without considering the relevant economic factors sufficiently. To address this gap, this study proposes a framework for optimizing data management design and maintenance decisions. The framework assumes that certain design characteristics of data repositories and data manufacturing processes significantly affect the utility of the data resources and the costs associated with implementing them. Modeling these effects helps identify design alternatives that maximize net-benefit, defined as the difference between utility and cost. The framework for the economic assessment of design alternatives is demonstrated for the optimal design of a large data set

A system integration framework for coupled multiphysics simulations

Multiphysics simulations are playing an increasingly important role in computational science and engineering for applications ranging from aircraft design to medical treatments. These simulations require integration of techniques and tools from multiple disciplines, and in turn demand new advanced technologies to integrate independently developed physics solvers effectively. In this paper, we describe some numerical, geometrical, and system software components required by such integration, with a concrete case study of detailed, three-dimensional, parallel rocket simulations involving system-level interactions among fluid, solid, and combustion, as well as subsystem-level interactions. We package these components into a software framework that provides common-refinement based methods for transferring data between potentially non-matching meshes, novel and robust face-offsetting methods for tracking Lagrangian surface meshes, as well as integrated support for parallel mesh optimization, remeshing, algebraic manipulations, performance monitoring, and high-level data management and I/O. From these general, reusable framework components we construct domain-specific building blocks to facilitate integration of parallel, multiphysics simulations from high-level specifications that are easy to read and can also be visualized graphically. These reusable building blocks are integrated with independently developed physics codes to perform various multiphysics simulations.

Medical Informatics in Medical Research

Computers are widely used for data management in clinical trials in the developed countries, unlike in developing countries. Dependable systems are vital for data management, and medical decision making in clinical research. Monitoring and evaluation of data management is critical. In this paper we describe database structures and procedures of systems used to implement, coordinate, and sustain data management in Africa. We outline major lessons, challenges and successes achieved, and recommendations to improve medical informatics application in biomedical research in sub-Saharan Africa. A consortium of experienced research units at five sites in Africa in studying children with disease formed a new clinical trials network, Severe Malaria in African Children. In December 2000, the network introduced an observational study involving these hospital-based sites. After prototyping, relational database management systems were implemented for data entry and verification, data submission and quality assurance monitoring. Between 2000 and 2005, 25,858 patients were enrolled. Failure to meet data submission deadline and data entry errors correlated positively (correlation coefficient, r = 0.82), with more errors occurring when data was submitted late. Data submission lateness correlated inversely with hospital admissions (r = -0.62). Developing and sustaining dependable DBMS, ongoing modifications to optimize data management is crucial for clinical studies. Monitoring and communication systems are vital in multi-center networks for good data management. Data timeliness is associated with data quality and hospital admissions.

Iterative solution of systems of linear equations arising in the context of stochastic finite elements

The particular properties of systems of linear equations arising in the context of the Stochastic Finite Element Method (SFEM) motivate the customization of existing iterative solution algorithms. The implementation described in this paper has aimed at optimizing data management, MAT-VEC operations and preconditioning strategies. It turns out that SFEM-systems can be solved with much less effort than their size suggests. The main idea is based on the fact that the full system matrix consists of few, relatively small submatrices with identical dimensions and sparsity pattern. This makes it very efficient to perform matrix–vector multiplications at the submatrix level and to avoid the assembly of the full coefficient matrix.

Safety and Management of Complex Processes: Supervision, Control, Optimization and Intelligent Process Data Management

The aim of this paper is to present a new global vision of plant data management in large scale processes for plant maximum efficiency with respect to plant safety and environmental regulations. In this perspective, one highlights the vulnerability of a plant to inaccurate data, and poor performance control systems based on cheap solutions compared to the reliability of new techniques based on artificial intelligence methods and their important role of handling plant knowledge extraction, information organization and coordination among diffirent plant's units and control systems to avoid dramatic situations.

Compliance to compulsory vaccination: strategies and results.

This report is devoted to analyze the effect that compulsory vaccination has on the compliance of the population, compared with the results obtained by massive campaigns for optional vaccinations. The implementation of a specific software for the management of individual schedules helps to reach a substantial complete coverage of the individuals for the first ones, while improving but incomplete results regard the vaccines against pertussis and measles-mumps-rubella, optional in Italy. The optimization of data management at the local health unit level improves the quality and the satisfaction of the work performed by the personnel, but has a limited effect on the already nearly complete coverage for the compulsory immunizations. The mounting percentage of children immunized with optional vaccines can be explained both by the massive campaigns of information conducted in recent years and by the better tracking of individual immunization schedules.