Justification of Data Warehousing Projects

Project justification is regarded as one of the major methodological deficits in Data Warehousing practice. As reasons for applying inappropriate methods, performing incomplete evaluations, or even entirely omitting justifications, the special nature of Data Warehousing benefits and the large portion of infrastructure-related activities are stated. In this paper, the economic justification of Data Warehousing projects is analyzed, and first results from a large academiaindustry collaboration project in the field of non-technical issues of Data Warehousing are presented. As conceptual foundations, the role of the Data Warehouse system in corporate application architectures is analyzed, and the specific properties of Data Warehousing projects are discussed. Based on an applicability analysis of traditional approaches to economic IT project justification, basic steps and responsibilities for the justification of Data Warehousing projects are derived.

Internet based multicenter study for thoracolumbar injuries: a new concept and preliminary results

This article reports about the internet based, second multicenter study (MCS II) of the spine study group (AG WS) of the German trauma association (DGU). It represents a continuation of the first study conducted between the years 1994 and 1996 (MCS I). For the purpose of one common, centralised data capture methodology, a newly developed internet-based data collection system ( http://www.memdoc.org ) of the Institute for Evaluative Research in Orthopaedic Surgery of the University of Bern was used. The aim of this first publication on the MCS II was to describe in detail the new method of data collection and the structure of the developed data base system, via internet. The goal of the study was the assessment of the current state of treatment for fresh traumatic injuries of the thoracolumbar spine in the German speaking part of Europe. For that reason, we intended to collect large number of cases and representative, valid information about the radiographic, clinical and subjective treatment outcomes. Thanks to the new study design of MCS II, not only the common surgical treatment concepts, but also the new and constantly broadening spectrum of spine surgery, i.e. vertebro-/kyphoplasty, computer assisted surgery and navigation, minimal-invasive, and endoscopic techniques, documented and evaluated. We present a first statistical overview and preliminary analysis of 18 centers from Germany and Austria that participated in MCS II. A real time data capture at source was made possible by the constant availability of the data collection system via internet access. Following the principle of an application service provider, software, questionnaires and validation routines are located on a central server, which is accessed from the periphery (hospitals) by means of standard Internet browsers. By that, costly and time consuming software installation and maintenance of local data repositories are avoided and, more importantly, cumbersome migration of data into one integrated database becomes obsolete. Finally, this set-up also replaces traditional systems wherein paper questionnaires were mailed to the central study office and entered by hand whereby incomplete or incorrect forms always represent a resource consuming problem and source of error. With the new study concept and the expanded inclusion criteria of MCS II 1, 251 case histories with admission and surgical data were collected. This remarkable number of interventions documented during 24 months represents an increase of 183% compared to the previously conducted MCS I. The concept and technical feasibility of the MEMdoc data collection system was proven, as the participants of the MCS II succeeded in collecting data ever published on the largest series of patients with spinal injuries treated within a 2 year period.

The application of medical informatics to the veterinary management programs at companion animal practices in Alberta, Canada: a case study.

Companion animals closely share their domestic environment with people and have the potential to, act as sources of zoonotic diseases. They also have the potential to be sentinels of infectious and noninfectious, diseases. With the exception of rabies, there has been minimal ongoing surveillance of, companion animals in Canada. We developed customized data extraction software, the University of, Calgary Data Extraction Program (UCDEP), to automatically extract and warehouse the electronic, medical records (EMR) from participating private veterinary practices to make them available for, disease surveillance and knowledge creation for evidence-based practice. It was not possible to build, generic data extraction software; the UCDEP required customization to meet the specific software, capabilities of the veterinary practices. The UCDEP, tailored to the participating veterinary practices', management software, was capable of extracting data from the EMR with greater than 99%, completeness and accuracy. The experiences of the people developing and using the UCDEP and the, quality of the extracted data were evaluated. The electronic medical record data stored in the data, warehouse may be a valuable resource for surveillance and evidence-based medical research.

Mining free-text medical records for companion animal enteric syndrome surveillance.

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

Compact low-power cortical recording architecture for compressive multichannel data acquisition

This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.

TARWIS - A Testbed Management Architecture for Wireless Sensor Network Testbeds

With research on Wireless Sensor Networks (WSNs) becoming more and more mature in the past five years, researchers from universities all over the world have set up testbeds of wireless sensor networks, in most cases to test and evaluate the real-world behavior of developed WSN protocol mechanisms. Although these testbeds differ heavily in the employed sensor node types and the general architectural set up, they all have similar requirements with respect to management and scheduling functionalities: as every shared resource, a testbed requires a notion of users, resource reservation features, support for reprogramming and reconfiguration of the nodes, provisions to debug and remotely reset sensor nodes in case of node failures, as well as a solution for collecting and storing experimental data. The TARWIS management architecture presented in this paper targets at providing these functionalities independent from node type and node operating system. TARWIS has been designed as a re-usable management solution for research and/or educational oriented research testbeds of wireless sensor networks, relieving researchers intending to deploy a testbed from the burden to implement their own scheduling and testbed management solutions from scratch.

Opportunistic Content-Centric Data Transmission During Short Network Contacts

In this paper, we investigate content-centric data transmission in the context of short opportunistic contacts and base our work on an existing content-centric networking architecture. In case of short interconnection times, file transfers may not be completed and the received information is discarded. Caches in content-centric networks are used for short-term storage and do not guarantee persistence. We implemented a mechanism to extend caching on persistent storage enabling the completion of disrupted content transfers. The mechanisms have been implemented in the CCNx framework and have been evaluated on wireless mesh nodes. Our evaluations using multicast and unicast communication show that the implementation can support content transfers in opportunistic environments without significant processing and storing overhead.

Lake Floor Morphology and Sediment Architecture of Lake Torneträsk, Northern Sweden

ABSTRACT. Here we present datasets from a hydroacoustic survey in July 2011 at Lake Torneträsk, northern Sweden. Our hydroacoustic data exhibit lake floor morphologies formed by glacial erosion and accumulation processes, insights into lacustrine sediment accumulation since the beginning of deglaciation, and information on seismic activity along the Pärvie Fault. Features of glacial scouring with a high-energy relief, steep slopes, and relative reliefs of more than 50 m are observed in the large W-basin. The remainder of the lacustrine subsurface appears to host a broad variety of well preserved formations from glacial accumulation related to the last retreat of the Fennoscandian ice sheet. Deposition of glaciolacustrine and lacustrine sediments is focused in areas situated in proximity to major inlets. Sediment accumulation in distal areas of the lake seldom exceeds 2 m or is not observable. We assume that lack of sediment deposition in the lake is a result of different factors, including low rates of erosion in the catchment, a previously high lake level leading to deposition of sediments in higher elevated paleodeltas, tributaries carrying low suspension loads as a result of sedimentation in upstream lakes, and an overall low productivity in the lake. A clear off-shore trace of the Pärvie Fault could not be detected from our hydroacoustic data. However, an absence of sediment disturbance in close proximity to the presumed fault trace implies minimal seismic activity since deposition of the glaciolacustrine and lacustrine sediments.

Mobility and bandwidth prediction in virtualized LTE systems: Architecture and challenges

Long Term Evolution (LTE) represents the fourth generation (4G) technology which is capable of providing high data rates as well as support of high speed mobility. The EU FP7 Mobile Cloud Networking (MCN) project integrates the use of cloud computing concepts in LTE mobile networks in order to increase LTE's performance. In this way a shared distributed virtualized LTE mobile network is built that can optimize the utilization of virtualized computing, storage and network resources and minimize communication delays. Two important features that can be used in such a virtualized system to improve its performance are the user mobility and bandwidth prediction. This paper introduces the architecture and challenges that are associated with user mobility and bandwidth prediction approaches in virtualized LTE systems.

RC-NDN: Raptor Codes Enabled Named Data Networking

Information-centric networking (ICN) has been proposed to cope with the drawbacks of the Internet Protocol, namely scalability and security. The majority of research efforts in ICN have focused on routing and caching in wired networks, while little attention has been paid to optimizing the communication and caching efficiency in wireless networks. In this work, we study the application of Raptor codes to Named Data Networking (NDN), which is a popular ICN architecture, in order to minimize the number of transmitted messages and accelerate content retrieval times. We propose RC-NDN, which is a NDN compatible Raptor codes architecture. In contrast to other coding-based NDN solutions that employ network codes, RC-NDN considers security architectures inherent to NDN. Moreover, different from existing network coding based solutions for NDN, RC-NDN does not require significant computational resources, which renders it appropriate for low cost networks. We evaluate RC-NDN in mobile scenarios with high mobility. Evaluations show that RC-NDN outperforms the original NDN significantly. RC-NDN is particularly efficient in dense environments, where retrieval times can be reduced by 83% and the number of Data transmissions by 84.5% compared to NDN.

Content-Aware Delivery of Scalable Video in Network Coding Enabled Named Data Networks

In this work, we propose a novel network coding enabled NDN architecture for the delivery of scalable video. Our scheme utilizes network coding in order to address the problem that arises in the original NDN protocol, where optimal use of the bandwidth and caching resources necessitates the coordination of the forwarding decisions. To optimize the performance of the proposed network coding based NDN protocol and render it appropriate for transmission of scalable video, we devise a novel rate allocation algorithm that decides on the optimal rates of Interest messages sent by clients and intermediate nodes. This algorithm guarantees that the achieved flow of Data objects will maximize the average quality of the video delivered to the client population. To support the handling of Interest messages and Data objects when intermediate nodes perform network coding, we modify the standard NDN protocol and introduce the use of Bloom filters, which store efficiently additional information about the Interest messages and Data objects. The proposed architecture is evaluated for transmission of scalable video over PlanetLab topologies. The evaluation shows that the proposed scheme performs very close to the optimal performance