Data warehouse design for mobile environment

Analysis and design are very important roles in Data Warehouse (DW) system development and forms as a backbone of any successful or failure of the DWproject. The emergence trends of ubiquitous-based application required DW system to be implemented in the mobile environment.However, current analysis and design approaches are based on existing DW environments that focusing on the deployment of DW system in static client-based applications. This will create the limitations on user accessed and reduced the used of analytical information by the decision makers.Consequently, this will prolong the adoption of business intelligence (BI) applications to the users and organisations. This research is to suggest an approach for designing the DW and implement the DW system on the mobile environments.A variant dimension modeling technique will be used to enhance the DW modeling in order to accommodate the requirements of mobile characteristics in the DW design

Data warehouse model for mobile-based applications

Analysis and design are very important roles in the Data Warehouse (DW) system development and forms as a backbone of any successful or failure of the DW project.The emerging trends of analytic-based application required the DW system to be implemented in the mobile environment. However, current analysis and design approaches are based on existing DW environments that focusing on the deployment of the DW system in traditional web-based applications.This will create the limitations on user accessed and the used of analytical information by the decision makers. Consequently, this will prolong the adoption of analytic-based applications to the users and organizations.This research aims to suggest an approach for modeling the DW and design the DW system on the mobile environments. A variant dimension of modeling techniques was used to enhance the DW schemas in order to accommodate the requirements of mobile characteristics in the DW design.A proposed mobile DW system was evaluated by expert review, and support the success of mobile DW-based application implementation

Trajectory Data Analysis in Support of Understanding Movement Patterns: A Data Mining Approach

Recent developments in wireless technology, mobility and networking infrastructures increased the amounts of data being captured every second. Data captured from the digital traces of moving objects and devices is called trajectory data. With the increasing volume of spatiotemporal trajectories, constructive and meaningful knowledge needs to be extracted. In this paper, a conceptual framework is proposed to apply data mining techniques on trajectories and semantically enrich the extracted patterns. A design science research approach is followed, where the framework is tested and evaluated using a prototypical instantiation, built to support decisions in the context of the Egyptian tourism industry. By applying association rule mining, the revealed time-stamped frequently visited regions of interest (ROI) patterns show that specific semantic annotations are required at early stages in the process and on lower levels of detail, refuting the presumption of cross-application usable patterns

Repairer\u27s recipe : volume 0

Why? Technology is accelerating; so is the amount of e-waste. Proliferating new purchases is a shortcut to economic gain, yet proliferation sacrifices social and ecological well being. Activating repair benefits systems— by decelerating the waste stream, and serving as a regenerative module for ethical material collection. Repair literacy encourages an individual’s engagement with materials while challenging corporations to acknowledge repair in the design process. Therefore, electronics users should have the opportunity to learn about repair before the need arises. A sustainable product ecosystem asks for the collaborative effort of public and private sectors and most importantly, the repair practices of individuals can lead this trajectory. How? Repairer\u27s Recipe is a repository that gathers research and proposals of the dynamic capabilities of repair and its role in the product ecosystem. You will find Aether, a Chrome plugin that assists consumers to factor in repair considerations during purchase. You will also find Learn Tech the Food Way, a visual series that brings much needed visibility to repair practices. By playfully analogizing the sophistication of a mobile phone structure to food preparation, thereby encouraging all electronics users to become repairers themselves. This book presents my research, interviews, testing, design, and proposals, in the forms of images, writings, diagrams, websites, and videos. You will follow me on the journey that investigates how products become waste through the lens of policies and business practices, with the continuous reintroduction of why repair should be an essential practice. This document is time-stamped in May 2020. If you wish to find updated information about this project, please visit repairersrecipe.com

Proposal to Strenghern Health Information System [HIS]

\ud The HMIS Program described in this document aims at improving and strengthening the current Health Management Information System (HMIS) in Tanzania, known as MTUHA. The consortium behind the HMIS Program is headed by the Ministry of Health & Social Welfare (MOHSW) and consists of the following additional partners; Ifakara Health Research and Development Centre, University of Dar es Salaam and the University of Oslo, representing national and international capacity in HMIS. The HMIS Program is linked to the Payment for performance (P4P) funding scheme which is initiated by the Norway Tanzania Partnership Initiative. The P4P has a focus on maternal and child health and relies upon quality indicators on performance in these areas from health facilities and districts. The provision of quality data and indicators on MDG 4 & 5 is therefore a key target for the HMIS Program. The chosen approach is, however, to derive these data from the HMIS and not to establish a separate data collection structure, hence the HMIS Program. Quality information by way of essential indicators, such as for monitoring the Millennium Development Goals 4 & 5, are crucial for health services delivery and program management as well as for M&E. Currently, however, the HMIS is not providing such needed data of sufficient completeness, timeliness and quality, leading health programs and funding agencies to establish their own structures for data collection, and thus creating fragmentation and adding to the problem. The HMIS Program aims at changing this negative trend and turning the HMIS into the key source of shared essential quality information in Tanzania by; focusing on action oriented use of information for management at each level of the health services and by providing timely quality information to all stakeholders, including all health programs and funding agencies in the HMIS strengthening process – making it an all-inclusive national process, focusing on capacity development; on-site support and facilitation, short courses and continuous education, building capacity in the MOHSW and establishing a national network of HMIS support, and by building on experience, methods and tools from Africa’s “best practices” HMIS, such as South Africa – and Zanzibar Within this proposal the aim is to carry out the HMIS strengthening process in 1/3 of the districts in the country, 7 regions, during the first 3 years. The objective, however, is to cover the entire country during the 5 years duration of the NTPI. By aiming at quick and tangible results, the expectation is that other funding agencies will join forces and thereby ensuring national coverage.\ud \u

Environmental Disasters Data Management Workshop Report

The Environmental Disasters Data Management (EDDM) project seeks to foster communication between collectors, managers, and users of data within the scientific research community, industry, NGOs, and government agencies, with a goal to identify and establish best practices for orderly collection, storage, and retrieval. The Coastal Response Research Center (CRRC) is assisting NOAA’s Office of Response and Restoration (ORR) with this effort. The objectives of the EDDM project are to: Engage the community of data users, data managers, and data collectors to foster a culture of applying consistent terms and concepts, data flow, and quality assurance and control; Provide oversight in the establishment and integration of foundational, baseline data collected prior to an environmental event, based on user requirements; Provide best‐practice guidance for data and metadata management; Suggest infrastructure design elements to facilitate quick and efficient search, discovery, and retrieval of data; Define the characteristics of a “gold standard” data management plan for appropriate data sampling, formatting, reliability, and retrievability; and Deliver workshop conclusions to end users in order to promote the use of the protocols, practices, or recommendations identified by participants

From the conception to the definition of a new service: the case of the European GeoPKDD project”

La tesi affronta il processo che parte dalla generazione di un nuovo servizio di tipo technology push ed arriva fino alla sua definizione, attraverso l’analisi del lavoro svolto per WIND Telecomunicazioni s.p.a. nell’ambito del progetto Europeo GeoPKDD. Dopo un inquadramento teorico sulle metodologie di sviluppo di nuovi servizi e sulle peculiarità di uno sviluppo technology push rispetto al caso market pull, il lavoro si concentra sul processo che, partendo dalla generazione di nuove idee basate sulla tecnologia GeoPKDD, si è concluso con la definizione delle specifiche finali da implementare nel servizio finale

The National Transport Data Framework

Report by Professor Peter Landshoff (Cambridge University) and Professor John Polak (Imperial College London) on a project for the Department for Transport. emails: [email protected] [email protected] NTDF is designed to be a resource for data owners to deposit descriptions into a central catalogue, so that people can search for data and find data and understand their characteristics. The value of this is to individuals, to commercial organizations, and to public bodies. For example, services that provide better information to travellers will help to make their journey less stressful and persuade them to make more use of public transport. Transport operators need very diverse information to help them plan developments to their services: demographic, geographical, economic etc. And policy makers need a similar range of information to help them decide how to divide their budget and afterwards to evaluate how valuable it has been.This work was supported by the Department for Transport (DfT)