Search

There are numerous ways to monitor business activities, but the most effective way is by adopting data-driven decision-making processes and technologies to enable the corporate entities to monitor and measure performance KPIs. Dashboards are commonly used as the main supporting tool for presenting analytical results. However, current approaches have some limitations. Since data sources are usually transformed and materialized during the design phase, end users of typical dashboards can only perform simple filtering and layout changes in most cases. In this work, we introduce a flexible qualitative data analytics dashboard framework called Cookbook. The main novelty of our approach is that we achieve a highly customizable dashboard framework by segregating data during design phase, and materializing data during execution phase.

A successful smart nation is one which uses information and Internet of Things (IoT) technology in a seamless integrated form to enhance transport, healthcare and other public services to improve the quality of life for citizens. In this paper we present our practical experience with smart cities platform design: A∗DAX, a powerful framework for extracting insight from heterogeneous, real-time and complex data sets. In fact, A∗DAX has been successfully deployed at the multi-agency Jurong Lake District (“JLD”) Smart City Test Bed in Singapore, with integration to a shared sensor network of close to 1,000 urban sensors and video analytics of more than 25 video sensors. The vision for JLD is to be a leading model for developing a mixed-used urban area that is sustainable, smart and connected. Through the A∗DAX data exchange portal and repository, test bed users will be able to access real-time and historical environmental data collected by the sensors, as well as video analytics from the camera streams and benefit from a variety of Smart Nation solutions providing real-time sensing and analytics.

A∗STAR Data Analytics Exchange (”A∗DAX”) is a scalable platform built upon open architecture and it is designed to facilitate the secure management and analytics of urban data. In this paper, we introduced A∗DAX-DAT, which is the latest development of A∗DAX. A∗DAX-DAT (or DAT for short) is the analytics component of the A∗DAX Platform. DAT aims to provide advance analytics functionalities to A∗DAX in such a way that: (i) it is extensible, (ii) it is easy to use for both end-users and developers and (iii) it is efficient in handling data regardless of variety, volume and velocity. DAT consists of three components: (a) a set of framework specifications for analytics libraries, (b) dynamic analytics libraries following the aforementioned framework specifications and (c) tools to develop/use the dynamic libraries either in standalone mode or in client/server mode. This paper presents the design of DAT components with implementation details before it discusses sample use-cases of DAT. Finally, it concludes with discussions on future works on DAT.

Paul Chang emphasised in his lecture the challenges posed by the new demands and crucial roles played by educational administrators. Some of the major problems highlighted in his paper included the varying abilities of teachers, school principals and school board members. He interpreted that if educational administration is identified with distinct roles, there is scope for creative management.

We introduce the A*STAR Data Analytics and Exchange Platform (“A*DAX”), which is the backbone data platform for different programs and projects under the Urban Systems Initiative launched by the Agency for Science, Technology and Research in Singapore. The A*DAX aims to provide a centralized system for public and private sectors to manage and share data; meanwhile, it also provides basic data analytics and visualization functions for authorized parties to consume data. A*DAX is also a channel for developers to develop innovative applications based on real data to improve urban services.