Data matters

Small Data Matters

This is a review of aspects of the theory of algorithmic information that may contribute to a framework for formulating questions related to complex, highly unpredictable systems. We start by contrasting Shannon Entropy and Kolmogorov-Chaitin complexity, which epitomise correlation and causation respectively, and then move onto surveying classical results from algorithmic complexity and algorit...

Wireless Graffiti - Data, Data Everywhere Matters

In this paper, we take a retrospective look at the problem of querying and updating location dependent data in massively distributed mobile environments. Looking forward, we paint our vision of the future dataspace – physical space enhanced with embedded digital information. Finally we describe a few of the applications enabled by dataspace due to the availability of large scale ad-hoc sensor n...

Data matters in IS theory building

Winter for useful discussions and critical comments on the editorial. I am also indebted to all participants of ICIS 2007 panel on Data Rich and Poor disciplines (Avital et al. 2007), and Senior Editors of JAIS who provided early comments and criticism on the JAIS data policies.

Data matters in IS theory building

In-Memory Spatial Join: The Data Matters!

A spatial join computes all pairs of spatial objects in two data sets satisfying a distance constraint. An increasing demand in applications ranging from human brain analysis to transportation data analysis motivates studies on designing new in-memory spatial join algorithms. Among recent proposals, the following six algorithms can efficiently perform in-memory spatial joins: Size Separation Sp...