Identifying Issues for the Bright ICT Initiative: A Worldwide Delphi Study of IS Journal Editors and Scholars

Information and communication technology (ICT) continues to change business as we know it. As ICT further integrates into our daily lives, it creates more opportunities to both help and hinder fundamental social problems throughout the world. In response to these growing and urgent societal needs, the Association for Information Systems approved the Bright ICT Initiative to extend IS research beyond a focus on business to take on the broader challenges of an ICT-enabled bright society. We conducted a Delphi study to provide guidance on where bright ICT-minded researchers might focus to produce their greatest impact. In this paper, we report on our findings. The Delphi panel comprised 182 globally distributed IS journal editors who participated in a three-round consensus-building process via the Internet. Our results provide a framework of eleven research priority areas and specific research topics for those engaged in future-oriented, socially conscious IS research

Monitoring spatial sustainable development: Semi-automated analysis of satellite and aerial images for energy transition and sustainability indicators

Solar panels are installed by a large and growing number of households due to the convenience of having cheap and renewable energy to power house appliances. In contrast to other energy sources solar installations are distributed very decentralized and spread over hundred-thousands of locations. On a global level more than 25% of solar photovoltaic (PV) installations were decentralized. The effect of the quick energy transition from a carbon based economy to a green economy is though still very difficult to quantify. As a matter of fact the quick adoption of solar panels by households is difficult to track, with local registries that miss a large number of the newly built solar panels. This makes the task of assessing the impact of renewable energies an impossible task. Although models of the output of a region exist, they are often black box estimations. This project's aim is twofold: First automate the process to extract the location of solar panels from aerial or satellite images and second, produce a map of solar panels along with statistics on the number of solar panels. Further, this project takes place in a wider framework which investigates how official statistics can benefit from new digital data sources. At project completion, a method for detecting solar panels from aerial images via machine learning will be developed and the methodology initially developed for BE, DE and NL will be standardized for application to other EU countries. In practice, machine learning techniques are used to identify solar panels in satellite and aerial images for the province of Limburg (NL), Flanders (BE) and North Rhine-Westphalia (DE).Comment: This document provides the reader with an overview of the various datasets which will be used throughout the project. The collection of satellite and aerial images as well as auxiliary information such as the location of buildings and roofs which is required to train, test and validate the machine learning algorithm that is being develope

Panel on future challenges in modeling methodology

This panel paper presents the views of six researchers and practitioners of simulation modeling. Collectively we attempt to address a range of key future challenges to modeling methodology. It is hoped that the views of this paper, and the presentations made by the panelists at the 2004 Winter Simulation Conference will raise awareness and stimulate further discussion on the future of modeling methodology in areas such as modeling problems in business applications, human factors and geographically dispersed networks; rapid model development and maintenance; legacy modeling approaches; markup languages; virtual interactive process design and simulation; standards; and Grid computing

Assembling and enriching digital library collections

People who create digital libraries need to gather together the raw material, add metadata as necessary, and design and build new collections. This paper sets out the requirements for these tasks and describes a new tool that supports them interactively, making it easy for users to create their own collections from electronic files of all types. The process involves selecting documents for inclusion, coming up with a suitable metadata set, assigning metadata to each document or group of documents, designing the form of the collection in terms of document formats, searchable indexes, and browsing facilities, building the necessary indexes and data structures, and putting the collection in place for others to use. Moreover, different situations require different workflows, and the system must be flexible enough to cope with these demands. Although the tool is specific to the Greenstone digital library software, the underlying ideas should prove useful in more general contexts