More than a business model: crowd-sourcing and impact in the humanities

Stuart Dunn examines the development of crowd-sourcing activities in academic contexts and identifies the potential for looking beyond the short-term benefits crowd-sourcing offers to a project’s completion. Particularly in the humanities, a more nuanced approach may be better suited, one which fosters reciprocal relationships and engages the shared interests amongst the public and academics

Software CROWD-Sourcing

Software crowdsourcing emerged from the crowdsourcing concept and inherited most of features from it. However, it adapted its nature according to the requirements of software engineering techniques and technologies. Therefore, it is important to understand the detailed elucidation of software crowdsourcing. This paper introduces the connotation of CROWD (Community, Remoteness, Open-call, Web, Diversity) in crowdsourcing and in particular software crowdsourcing. It expounds the meaning and importance of these five CROWD components of software crowdsourcing and their contribution in making it successful

Towns conquer: a gamified application to collect geographical names (vernacular names/toponyms)

The traditional model for geospatial crowd sourcing asks the public to use their free time collecting geospatial data for no obvious reward. This model has shown to work very well on projects such as Open Street Map, but comes with some clear disadvantages such as reliance on small communities of ‘Neo-geographers’ and variability in quality and content of collected data. This project aims at tackling these problems by providing alternative motivation specifically a smartphone based computer game service. Geographical names (vernacular names/ toponyms) have been identified as potential targets as they are difficult to collect on a large scale and easy to collect locally, thus ideal for crowd sourcing. The data set will be a toponyms database provided by the Spanish National Geographic Institute (IGN Spain). A location based game is targeted as it is easy to guide data collection with in-game rewards (prizes, points, badges etc.). Android is chosen for its accessible API and wide use

Focused Proofreading: Efficiently Extracting Connectomes from Segmented EM Images

Identifying complex neural circuitry from electron microscopic (EM) images may help unlock the mysteries of the brain. However, identifying this circuitry requires time-consuming, manual tracing (proofreading) due to the size and intricacy of these image datasets, thus limiting state-of-the-art analysis to very small brain regions. Potential avenues to improve scalability include automatic image segmentation and crowd sourcing, but current efforts have had limited success. In this paper, we propose a new strategy, focused proofreading, that works with automatic segmentation and aims to limit proofreading to the regions of a dataset that are most impactful to the resulting circuit. We then introduce a novel workflow, which exploits biological information such as synapses, and apply it to a large dataset in the fly optic lobe. With our techniques, we achieve significant tracing speedups of 3-5x without sacrificing the quality of the resulting circuit. Furthermore, our methodology makes the task of proofreading much more accessible and hence potentially enhances the effectiveness of crowd sourcing

Crowd sourcing challenges assessment index for disaster management

Emergency agencies (EA) rely on inter-agency approaches to information management during disasters. EA have shown a significant interest in the use of cloud-based social media such as Twitter and Facebook for crowd-sourcing and distribution of disaster information. While the intentions are clear, the question of what are its major challenges are not. EA have a need to recognise the challenges in the use of social media under their local circumstances. This paper analysed the recent literature, 2010 Haiti earthquake and 2010-11 Queensland flood cases and developed a crowd sourcing challenges assessment index construct specific to EA areas of interest. We argue that, this assessment index, as a part of our large conceptual framework of context aware cloud adaptation (CACA), can be useful for the facilitation of citizens, NGOs and government agencies in a strategy for use of social media for crowd sourcing, in preventing, preparing for, responding to and recovering from disasters. © (2012) by the AIS/ICIS Administrative Office All rights reserved