Ohmage

Abstract

Participatory sensing (PS) is a distributed data collection and analysis approach where individuals, acting alone or in groups, use their personal mobile devices to systematically explore interesting aspects of their lives and communities [Burke et al. 2006]. These mobile devices can be used to capture diverse spatiotemporal data through both intermittent self-report and continuous recording from on-board sensors and applications. Ohmage (http://ohmage.org) is a modular and extensible open-source, mobile to Web PS platform that records, stores, analyzes, and visualizes data from both prompted self-report and continuous data streams. These data streams are authorable and can dynamically be deployed in diverse settings. Feedback from hundreds of behavioral and technology researchers, focus group participants, and end users has been integrated into ohmage through an iterative participatory design process. Ohmage has been used as an enabling platform in more than 20 independent projects in many disciplines. We summarize the PS requirements, challenges and key design objectives learned through our design process, and ohmage system architecture to achieve those objectives. The flexibility, modularity, and extensibility of ohmage in supporting diverse deployment settings are presented through three distinct case studies in education, health, and clinical research.

Analyzing Spatial and Temporal User Behavior in Participatory Sensing

“…For the former, the deployment showed that the framework's campaign editor effectively enabled campaign authors to intuitively design their desired participatory sensing campaigns that collect meaningful city-related information on one hand, and that the framework's mobile application effectively assisted data collectors in gathering various types of data through their mobile devices on the other hand. This result reaffirms the potentials, applicabilities and effectiveness of multi-purpose participatory sensing frameworks, with Citizense as an example, in collecting a large variety of data in different scenarios [30,31].…”

“…Participatory sensing has been utilized in various application domains [13], such as bird conservation [25], urban infrastructure monitoring [26], traffic monitoring [27], radio signal strength measuring [28] and other information in the city [29]. The plethora of participatory sensing applications can be divided into two groups: single-purpose applications (i.e., [26,27]) and multi-purpose applications or frameworks [30,31]. The emergence of these multi-purpose participatory sensing applications shows a significant change in the realization of the participatory sensing concept.…”

“…Although it is hard to estimate the exact number of existing participatory sensing applications to date (the surveys of Khan et al [12] and Guo et al [4] analyzed 45 and 66 applications, respectively), the 21 applications used in this comparison were selected from the growing list of participatory sensing examples, and at the same time they represent the diverse and complex nature of participatory sensing. Our comparison was performed along common features observed in literature: flexibility of the tool [32], the presence of incentive [33,34], the selection of data collectors [35,36], result delivery [37,38], identity of data collectors [39] and the flexibility of the sensing process [30] (see Table 1). Additionally, useful meta-data are listed: name and publication time of the application, theme covered, origin (industry or academia) and the status of the application (a research prototype or a complete product).…”

“…Additionally, useful meta-data are listed: name and publication time of the application, theme covered, origin (industry or academia) and the status of the application (a research prototype or a complete product). Compared with other participatory sensing applications, and multi-purpose participatory sensing frameworks such as Ohmage [30] and OpenDataKit [31], Citizense proves to be more complete, combining all features from other applications/frameworks and introducing some novelties. First, it allows the selection of participants based on various criteria such as time, their profile and location.…”

A flow-based programming framework for mobile App development

“…This is exactly why more recently, several reconfigurable and reusable frameworks for mobile sensing applications have been proposed. Projects such as Sensr [8], Epicollect [3], ODK [2], and ohmage [12] provide frameworks for constructing mobile data-gathering tools. However, these configurable frameworks limit the type of data that can be collected (typically only through a form).…”