Ecosystems monitoring is essential to properly understand their development and the effects of events, both climatological and anthropological in nature. The amount of data used in these assessments is increasing at very high rates. This is due to increasing availability of sensing systems and the development of new techniques to analyze sensor data. The Enviro-Net Project encompasses several of such sensor system deployments across five countries in the Americas. These deployments use a few different ground-based sensor systems, installed at different heights monitoring the conditions in tropical dry forests over long periods of time. This paper presents our experience in deploying and maintaining these systems, retrieving and pre-processing the data, and describes the Web portal developed to help with data management, visualization and analysis.
To the best of our knowledge, none of the deployment efforts reviewed here address the same scenario as ours: having (multi-year) long term deployments, based on cooperative efforts of several (heterogeneous) teams, using commercially available equipment from multiple manufacturers, with an integrated effort of data retrieval, quality control and data availability through an easy to use Web-based platform. We believe this is a more realistic scenario for ground-based environmental monitoring efforts. The current efforts within the Life Under Your Feet project ( http: lifeunderyourfeet.org ) @cite_23 are the closest to our own, also having long term, spatially distributed deployments with a Web-based data visualization interface integrated with geolocation information. However, they do not seem to deal with heterogeneous equipment and data formats, nor offer filtering aggregation options, derived datasets or quality information in their data management solution.
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Abstract. In principle, water quality can be managed through an integrative perspective on watersheds, facilitated by a web-based information system. This paper describes a prototype of a web-based Information System for Georgia watersheds called ‘GWIS: Georgia Watershed Information System’. The principal functionality of the system is to provide a platform for integrating state-wide efforts in environmental information collection, collation, storage, analysis, retrieval, and dissemination to all potential stakeholders. Several data management, modeling, visualization, mapping and resource management tools for watersheds, as well as interfaces for integration across diverse and dispersed data sources, are included in the system. As its initial point of departure — to provide substantial and specific content — GWIS has been populated with the high-volume high-quality (HVHQ; near continuous) water quality data acquired during field monitoring campaigns over the past 11 years with the Environmental Process Control Laboratory (EPCL) of the University of Georgia. Information Systems (EIS) modeling with artificial in Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in Long-Term Scenarios (STRANDS) project (http: strandsproject.eu), we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots and deploying these systems for long-term installations in security and care environments. Our robots have been operational for a combined duration of 104 days over four deployments, autonomously performing end-user-defined tasks and traversing 116 km in the process. In this article, we describe the approach we used to enable long-term autonomous operation in everyday environments and how our robots are able to use their long run times to improve their own performance. The NERSC Web Toolkit (NEWT) brings High Performance Computing (HPC) to the web through easy to write web applications. Our work seeks to make HPC resources more accessible and useful to scientists who are more comfortable with the web than they are with command line interfaces. The effort required to get a fully functioning web application is decreasing, thanks to Web 2.0 standards and protocols such as AJAX, HTML5, JSON and REST. We believe HPC can speak the same language as the web, by leveraging these technologies to interface with existing grid technologies. NEWT presents computational and data resources through simple transactions against URIs. In this paper we describe our approach to building web applications for science using a RESTful web service. We present the NEWT web service and describe how it can be used to access HPC resources in a web browser environment using AJAX and JSON. We discuss our REST API for NEWT, and address specific challenges in integrating a heterogeneous collection of backend resources under a single web service. We provide examples of client side applications that leverage NEWT to access resources directly in the web browser. The goal of this effort is to create a model whereby HPC becomes easily accessible through the web, allowing users to interact with their scientific computing, data and applications entirely through such web interfaces. Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, data annotation, natural-language processing and decision support. BioPortal (http: bioportal.bioontology.org) is an open repository of biomedical ontologies that provides access via Web services and Web browsers to ontologies developed in OWL, RDF, OBO format and Protege frames. BioPortal functionality includes the ability to browse, search and visualize ontologies. The Web interface also facilitates community-based participation in the evaluation and evolution of ontology content by providing features to add notes to ontology terms, mappings between terms and ontology reviews based on criteria such as usability, domain coverage, quality of content, and documentation and support. BioPortal also enables integrated search of biomedical data resources such as the Gene Expression Omnibus (GEO), ClinicalTrials.gov, and ArrayExpress, through the annotation and indexing of these resources with ontologies in BioPortal. Thus, BioPortal not only provides investigators, clinicians, and developers ‘one-stop shopping’ to programmatically access biomedical ontologies, but also provides support to integrate data from a variety of biomedical resources.