Semantically-Enabled Environmental Data Discovery and Integration: Demonstration Using the Iceland Volcano Use Case

2013 ◽  
pp. 289-297 ◽  
Author(s):  
Tatiana Tarasova ◽  
Massimo Argenti ◽  
Maarten Marx
Keyword(s):  
Environmental Data ◽  
Use Case ◽  
Data Discovery ◽  
Discovery And Integration

scholarly journals Efficient Processing of Geospatial mHealth Data Using a Scalable Crowdsensing Platform

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3456
Author(s):  
Robin Kraft ◽  
Ferdinand Birk ◽  
Manfred Reichert ◽  
Aniruddha Deshpande ◽  
Winfried Schlee ◽  
...  
Keyword(s):  
Architectural Design ◽  
Environmental Data ◽  
Common Interest ◽  
Sensor Data ◽  
Smart Sensors ◽  
Use Case ◽  
Sound Levels ◽  
Efficient Processing ◽  
Interactive Map ◽  
Technical Solutions

Smart sensors and smartphones are becoming increasingly prevalent. Both can be used to gather environmental data (e.g., noise). Importantly, these devices can be connected to each other as well as to the Internet to collect large amounts of sensor data, which leads to many new opportunities. In particular, mobile crowdsensing techniques can be used to capture phenomena of common interest. Especially valuable insights can be gained if the collected data are additionally related to the time and place of the measurements. However, many technical solutions still use monolithic backends that are not capable of processing crowdsensing data in a flexible, efficient, and scalable manner. In this work, an architectural design was conceived with the goal to manage geospatial data in challenging crowdsensing healthcare scenarios. It will be shown how the proposed approach can be used to provide users with an interactive map of environmental noise, allowing tinnitus patients and other health-conscious people to avoid locations with harmful sound levels. Technically, the shown approach combines cloud-native applications with Big Data and stream processing concepts. In general, the presented architectural design shall serve as a foundation to implement practical and scalable crowdsensing platforms for various healthcare scenarios beyond the addressed use case.

Parquet Cube to store and process gridded data

2020 ◽  
Author(s):  
elisabeth lambert ◽  
Jean-michel Zigna ◽  
Thomas Zilio ◽  
Flavien Gouillon
Keyword(s):  
Big Data ◽  
Open Source ◽  
Value Chain ◽  
Environmental Data ◽  
Use Cases ◽  
Use Case ◽  
Gridded Data ◽  
The Earth ◽  
Oceanographic Data ◽  
Second Use

<p>The volume of data in the earth data observation domain grows considerably, especially with the emergence of new generations of satellites providing much more precise measures and thus voluminous data and files. The ‘big data’ field provides solutions for storing and processing huge amount of data. However, there is no established consensus, neither in the industrial market nor the open source community, on big data solutions adapted to the earth data observation domain. The main difficulty is that these multi-dimensional data are not naturally scalable. CNES and CLS, driven by a CLS business needs, carried out a study to address this difficulty and try to answer it.</p><p>Two use cases have been identified, these two being complementary because at different points in the value chain: 1) the development of an altimetric processing chain, storing low level altimetric measurements from multiple satellite missions, and 2) the extraction of oceanographic environmental data along animal and ships tracks. The original data format of these environmental variables is netCDF. We will first show the state of the art of big data technologies that are adapted to this problematic and their limitations. Then, we will describe the prototypes behind both use cases and in particular how the data is split into independent chunks that then can be processed in parallel. The storage format chosen is the Apache parquet and in the first use case, the manipulation of the data is made with the xarray library while all the parallel processes are implemented with the Dask framework. An implementation using Zarr library instead of Parquet has also been developed and results will also be shown. In the second use case, the enrichment of the track with METOC (Meteo/Oceanographic) data is developed using the Spark framework. Finally, results of this second use case, that runs operationally today for the extraction of oceanographic data along tracks, will be shown. This second solution is an alternative to Pangeo solution in the world of industrial and Java development. It extends the traditional THREDDS subsetter, delivered by the Open source Unidata Community, to a bigdata implementation. This Parquet storage and associated service implements a smoothed transition of gridded data in Big Data infrastructures.</p>

scholarly journals Development and Application of an Open Tool for Sharing and Analyzing Integrated Clinical and Environmental Exposures Data: an Asthma Use Case (Preprint)

2021 ◽  
Author(s):  
Karamarie Fecho ◽  
Stanley C Ahalt ◽  
Steven Appold ◽  
Saravanan Arunachalam ◽  
Emily Pfaff ◽  
...  
Keyword(s):  
Emergency Department ◽  
Open Source ◽  
Environmental Exposures ◽  
Application Programming Interface ◽  
Primary Outcome Measure ◽  
Environmental Data ◽  
Use Case ◽  
Chi Square ◽  
Patient Level ◽  
Asthma Exacerbations

BACKGROUND The Integrated Clinical and Environmental Exposures Service (ICEES) serves as an open-source, disease-agnostic, regulatory-compliant framework and approach for openly exposing and exploring clinical data that have been integrated at the patient level with a variety of environmental exposures data. ICEES is equipped with tools to support basic statistical exploration of the integrated data in a completely open manner. OBJECTIVE This study aims to further develop and apply ICEES as a novel tool for openly exposing and exploring integrated clinical and environmental data. We focus on an asthma use case. METHODS We queried the ICEES open application programming interface using a functionality that supports Chi Square tests between feature variables and a primary outcome measure, with a Bonferroni correction for multiple comparisons (α=.001). We focused on two primary outcomes that are indicative of asthma exacerbations: annual emergency department (ED) or inpatient visits for respiratory issues; and annual prescriptions for prednisone. RESULTS Of the N = 157,410 patients within the asthma cohort, N = 26,332 patients (16.05%) had one or more annual emergency department or inpatient visits for respiratory issues, and N = 17,056 patients (10.40%) had one or more annual prescriptions for prednisone. We found that close proximity to a major roadway or highway, exposure to high levels of PM2.5 or ozone, female sex, Caucasian race, low residential density, lack of health insurance, and low household income were significantly associated with asthma exacerbations (P<.001). Asthma exacerbations did not vary by rural vs urban residence. Moreover, the results were largely consistent across outcome measures. CONCLUSIONS Our results demonstrate that ICEES can be used to replicate and extend published findings on factors that influence asthma exacerbations. As a disease-agnostic, open-source approach for integrating, exposing, and exploring patient-level clinical and environmental exposures data, we believe that ICEES will have broad adoption by other institutions and application in environmental health and other biomedical fields.

scholarly journals BiobankUniverse: automatic matchmaking between datasets for biobank data discovery and integration

2017 ◽  
Vol 33 (22) ◽  
pp. 3627-3634 ◽  
Author(s):  
Chao Pang ◽  
Fleur Kelpin ◽  
David van Enckevort ◽  
Niina Eklund ◽  
Kaisa Silander ◽  
...  
Keyword(s):  
Data Discovery ◽  
Discovery And Integration

scholarly journals Burgeoning Data Repository Systems, Characteristics, and Development Strategies: Insights of Natural Resources and Environmental Scientists

2017 ◽  
Vol 1 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Yi Shen
Keyword(s):  
Natural Resources ◽  
Scientific Data ◽  
Environmental Data ◽  
Community Research ◽  
Data Repository ◽  
Data Discovery ◽  
Data Repositories ◽  
Multiple Data ◽  
Novel Approach ◽  
Value Propositions

Abstract Currently, we are witnessing the emergence and abundance of many different data repositories and archival systems for scientific data discovery, use, and analysis. With the burgeoning of available data-sharing platforms, this study addresses how scientists working in the fields of natural resources and environmental sciences navigate these diverse data sources, what their concerns and value propositions are toward multiple data discovery channels, and most importantly, how they perceive the characteristics and compare the functionalities of different types of data repository systems. Through a user community research of domain scientists on their data use dynamics and insights, this research provides strategies and discusses ideas on how to leverage these different platforms. Furthermore, it proposes a top–down, novel approach to the processes of searching, browsing, and visualizing for the dynamic exploration of environmental data.

ViSER: Visualizing Supply Chains for Eco-Conscious Redesign

2014 ◽  
Author(s):  
William Z. Bernstein ◽  
Devarajan Ramanujan ◽  
Niklas Elmqvist ◽  
Fu Zhao ◽  
Karthik Ramani
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Visual Analytics ◽  
Environmental Data ◽  
Product Architecture ◽  
Change Propagation ◽  
Use Case ◽  
Data Representations

In this paper, we present ViSER, an interactive visual analytics platform that visualizes supply chain data for enabling eco-conscious redesign. ViSER provides a visualization dashboard consisting of multiple mutually coordinated views that provide different perspectives on a particular supply chain scenario. Our platform allows users to visualize a change propagation metric associated with a particular redesign path. Hence, the user can balance the advantages of a redesign opportunity with the risk associated with its effect on the rest of the supply chain. Furthermore, ViSER offers lifecycle data representations that inform users’ decisions particularly in the context of eco-conscious re-design. Coupling such environmental data with graph-based visualizations of product architecture, ViSER provides a novel decision platform for designers with a range of expertise levels. To demonstrate its utility, two use-case scenarios, from both a novice and expert perspective, are presented in detail.

scholarly journals Planet Microbe: a platform for marine microbiology to discover and analyze interconnected ‘omics and environmental data

2020 ◽  
Vol 49 (D1) ◽  
pp. D792-D802
Author(s):  
Alise J Ponsero ◽  
Matthew Bomhoff ◽  
Kai Blumberg ◽  
Ken Youens-Clark ◽  
Nina M Herz ◽  
...  
Keyword(s):  
Large Scale ◽  
Environmental Data ◽  
Sequencing Data ◽  
Sample Collection ◽  
Data Discovery ◽  
Web Based ◽  
Marine Microbiology ◽  
Science Community ◽  
Marine Microbial Communities ◽  
Collaborative Efforts

Abstract In recent years, large-scale oceanic sequencing efforts have provided a deeper understanding of marine microbial communities and their dynamics. These research endeavors require the acquisition of complex and varied datasets through large, interdisciplinary and collaborative efforts. However, no unifying framework currently exists for the marine science community to integrate sequencing data with physical, geological, and geochemical datasets. Planet Microbe is a web-based platform that enables data discovery from curated historical and on-going oceanographic sequencing efforts. In Planet Microbe, each ‘omics sample is linked with other biological and physiochemical measurements collected for the same water samples or during the same sample collection event, to provide a broader environmental context. This work highlights the need for curated aggregation efforts that can enable new insights into high-quality metagenomic datasets. Planet Microbe is freely accessible from https://www.planetmicrobe.org/.

Pemodelan Website Geografis Tempat Pelayanan Kesehatan di Palembang

2018 ◽  
Vol 7 (2) ◽  
pp. 144
Author(s):  
Arsia Rini ◽  
Heki Aprianto
Keyword(s):  
Object Oriented ◽  
Use Case ◽  
Activity Diagram ◽  
Use Case Diagram

Tempat pelayanan kesehatan bertujuan untuk memberikan pelayanan kesehatan kepada masyarakat melalui lembaga institusi pelayanan kesehatan. Masyarakat di Kota Palembang mendapatkan informasi tempat pelayanan kesehatan melalui informasi masyarakat sekitar, lembaga pelayanan kesehatan dan beberapa situs internet yang ditampilkan secara terpisah. Maka sebuah website geografis diperlukan untuk menampilkan tata letak lokasi pelayanan kesehatan dan informasi lengkap tentang pelayanan kesehatan di Kota Palembang. Penelitian ini bertujuan untuk membuat sebuah pemodelan website geografis tempat pelayanan kesehatan di Kota Palembang. Pemodelan yang digunakan berbasis object oriented dengan menerapkan use case diagram dan activity diagram.

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