J
John H. Porter
Researcher at University of Virginia
Publications - 57
Citations - 7295
John H. Porter is an academic researcher from University of Virginia. The author has contributed to research in topics: Information management & Barrier island. The author has an hindex of 24, co-authored 57 publications receiving 6546 citations. Previous affiliations of John H. Porter include University of Liverpool.
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Improving forecasts for noisy geographic time series
TL;DR: It is suggested that simple top-down forecasting models may provide a general-purpose method for improving forecasting for noisy geographic time series in many applications.
Journal ArticleDOI
Cost-distance analysis of mesopredators as a tool for avian habitat restoration on a naturally fragmented landscape
TL;DR: This work applied cost-distance analysis, coupled to a sensitivity analysis, and least-cost path analysis to raccoons and red foxes on the Virginia barrier islands to determine the landscape resistance, supporting the resistance structure identified.
Journal ArticleDOI
A prototype system for multilingual data discovery of International Long-Term Ecological Research (ILTER) Network data
Kristin Vanderbilt,John H. Porter,Sheng-Shan Lu,Nic Bertrand,David Blankman,Xuebing Guo,Honglin He,Don Henshaw,Karpjoo Jeong,Eun-Shik Kim,Chau-Chin Lin,Margaret O'Brien,Takeshi Osawa,Éamonn Ó Tuama,Wen Su,Haibo Yang +15 more
TL;DR: This work implemented a prototype web-services-based system for searching International Long-Term Ecological Research Network data repositories that builds on the use of a multilingual thesaurus to make searches more complete than would be obtained through search term-translation alone.
A Metadata-based Framework for Multilingual Ecological Information Management
TL;DR: A framework of an ecological information management prototype of tools based on a metadata standard and results of the application consist of an Ecological Metadata Language (EML) document database module, a data analysis function module, and a collection of 58 EML documents.
Establishing an EML-based Data Management System for Automating Analysis of Field Sensor Data
TL;DR: To address the management and quality assurance problems of sensor data, a tool based on the Ecological Metadata Language (EML) is developed that allows researchers to access EML, upload data, check data quality, and then run R code on the server.