Research paper: A centralized tool for managing, archiving, and serving point-in-time data in ecological research laboratories

  • Authors:

  • Seth J. K. Mason;Sean B. Cleveland;Pol Llovet;Clemente Izurieta;Geoffrey C. Poole

  • Affiliations:

  • Department of Computer Science, Montana State University, 357 EPS Building, Bozeman, MT 59717, USA;Research Computing Group, Montana State University, P.O. Box 173505, Bozeman, MT 59715, USA;Research Computing Group, Montana State University, P.O. Box 173505, Bozeman, MT 59715, USA;Department of Computer Science, Montana State University, 357 EPS Building, Bozeman, MT 59717, USA and Montana Institute on Ecosystems, Montana State University, 106 AJM Johnson Hall, Bozeman, MT ...;Department of Land Resources and Environmental Sciences, Montana State University, P.O. Box 173120, Bozeman, MT 59717, USA and Research Computing Group, Montana State University, P.O. Box 173505, ...

  • Venue:
  • Environmental Modelling & Software
  • Year:
  • 2014

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Abstract

The recent proliferation of software tools that aid researchers in various phases of data tracking and analysis undoubtedly contribute to successful development of increasingly complex and data-intensive scientific investigations. However, the lack of fully integrated solutions to data acquisition and storage, quality assurance/control, visualization, and provenance tracking of heterogeneous temporal data streams collected at numerous geospatial locations continues to occupy a general problem area for scientists and data managers working in the environmental sciences. We present a new Service Oriented Architecture (SOA) that allows users to: 1) automate the process of pushing real-time data streams from networks of environmental sensors or other data sources to an electronic data archive; 2) to perform basic data management and quality control tasks; and 3) to publish any subset of the data to existing cyberinfrastructure platforms for global discovery and distribution via the World Wide Web. The approach outlined here supports management of: 1) repeated field observations, 2) data from laboratory analysis of field samples, 3) simulation results, and 4) derived values. We describe how the use of Hypertext Transfer Protocol (HTTP) Application Programming Interfaces (APIs) Representational State Transfer (REST) methods for data model objects and Resource Query Language (RQL) interfaces respond to a basic problem area in environmental modelling by enabling researchers to integrate an electronic data repository with existing workflows, simulation models, or third-party software.