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Featured Articles

Featured Articles

Sensor and sensor data management best practices released

Issue: 
Spring 2014

Corinna Gries (NTL), Don Henshaw (AND), Renee F.

LTER Information Management: Continuing Education and Site Change

Issue: 
Spring 2011

Karen Baker and Mason Kortz (PAL, CCE)

Auditing LTER Data Access

Issue: 
Fall 2007

- Mark Servilla and James Brunt (LNO)

Authors' note - The information in this article was first presented in May 2007 as a Request for Comments (RFC) sent to the LTER Information Managers. This article has incorporated some of the remarks provided back from the RFC, and the authors would like to thank those who provided comments.

WaterViz for Hubbard Brook: A New Water Cycle Visualization and Sonification Tool

Issue: 
Fall 2014

Using the GCE Data Toolbox as an EML-compatible workflow engine for PASTA

Issue: 
Fall 2014

Wade Sheldon (GCE)

The GCE Data Toolbox for MATLAB was initially developed in 2000 to process, quality control and document environmental data collected at the then-new Georgia Coastal Ecosystems LTER site (Sheldon, 2001). Development of this software framework has continued steadily since then, adding graphical user interface dialogs (Sheldon, 2002), data indexing and search (Sheldon, 2005), web-based data mining (Sheldon, 2006; Sheldon, 2011b), dynamic QA/QC (Sheldon, 2008), and a growing suite of tools for automating data harvesting and publishing (Sheldon et al. 2013; Gries et al., 2013). We began distributing a compiled version of the toolbox to the public in 2002, and in 2010 we released the complete source code under an open source GPL license (Sheldon, 2011a). Today, the GCE Data Toolbox is used at multiple LTER sites and other research programs across the world for a wide variety of environmental data management tasks, and we are actively working to make it a more generalized tool for the scientific community (Chamblee et al., 2013).

The toolbox can be leveraged in many ways, but it has proven particularly useful for designing automated data processing, quality control and synthesis workflows (Sheldon et al., 2013; Cary and Chamblee, 2013; Gries et al., 2013). Key factors include broad data format support, a flexible metadata templating system, dynamic rule-based QA/QC, automated metadata generation and metadata-based semantic processing (fig.1). Consequently, the GCE Data Toolbox was one of the technologies chosen for a 2012 LTER NIS workshop convened to test the PASTA Framework for running analytical workflows (see http://im.lternet.edu/im_practices/data_management/nis_workflows). The lack of built-in support for EML metadata proved to be a significant barrier to fully utilizing this toolbox for PASTA workflows during the workshop; however, complete EML support has since been implemented. This article describes how the GCE Data Toolbox can now be used as a complete workflow engine for PASTA and other EML-compatible frameworks.

 

DataONE to enable semantic searches for LTER NPP data

Issue: 
Fall 2014

Margaret O'Brien (SBC)

Obstacles finding complex NPP data

Google, Bing, Yahoo and your metadata

Issue: 
Fall 2014

Inigo San Gil (MCM), Stéphane Corlosquet (Aquia) and Adam Shepherd (ESIP - WHOI)

After years of suspense, the wait is over:  The big three search engines have chosen a standard (aka specification) to provide information contributors with better mechanisms for describing information resources.  The search engines improved the classification and sorting of information, resulting in a better experience when searching content on the web. When we say "content", we include datasets. This is the reason why data keepers should put attention to these particular advances by the main search engines and the reason we wrote this brief article.

The Google-Bing-Yahoo-Yandex chosen specifications reside in schema.org. The initiative was announced in June 2011, followed by workshops and early adopters (such as the White House). The first author of this article became aware of the Schema.org initiative during the last IM/ESIP meeting (ESIP, 2014). Here we expand on the Schema.org related topics covered at the ESIP Schema.org hack-a-thon session (Fils and Shepperd, 2014).

This article offers you a light view of the dataset specification at schema.org, a practical way to catch up with the schema.org specification, along with a motivation -- why would LTER comply with yet another metadata specification. The main merit of Schema.org adoption is to mitigate the failure in data discovery when the data seeker uses the main internet search engines.

Becoming an Information Professional: A Student Experience with UIUC MLIS Program’s Data Curation Specialization

Issue: 
Fall 2014

Chung-Yi Hou, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign

History of Geographic Information Systems (GIS) in the LTER Network

Issue: 
Spring 2014

Theresa Valentine (AND)

Data Integration Experiences

Issue: 
Spring 2014

James Connors (CCE, PAL)

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