Assessing Field Spectroscopy Metadata Quality

This paper presents the proposed criteria for measuring the quality and completeness of field spectroscopy metadata in a spectral archive. Definitions for metadata quality and completeness for field spectroscopy datasets are introduced. Unique methods for measuring quality and completeness of metadata to meet the requirements of field spectroscopy datasets are presented. Field spectroscopy metadata quality can be defined in terms of (but is not limited to) logical consistency, lineage, semantic and syntactic error rates, compliance with a quality standard, quality assurance by a recognized authority, and reputational authority of the data owners/data creators. Two spectral libraries are examined as case studies of operationalized metadata policies, and the degree to which they are aligned with the needs of field spectroscopy scientists. The case studies reveal that the metadata in publicly available spectral datasets are underperforming on the quality and completeness measures. This paper is part two in a series examining the issues central to a metadata standard for field spectroscopy datasets.

[1]  H. Kaiser.  The Application of Electronic Computers to Factor Analysis , 1960 .

[2]  Cindy Ong,et al.  Reflectance measurements of soils in the laboratory: Standards and protocols , 2015 .

[3]  Jens Nieke,et al.  The spectral database SPECCHIO for improved long-term usability and data sharing , 2009, Comput. Geosci..

[4]  Chris Bellman,et al.  Designing a robust hyperspectral dataset: The fundamental role of metadata protocols in hyperspectral field campaigns , 2011 .

[5]  Barbara A. Rasaiah,et al.  Critical Metadata Protocols in Hyperspectral Field Campaigns for Building Robust Hyperspectral Datasets , 2012 .

[6]  Punam V. Khandar,et al.  KNOWLEDGE DISCOVERY and SAMPLING TECHNIQUES with DATA MINING for IDENTIFYING TRENDS in DATA SETS , 2010 .

[7]  Erik Duval,et al.  Automatic evaluation of metadata quality in digital repositories , 2009, International Journal on Digital Libraries.

[8]  Michael F. Goodchild,et al.  BEYOND METADATA: TOWARDS USER-CENTRIC DESCRIPTION OF DATA QUALITY , 2007 .

[9]  Barbara A. Rasaiah,et al.  Critical Metadata for Spectroscopy Field Campaigns , 2014, Remote. Sens..

[10]  Dirk Leinders,et al.  Metadata Quality Evaluation of a Repository Based on a Sample Technique , 2012, MTSR.

[11]  Andreas Hueni,et al.  Approaches to establishing a metadata standard for field spectroscopy datasets , 2013, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS.

[12]  Athanasios Manitsaris,et al.  A Conceptual Framework for Metadata Quality Assessment , 2008, Dublin Core Conference.

[13]  Wolfgang Kresse,et al.  Status of the ISO/TS 19159-x technical specifications: Geographic information — Calibration and validation of remote sensing imagery sensors , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[14]  Timothy W. Cole.  Creating a Framework of Guidance for Building Good Digital Collections , 2002, First Monday.

[15]  S. J. Sutley,et al.  USGS Digital Spectral Library splib06a , 2007 .

[16]  Christian Götze,et al.  Overview of Experimental Setups in Spectroscopic Laboratory Measurements - the SpecTour Project , 2012 .

[17]  Jacqueline J Meulman,et al.  Nonlinear principal components analysis: introduction and application. , 2007, Psychological methods.

[18]  Chris Bellman,et al.  Building better hyperspectral datasets: The fundamental role of metadata protocols in hyperspectral field campaigns , 2011 .

[19]  J. Barton,et al.  Quality assurance for digital learning object repositories: issues for the metadata creation process , 2004 .

[20]  Diane I. Hillmann,et al.  The Continuum of Metadata Quality: Defining, Expressing, Exploiting , 2004 .

[21]  M. Schildhauer,et al.  Spectral Network (SpecNet)—What is it and why do we need it? , 2006 .

[22]  Jung-ran Park.  Metadata Quality in Digital Repositories: A Survey of the Current State of the Art , 2009 .

[23]  Les Gasser,et al.  A framework for information quality assessment , 2007, J. Assoc. Inf. Sci. Technol..

[24]  Owen White,et al.  The Metadata Coverage Index (MCI): A standardized metric for quantifying database metadata richness , 2012, Standards in genomic sciences.

[25]  Liping Di,et al.  U.S. FGDC CONTENT STANDARD FOR DIGITAL GEOSPATIAL METADATA: EXTENSIONS FOR REMOTE SENSING METADATA , 2000 .

[26]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[27]  Les Gasser,et al.  Metadata Quality For Federated Collections , 2004, ICIQ.