Data and Metadata Challenges

1. 5 1 2 6 5 3 4 Implementation Effort Abstract WALSAIP Conceptual Model References Ongoing Work Problem Formulation Proposed Solution Study Mechanisms for data and metadata acquisition • Data + Metadata + Processing • Decision Making! Study correspondences of data and metadata files Raw Data Servers Computed Data Servers INTERNET Data Representation Systems Computational Signal Processing Systems Signal Data Post-processing Information Rendering Systems Signal Conditioning System 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 2006-07-05 22:23:00.14 2006-07-06 22:23:00.14 0 138 humidity Sensor Array Structures Pre-processing Stage Processing Stage Post-processing Stage Data Metadata Automated XML Schema Representation in Sensor Array Processing Systems Luz V. Acabá-Cuevas – M.S. Student Prof. Domingo Rodríguez – Advisor AIP Group, ECE Department, University of Puerto Rico, Email: Luz.Acaba@ece.uprm.edu Mayagüez Campus Hazards: JammingInterferencePower FailureEtc…. AUTOMATE! This research aims to provide solution to problems on remote sensing such as lack of direct physical relationship between data and metadata files and the ambiguity of interpretation between different users with heterogeneous systems (software in which data/metadata will be processed), and platforms (Linux, Windows, Unix, ...etc). To address the accessibility and interoperability aspects of data in the Wide Area Large Scale Automated Information Processing Project (WALSAIP) this work explores the encapsulation of data and metadata together in order to create a direct relationship between them ensuring the usefulness of each reading taken from sensors. Data MetaData • Using Java, XML, and FTP technologies, will be used to encapsulate data and metadata files together in order to transfer them across multiple server. • The encapsulation can be reversed in order to fit information destination. • Once encapsulated, files can be transferred using FTP technology. • The user can create a Stencil in order to customize XML tags that are going to be used in the encapsulation. XML Information Source XML Coder Tx Transmitter Communication Channel Data MetaData XML Information Destination XML Decoder Rx Receiver Figure 4. Shannon’s Theory and XML Processing • The solution contemplates dynamic metadata management. • Data and metadata can be enhanced with user observations. • User can edit the obtained data by adding comments and parameters. Figure 5. Information Flow Using Shannon’s Theory Figure 1. WALSAIP Conceptual Model   <?xml version="1.0" encoding="iso-8859-1" ?> <walsaip> <metadata> <research>   <researchName>Wide Area Large Scale Automated Information Processing</researchName>   <intitution>University of Puerto Rico at Mayaguez</intitution>   <department>Department of Electrical and Computer Engineering</department>   <address>PO Box 9000, Mayagüez, P.R. 00681-9000</address>   <phone>787-832-4040</phone>   <contact>Domingo Rodriguez</contact>   <email>domingo@ece.uprm.edu</email>   </research> <sensingInfo>   <InitialTimeStamp>2006-07-05 22:23:00.14</InitialTimeStamp>   <endingTimeStamp>2006-07-06 22:23:00.14</endingTimeStamp>   <nodeID>0</nodeID>   <samplingRate>138</samplingRate>   <dataType>humidity</dataType>   </sensingInfo>   </metadata> <data> 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 65535 </data>   </walsaip> • Develop a framework for sensor signal acquisition and server storage of raw data. • Implement solution to force direct and specific relationship between data and metadata files. • Analyze dynamic metadata management. Data and Metadata • Signal Data - all readings collected directly from sensors. • Metadata – data that describes data. Metadata is crucial to provide researchers a concrete idea of the real conditions in which data was collected. Metadata is a determinant of how the environment influenced the measurement in case of abnormal findings. Data and Metadata Challenges • There is a need to ensure direct physical relationship between data and metadata files in order to ensure the significance of readings. • Data should be interoperable across heterogeneous users. Heterogeneous users are users with different data architectures, storage systems, and platforms. • A mechanism should be design to make data readable and comprehensive across users heterogeneous users and different disciplines. • Lack of support for dynamic metadata. • Need to incorporate information from “Human Sensors”. Figure 5. Data and Metadata Encapsulation Process • Applying software engineering techniques to the design of the solution. • Generating the code that implements the solution. • Identifying potential test cases to perform functional verification test at the end of the coding. • Integrate the solution to the WALSAIP architecture. Figure 2. Decision Making Input [1] Manetti Luca, Terribilini Andrea, Knecht Alfredo, “Autonomous Remote Monitoring System for Landslides”, SPIE’s 9th Annual International Symposium on Smart Structures and Materials, 2002, San Diego, CA. [2] Nativi Stefano, Giuli Dino, Innocenti Emilio Bugli, “Interoperability for Multimedia Systems to Support Decision-Makers in the Environment Sector” IEEE International Conference On Multimedia Computing and Systems, Volume 2, June 1999, Pages 338-342 [3] Dong-Jun Won, Il-Yop Chung,   Joong-Moon Kim,  Seung-Il Moon,   Jang-Cheol Seo,   Jong-Woong Choe, D Won, II-Yop Chung, J. Kim, S. Moon, J. Seo, J. Choe, “Development of Power Quality Monitoring System with Central Processing Scheme”, Power Engineering Society Summer Meeting, IEEE, South Korea, pp. 915-919 vol.2, 21-25 July 2002. [4] MANTIS Project (MultimodAl Networks of In-situ Sensors): http://mantis.cs.colorado.edu/index.php/tiki-index.php Figure 3. Example: NERR System Data/Metadata