OPeNDAP: Accessing Data in a Distributed, Heterogeneous Environment

Slides:



Advertisements
Similar presentations
Forest Markup / Metadata Language FML
Advertisements

The current state of Metadata - as far as we understand it - Peter Wittenburg The Language Archive - Max Planck Institute CLARIN Research Infrastructure.
Data - Information - Knowledge
Technical Architectures
The HITCH project: Cooperation between EuroRec and IHE Pascal Coorevits EuroRec 2010 Annual Conference June 18 th 2010.
A New Computing Paradigm. Overview of Web Services Over 66 percent of respondents to a 2001 InfoWorld magazine poll agreed that "Web services are likely.
Architecture, Deployment Diagrams, Web Modeling Elizabeth Bigelow CS-15499C October 6, 2000.
Chapter 2 Database Environment Pearson Education © 2014.
Peter Cornillon University of Rhode Island Presented at the 10 September 2003 NVODS Workshop Washington DC The National Virtual Ocean Data System (NVODS):
Presented by Sujit Tilak. Evolution of Client/Server Architecture Clients & Server on different computer systems Local Area Network for Server and Client.
Web-based Portal for Discovery, Retrieval and Visualization of Earth Science Datasets in Grid Environment Zhenping (Jane) Liu.
Open Cloud Sunil Kumar Balaganchi Thammaiah Internet and Web Systems 2, Spring 2012 Department of Computer Science University of Massachusetts Lowell.
System Design/Implementation and Support for Build 2 PDS Management Council Face-to-Face Mountain View, CA Nov 30 - Dec 1, 2011 Sean Hardman.
CSCI 5980: From GPS and Google Earth to Spatial Computing Fall 2012 Midterm Presentation Chapter 7: Architectures Team 9: Thao Nguyen, Nathan Poole October.
Metadata and Geographical Information Systems Adrian Moss KINDS project, Manchester Metropolitan University, UK
Peter Cornillon Graduate School of Oceanography University of Rhode Island Presented at the NSF Sponsored Cyberinfrastructure Meeting 31 October 2002 OPeNDAP:
Accessing Remote Datasets using the DAP protocol through the netCDF interface. Dr. Dennis Heimbigner Unidata netCDF Workshop August 3-4, 2009.
Peter Cornillon University of Rhode Island Presented at the 12 September 2003 NVODS Workshop Washington DC NVODS: Summary.
Manag ing Software Change CIS 376 Bruce R. Maxim UM-Dearborn.
Metadata – use data discovery e.g. a library catalog data assessment determine the fitness-for-purpose of a data set data retrieval e.g., format.
Cooperation & Interoperability Architecture & Ontology.
Sun Earth Connection Distributed Data Services Presented at the Principle Investigator's Meeting NASA's Applied Information Systems Research Program 5.
Chapter 2 Database Environment.
File Transfer And Access (FTP, TFTP, NFS). Remote File Access, Transfer and Storage Networks For different goals variety of approaches to remote file.
1 Chapter 22 Distributed DBMSs - Concepts and Design Simplified Transparencies © Pearson Education Limited 1995, 2005.
Data Grids, Digital Libraries and Persistent Archives: An Integrated Approach to Publishing, Sharing and Archiving Data. Written By: R. Moore, A. Rajasekar,
Client/Server Technology
Distributed OS.
Data Browsing/Mining/Metadata
4.01 How Web Pages Work.
DAP+NETCDF Using the netCDF-4 Data Model
James Gallagher OPeNDAP
HTTP and Abstraction on the Internet
Fundamentals of Information Systems, Sixth Edition
Distributed Shared Memory
HTTP and Abstraction on the Internet
WEB SERVICES.
REST- Representational State Transfer Enn Õunapuu
Operating Systems (CS 340 D)
Siri Jodha Khalsa CIRES, Univ. of Colorado
SOA (Service Oriented Architecture)
E-commerce | WWW World Wide Web - Concepts
Distributed Databases
Telemedicine.
E-commerce | WWW World Wide Web - Concepts
Active Data Management in Space 20m DG
Integrating Data and Information Across Observing System
University of Technology
Introduction to Cloud Computing
#01 Client/Server Computing
Unit# 8: Introduction to Computer Programming
Chapter 2 Database Environment Pearson Education © 2009.
ECE 4450:427/527 - Computer Networks Spring 2017
Automated MS Word and PowerPoint Translator
File Systems and Databases
Database Environment Transparencies
Health Ingenuity Exchange - HingX
An ecosystem of contributions
HTTP and Abstraction on the Internet / The Need for DNS
Chapter 17: Client/Server Computing
Institutional Repositories
ExPLORE Complex Oceanographic Data
Computer Networking A Top-Down Approach Featuring the Internet
Categories of Networks
MSDI training courses feedback MSDIWG10 March 2019 Busan
Brokering as a Core Element of EarthCube’s Cyberinfrastructure
Web Servers (IIS and Apache)
Exceptions and networking
#01 Client/Server Computing
Presentation transcript:

OPeNDAP: Accessing Data in a Distributed, Heterogeneous Environment Peter Cornillon Graduate School of Oceanography University of Rhode Island Presented at the NSF Sponsored Cyberinfrastructure Meeting 31 October 2002

Distributed Oceanographic Data System DODS consisted of two fundamental parts: a discipline independent core infrastructure for moving data on the net, a discipline specific portion related to data –population, location, specialized clients, etc.

DODS  OPeNDAP & NVODS To isolate the discipline independent part of the system from the discipline specific part, two entities have been formed: Open Source Project for a Network Data Access Protocol (OPeNDAP) National Virtual Ocean Data System (NVODS)

The Core Infrastructure Interoperability

Interoperability - Metadata The degree to which machine-to-machine interoperability is achieved depends on the metadata associated with the data.

OPeNDAP and Metadata

Metadata Types We define two classes of metadata: Search metadata – used to locate data sets of interest in a distributed data system. Use metadata –needed to actually use the data.

Use Metadata Syntactic use metadata Semantic use metadata We divide use metadata into two classes: Syntactic use metadata Semantic use metadata

Syntactic Use Metadata Information about the data types and structures at the computer level - the syntax of the data; e.g., variable T represents a 20x40 element floating point array.

Semantic Use Metadata e.g., variable T represents Information about the contents of the data set. e.g., variable T represents sea surface temperature with units of ºC

Semantic Use Metadata We divide semantic use metadata into two classes: Translational Semantic Use Metadata Descriptive Semantic Use Metadata

Translational Semantic Use Metadata Metadata required to make use of the data; e.g., to properly label a plot of the data Define the translation from received values to semantically meaningful values Examples Variable names in the data set: t  SST Units of the data: 0.125 C+4  C Missing value flags: -99  missing value

OPeNDAP and Metadata

OPeNDAP - NVODS Status

OPeNDAP/NVODS Server Sites OPeNDAP Server Sites OPeNDAP/NVODS Server Sites

OPeNDAP Client and Server Status

Special Servers

Lessons (Re)Learned

Lessons (Re)Learned 1. Modularity provides for flexibility The more modular the underlying infrastructure the more flexible the system. This is particularly important for network based systems for which the technology, software and hardware, are changing rapidly.

Lessons (Re)Learned 2. Data of interest will be stored in a variety of formats. Regardless of how much one might want to define the format to be used by system participants, in the end the data will be stored in a variety of formats. 2a. The same is true of translational use metadata!

Lessons Learned 3. Structural representation of sequence data sets is a major obstacle to interoperability Care must be given to the organizational structure (as opposed to the format) of the data. This is the single largest constraint to the use of profile data in NVODS.

Lessons (Re)Learned 4. “Not invented here” Avoid the “not invented here” trap. The basic concepts of a data system are relatively straightforward to define. Implementing these concepts ALWAYS involves substantially more work than originally anticipated. The “Devil’s in the details”. Take advantage of existing software wherever possible.

Lessons (Re)Learned 5. Work with those who adopt the system for their own needs. Take advantage of those who are interested in contributing to the system because the system addresses their needs as opposed to those who are simply doing the work for the associated funding. => Open source.

Lessons Learned 6. There is no well defined funding structure for community based operational systems. It is much easier to obtain funding to develop a system than it is to obtain funding to maintain and evolve a system. This is a major obstacle to development of a stable cyberinfrastructure that meets the needs of the research community.

Lessons Learned 7. It is relatively more difficult to obtain funding for applied system development than for research related to data systems. This is another obstacle to the development of cyberinfrastructure that meets the needs of the research community.

Lessons (Re)Learned 8. “Tough to teach old dogs new tricks” Introducing new technology often requires a cultural change in usage that is difficult to effect. This can negatively effect system development.

Lesser Lessons Learned 9. Some surprises encountered in the NVODS/ OPeNDAP effort Heavy within organization usage. Metadata focus in the past is appropriate for interoperability at the data level. Number of variables increases almost linearly with the number of data sets. Users will take advantage of all of the flexibility offered by a system sometimes to the disadvantage of all. Incredible variability in the structural organization of data.

Lessons Learned 10. Metrics suggest Increasing use of scripted requests Large volume transfers As data systems offering machine-to- machine interoperability with semantic meaning take hold, we could well see an explosive growth in the use of the web.

Lessons Learned 11. Time to maturity is order 10 years not 3 Developing new infrastructure takes time, both to iron out all of the %^*% little details and adoption of the infrastructure takes time.

The more metadata required the less data delivered Peter’s Law The more metadata required the less data delivered Of course, the less metadata, the harder it is to use the data

http://unidata.ucar.edu/packages/dods http://nvods.org http://unidata.ucar.edu/packages/dods http://nvods.org