SlideShare uma empresa Scribd logo
1 de 22
HDF Update
Mike Folk
HDF-EOS Workshop IV
Sept. 19-21, 2000
University of Illinois at Urbana-Champaign

-1-

HDF
Topics
• What is HDF?
• HDF community
• HDF4
– past and future work

• HDF5
–
–
–
–

HDF5-HDF5 interoperability
Activities and growth
Tools and utilities
Focus for 2001
University of Illinois at Urbana-Champaign

-2-

HDF
NCSA HDF Mission

To develop, promote, deploy, and support
open and free technologies that facilitate
scientific data storage, exchange, access,
analysis and discovery.

University of Illinois at Urbana-Champaign

-3-

HDF
What is HDF?
•
•
•
•
•
•

Format and software for scientific data
Stores images, arrays, tables, etc.
Emphasis on storage and I/O efficiency
Free and commercial software support
Emphasis on standards
Users from many engineering & scientific fields
University of Illinois at Urbana-Champaign

-4-

HDF
HDF People
• NCSA
– QA, maintanance & support
– Library development & performance
– Tools development

• EOS & ASCI
– Users, applications and tools
– Performance

• Volunteers from all over
– Users, applications & tools
University of Illinois at Urbana-Champaign

-5-

HDF
Who is supporting HDF?
• NASA/ESDIS
– Earth science applications, instrument data
– All aspects of data management
• DOE/ASCI (Accelerated Strategic Computing Init.)
– Simulations on massively parallel machines
– Emphasis on parallel I/O performance, functionality

• NCSA
– Grid, Vis, other R&D, user support

• Others
– Applications, support, some R&D
University of Illinois at Urbana-Champaign

-6-

HDF
HDF4
•
•
•
•

User support, tools, maintenance, QA
JHV (Java viewer) - two update releases
HDF4 dumper (hdp) - many improvements
Next HDF4 Release (Oct. 2000)
–
–
–
–

Bug fixes
Chunking for General Raster (GR) images
Unlimited dimensions for SDS
GIF <--> HDF4 conversion tools
University of Illinois at Urbana-Champaign

-7-

HDF
HDF4 Archiving
• New File Format and Specification Manual
–
–
–
–

Facilitate long term maintenance of HDF4
Necessary for bug fixing, adding new features
Decreases learning curve for new developers
Available soon in
• PDF, HTML and PS formats

University of Illinois at Urbana-Champaign

-8-

HDF
HDF5
University of Illinois at Urbana-Champaign

-9-

HDF
The growth of HDF5
• Users in 27 countries
• Users include
–
–
–
–

Government agencies
National labs
Companies
Universities

University of Illinois at Urbana-Champaign

- 10 -

HDF
The growth of HDF5
• Scientific fields
– Astronomy, astrophysics, aerospace engineering
– Geophysics, remote sensing, meteorology,
– Oceanography, environmental Science
– Informational Science
– Medical Research (brain, cancer, biotech)
– Product model data
University of Illinois at Urbana-Champaign

- 11 -

HDF
Facilitating interoperability
between HDF4 and HDF5
• HDF4 to HDF5 mapping specification
– “Mapping HDF4 Objects to HDF5 Objects”
• http://hdf.ncsa.uiuc.edu/HDF5/papers

– Rules for mapping high level HDF4 objects to HDF5
• How to describe HDF4 objects in HDF5
• How to interpret HDF5 objects as HDF4 objects

• HDF4-to-HDF5 conversion software (later)
• Space Research, Inc. Explorer 1.1
– reads both HDF4 and HDF5
University of Illinois at Urbana-Champaign

- 12 -

HDF
HDF5 Activities in 2000
•
•
•
•
•
•

HDF5 1.2.2 library release
Fortran 90 & C++ API
HDF5 Abstract Data Model
XML Document Type Definition (DTD)
HDF5 tools
Support for users and application
developers
• HDF5 Tutorial
• Searchable, printable documentation

University of Illinois at Urbana-Champaign

- 13 -

HDF
Tools & Utilities
• NCSA
–
–
–
–

Java wrapper for HDF5
H5View: Java browser/Editor for HDF5
H5gen: XML-to-HDF5 file generator (Java)
H5dump & H5ls

• Others
–
–
–
–

VisAD data adapter for HDF5 (Java toolkit)
HDF Inspector/Explorer
Open Data Explorer (IBM)
Ensight
University of Illinois at Urbana-Champaign

- 15 -

HDF
H5View

University of Illinois at Urbana-Champaign

- 16 -

HDF
H5View
• Java-based tool for browsing and editing
• Display structure of file
• Display content of objects
• Create and delete objects
• Modify values of objects and attributes
University of Illinois at Urbana-Champaign

- 17 -

HDF
HDF5 XML DTD
• A flexible standard language that can
describe an HDF5 file in precise detail
– Datasets, dataspaces, datatypes
– Groups and links, structure of the file
– Values of the attributes and data

•

http://hdf.ncsa.uiuc.edu/HDF5/XML
University of Illinois at Urbana-Champaign

- 18 -

HDF
H5Gen: XML HDF5
• Reads an XML description of an HDF5 file
• Generates the corresponding HDF5 file
• Validates XML description vs. HDF5 DTD

University of Illinois at Urbana-Champaign

- 19 -

HDF
Some uses of XML
Archive

XML
documentation
of metadata
& structure

XML to HDF5 (H5gen)
HDF5 to XML
Generate, validate,
reconstruct HDF5 files

Description
in XML using
HDF5 DTD

XML
to
HTML
Catalog
records
in XML

View
HDF5 files
using a web
browser

Data
location
services

XML to Java
Java to XML

HDF5
file
- 20 -

Java
viewers,editors,
University of Illinois at Urbana-Champaign
other tools

HDF
Focus areas for 2001
•
•
•
•
•
•

Support Terra & Aqua
Get ready for Aura
Support HDF-EOS 3
Enhance HDF5View
Refine XML DTD & design tools around it
HDF5 converters
– HDF5 XML
– HDF4-to-HDF5
– Others (e.g. GIF

HDF5)
University of Illinois at Urbana-Champaign

- 21 -

HDF
Focus areas for 2001
•
•
•
•
•
•
•
•

Expand list of applications and users
Facilitate access to other tools & software
Get vendors on board
Performance testing and tuning
Extend API with ease-of-use functions
Clusters and other new environments
Implement a thread-safe version
HDF5 advanced tutorial
University of Illinois at Urbana-Champaign

- 22 -

HDF
Thank you!
HDF • HDF website
– http://hdf.ncsa.uiuc.edu/

5 • HDF5 Information Center

– http://hdf.ncsa.uiuc.edu/HDF5/

• HDF Helpdesk
– hdfhelp@ncsa.uiuc.edu

• HDF users mailing list
– hdfnews@ncsa.uiuc.edu
University of Illinois at Urbana-Champaign

- 23 -

HDF

Mais conteúdo relacionado

Mais procurados

Aggregation of cultural heritage datasets through the Web of Data
Aggregation of cultural heritage datasets through the Web of DataAggregation of cultural heritage datasets through the Web of Data
Aggregation of cultural heritage datasets through the Web of Data
Nuno Freire
 
DataCite and its DOI infrastructure - IASSIST 2013
DataCite and its DOI infrastructure - IASSIST 2013DataCite and its DOI infrastructure - IASSIST 2013
DataCite and its DOI infrastructure - IASSIST 2013
Frauke Ziedorn
 
IASSIST 2012 - DDI-RDF - Trouble with Triples
IASSIST 2012 - DDI-RDF - Trouble with TriplesIASSIST 2012 - DDI-RDF - Trouble with Triples
IASSIST 2012 - DDI-RDF - Trouble with Triples
Dr.-Ing. Thomas Hartmann
 

Mais procurados (20)

Aggregation of cultural heritage datasets through the Web of Data
Aggregation of cultural heritage datasets through the Web of DataAggregation of cultural heritage datasets through the Web of Data
Aggregation of cultural heritage datasets through the Web of Data
 
5.15.17 Powering Linked Data and Hosted Solutions with Fedora Webinar Slides
5.15.17 Powering Linked Data and Hosted Solutions with Fedora Webinar Slides5.15.17 Powering Linked Data and Hosted Solutions with Fedora Webinar Slides
5.15.17 Powering Linked Data and Hosted Solutions with Fedora Webinar Slides
 
Who is doing what, and how do we know? [PEPRS]
Who is doing what, and how do we know? [PEPRS]Who is doing what, and how do we know? [PEPRS]
Who is doing what, and how do we know? [PEPRS]
 
DataCite and its DOI infrastructure - IASSIST 2013
DataCite and its DOI infrastructure - IASSIST 2013DataCite and its DOI infrastructure - IASSIST 2013
DataCite and its DOI infrastructure - IASSIST 2013
 
COMSODE networking session at ICT Lisbon 2015
COMSODE networking session at ICT Lisbon 2015COMSODE networking session at ICT Lisbon 2015
COMSODE networking session at ICT Lisbon 2015
 
Harvesting Repositories: DPLA, Europeana, & Other Case Studies
Harvesting Repositories:  DPLA, Europeana, & Other Case StudiesHarvesting Repositories:  DPLA, Europeana, & Other Case Studies
Harvesting Repositories: DPLA, Europeana, & Other Case Studies
 
Edinburgh DataShare – A DSpace Data Repository: Achievements and Aspirations
Edinburgh DataShare – A DSpace Data Repository: Achievements and Aspirations Edinburgh DataShare – A DSpace Data Repository: Achievements and Aspirations
Edinburgh DataShare – A DSpace Data Repository: Achievements and Aspirations
 
Digital Preservation in Production (DPN and DuraCloud Vault)
Digital Preservation in Production (DPN and DuraCloud Vault)Digital Preservation in Production (DPN and DuraCloud Vault)
Digital Preservation in Production (DPN and DuraCloud Vault)
 
Requirements for Open Sharing of Archaeological Research Data
Requirements for Open Sharing of Archaeological Research DataRequirements for Open Sharing of Archaeological Research Data
Requirements for Open Sharing of Archaeological Research Data
 
Metadata Working Group - Status update
Metadata Working Group -Status updateMetadata Working Group -Status update
Metadata Working Group - Status update
 
ESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge GraphsESWC 2017 Tutorial Knowledge Graphs
ESWC 2017 Tutorial Knowledge Graphs
 
TIB's action for research data managament as a national library's strategy in...
TIB's action for research data managament as a national library's strategy in...TIB's action for research data managament as a national library's strategy in...
TIB's action for research data managament as a national library's strategy in...
 
Open Data Publication - Requirements, Good practices, and Benefits
Open Data Publication - Requirements, Good practices, and BenefitsOpen Data Publication - Requirements, Good practices, and Benefits
Open Data Publication - Requirements, Good practices, and Benefits
 
IASSIST 2012 - DDI-RDF - Trouble with Triples
IASSIST 2012 - DDI-RDF - Trouble with TriplesIASSIST 2012 - DDI-RDF - Trouble with Triples
IASSIST 2012 - DDI-RDF - Trouble with Triples
 
Service Integration to Enhance RDM
Service Integration to Enhance RDMService Integration to Enhance RDM
Service Integration to Enhance RDM
 
The Information Workbench - Linked Data and Semantic Wikis in the Enterprise
The Information Workbench - Linked Data and Semantic Wikis in the EnterpriseThe Information Workbench - Linked Data and Semantic Wikis in the Enterprise
The Information Workbench - Linked Data and Semantic Wikis in the Enterprise
 
Data management planning – what it is and how to do it
Data management planning – what it is and how to do itData management planning – what it is and how to do it
Data management planning – what it is and how to do it
 
DSpace-CRIS Workshop OR2015: Slides
DSpace-CRIS Workshop OR2015: SlidesDSpace-CRIS Workshop OR2015: Slides
DSpace-CRIS Workshop OR2015: Slides
 
COBWEB: Brief Introduction, GBIF Secretariat
COBWEB: Brief Introduction, GBIF SecretariatCOBWEB: Brief Introduction, GBIF Secretariat
COBWEB: Brief Introduction, GBIF Secretariat
 
Digital Preservation at UNM Libraries
Digital Preservation at UNM LibrariesDigital Preservation at UNM Libraries
Digital Preservation at UNM Libraries
 

Semelhante a HDF Update

Improving long-term preservation of EOS data by independently mapping HDF4 da...
Improving long-term preservation of EOS data by independently mapping HDF4 da...Improving long-term preservation of EOS data by independently mapping HDF4 da...
Improving long-term preservation of EOS data by independently mapping HDF4 da...
The HDF-EOS Tools and Information Center
 

Semelhante a HDF Update (20)

HDF
HDFHDF
HDF
 
HDF
HDFHDF
HDF
 
HDF5 and The HDF Group
HDF5 and The HDF GroupHDF5 and The HDF Group
HDF5 and The HDF Group
 
HDF Update
HDF UpdateHDF Update
HDF Update
 
HDF Update
HDF UpdateHDF Update
HDF Update
 
HDF Update
HDF UpdateHDF Update
HDF Update
 
HDF Updae
HDF UpdaeHDF Updae
HDF Updae
 
HDF Software Process - Lessons Learned & Success Factors
HDF Software Process - Lessons Learned & Success FactorsHDF Software Process - Lessons Learned & Success Factors
HDF Software Process - Lessons Learned & Success Factors
 
HDF Update
HDF UpdateHDF Update
HDF Update
 
HDF and Augmentation
HDF and Augmentation HDF and Augmentation
HDF and Augmentation
 
Transitioning from HDF4 to HDF5
Transitioning from HDF4 to HDF5Transitioning from HDF4 to HDF5
Transitioning from HDF4 to HDF5
 
Transitions from HDF4 to HDF5: Issues
Transitions from HDF4 to HDF5: IssuesTransitions from HDF4 to HDF5: Issues
Transitions from HDF4 to HDF5: Issues
 
HDF Status and Development
HDF Status and DevelopmentHDF Status and Development
HDF Status and Development
 
Improving long-term preservation of EOS data by independently mapping HDF4 da...
Improving long-term preservation of EOS data by independently mapping HDF4 da...Improving long-term preservation of EOS data by independently mapping HDF4 da...
Improving long-term preservation of EOS data by independently mapping HDF4 da...
 
HDF Project Update
HDF Project UpdateHDF Project Update
HDF Project Update
 
HDF Product Designer
HDF Product DesignerHDF Product Designer
HDF Product Designer
 
Research data management: DMP & repository
Research data management: DMP & repositoryResearch data management: DMP & repository
Research data management: DMP & repository
 
HDF Studio
HDF StudioHDF Studio
HDF Studio
 
Steven McEachern - ADA, DDI (metadata standard) and the Data Lifecycle
Steven McEachern - ADA, DDI (metadata standard) and the Data LifecycleSteven McEachern - ADA, DDI (metadata standard) and the Data Lifecycle
Steven McEachern - ADA, DDI (metadata standard) and the Data Lifecycle
 
ADA, DDI and the data lifecycle - Steve McEachern - 7 April 2017
ADA, DDI and the data lifecycle - Steve McEachern - 7 April 2017ADA, DDI and the data lifecycle - Steve McEachern - 7 April 2017
ADA, DDI and the data lifecycle - Steve McEachern - 7 April 2017
 

Mais de The HDF-EOS Tools and Information Center

Mais de The HDF-EOS Tools and Information Center (20)

Cloud-Optimized HDF5 Files
Cloud-Optimized HDF5 FilesCloud-Optimized HDF5 Files
Cloud-Optimized HDF5 Files
 
Accessing HDF5 data in the cloud with HSDS
Accessing HDF5 data in the cloud with HSDSAccessing HDF5 data in the cloud with HSDS
Accessing HDF5 data in the cloud with HSDS
 
The State of HDF
The State of HDFThe State of HDF
The State of HDF
 
Highly Scalable Data Service (HSDS) Performance Features
Highly Scalable Data Service (HSDS) Performance FeaturesHighly Scalable Data Service (HSDS) Performance Features
Highly Scalable Data Service (HSDS) Performance Features
 
Creating Cloud-Optimized HDF5 Files
Creating Cloud-Optimized HDF5 FilesCreating Cloud-Optimized HDF5 Files
Creating Cloud-Optimized HDF5 Files
 
HDF5 OPeNDAP Handler Updates, and Performance Discussion
HDF5 OPeNDAP Handler Updates, and Performance DiscussionHDF5 OPeNDAP Handler Updates, and Performance Discussion
HDF5 OPeNDAP Handler Updates, and Performance Discussion
 
Hyrax: Serving Data from S3
Hyrax: Serving Data from S3Hyrax: Serving Data from S3
Hyrax: Serving Data from S3
 
Accessing Cloud Data and Services Using EDL, Pydap, MATLAB
Accessing Cloud Data and Services Using EDL, Pydap, MATLABAccessing Cloud Data and Services Using EDL, Pydap, MATLAB
Accessing Cloud Data and Services Using EDL, Pydap, MATLAB
 
HDF - Current status and Future Directions
HDF - Current status and Future DirectionsHDF - Current status and Future Directions
HDF - Current status and Future Directions
 
HDFEOS.org User Analsys, Updates, and Future
HDFEOS.org User Analsys, Updates, and FutureHDFEOS.org User Analsys, Updates, and Future
HDFEOS.org User Analsys, Updates, and Future
 
HDF - Current status and Future Directions
HDF - Current status and Future Directions HDF - Current status and Future Directions
HDF - Current status and Future Directions
 
H5Coro: The Cloud-Optimized Read-Only Library
H5Coro: The Cloud-Optimized Read-Only LibraryH5Coro: The Cloud-Optimized Read-Only Library
H5Coro: The Cloud-Optimized Read-Only Library
 
MATLAB Modernization on HDF5 1.10
MATLAB Modernization on HDF5 1.10MATLAB Modernization on HDF5 1.10
MATLAB Modernization on HDF5 1.10
 
HDF for the Cloud - Serverless HDF
HDF for the Cloud - Serverless HDFHDF for the Cloud - Serverless HDF
HDF for the Cloud - Serverless HDF
 
HDF5 <-> Zarr
HDF5 <-> ZarrHDF5 <-> Zarr
HDF5 <-> Zarr
 
HDF for the Cloud - New HDF Server Features
HDF for the Cloud - New HDF Server FeaturesHDF for the Cloud - New HDF Server Features
HDF for the Cloud - New HDF Server Features
 
Apache Drill and Unidata THREDDS Data Server for NASA HDF-EOS on S3
Apache Drill and Unidata THREDDS Data Server for NASA HDF-EOS on S3Apache Drill and Unidata THREDDS Data Server for NASA HDF-EOS on S3
Apache Drill and Unidata THREDDS Data Server for NASA HDF-EOS on S3
 
STARE-PODS: A Versatile Data Store Leveraging the HDF Virtual Object Layer fo...
STARE-PODS: A Versatile Data Store Leveraging the HDF Virtual Object Layer fo...STARE-PODS: A Versatile Data Store Leveraging the HDF Virtual Object Layer fo...
STARE-PODS: A Versatile Data Store Leveraging the HDF Virtual Object Layer fo...
 
HDF5 and Ecosystem: What Is New?
HDF5 and Ecosystem: What Is New?HDF5 and Ecosystem: What Is New?
HDF5 and Ecosystem: What Is New?
 
HDF5 Roadmap 2019-2020
HDF5 Roadmap 2019-2020HDF5 Roadmap 2019-2020
HDF5 Roadmap 2019-2020
 

Último

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Victor Rentea
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Victor Rentea
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Último (20)

Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUKSpring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 

HDF Update

  • 1. HDF Update Mike Folk HDF-EOS Workshop IV Sept. 19-21, 2000 University of Illinois at Urbana-Champaign -1- HDF
  • 2. Topics • What is HDF? • HDF community • HDF4 – past and future work • HDF5 – – – – HDF5-HDF5 interoperability Activities and growth Tools and utilities Focus for 2001 University of Illinois at Urbana-Champaign -2- HDF
  • 3. NCSA HDF Mission To develop, promote, deploy, and support open and free technologies that facilitate scientific data storage, exchange, access, analysis and discovery. University of Illinois at Urbana-Champaign -3- HDF
  • 4. What is HDF? • • • • • • Format and software for scientific data Stores images, arrays, tables, etc. Emphasis on storage and I/O efficiency Free and commercial software support Emphasis on standards Users from many engineering & scientific fields University of Illinois at Urbana-Champaign -4- HDF
  • 5. HDF People • NCSA – QA, maintanance & support – Library development & performance – Tools development • EOS & ASCI – Users, applications and tools – Performance • Volunteers from all over – Users, applications & tools University of Illinois at Urbana-Champaign -5- HDF
  • 6. Who is supporting HDF? • NASA/ESDIS – Earth science applications, instrument data – All aspects of data management • DOE/ASCI (Accelerated Strategic Computing Init.) – Simulations on massively parallel machines – Emphasis on parallel I/O performance, functionality • NCSA – Grid, Vis, other R&D, user support • Others – Applications, support, some R&D University of Illinois at Urbana-Champaign -6- HDF
  • 7. HDF4 • • • • User support, tools, maintenance, QA JHV (Java viewer) - two update releases HDF4 dumper (hdp) - many improvements Next HDF4 Release (Oct. 2000) – – – – Bug fixes Chunking for General Raster (GR) images Unlimited dimensions for SDS GIF <--> HDF4 conversion tools University of Illinois at Urbana-Champaign -7- HDF
  • 8. HDF4 Archiving • New File Format and Specification Manual – – – – Facilitate long term maintenance of HDF4 Necessary for bug fixing, adding new features Decreases learning curve for new developers Available soon in • PDF, HTML and PS formats University of Illinois at Urbana-Champaign -8- HDF
  • 9. HDF5 University of Illinois at Urbana-Champaign -9- HDF
  • 10. The growth of HDF5 • Users in 27 countries • Users include – – – – Government agencies National labs Companies Universities University of Illinois at Urbana-Champaign - 10 - HDF
  • 11. The growth of HDF5 • Scientific fields – Astronomy, astrophysics, aerospace engineering – Geophysics, remote sensing, meteorology, – Oceanography, environmental Science – Informational Science – Medical Research (brain, cancer, biotech) – Product model data University of Illinois at Urbana-Champaign - 11 - HDF
  • 12. Facilitating interoperability between HDF4 and HDF5 • HDF4 to HDF5 mapping specification – “Mapping HDF4 Objects to HDF5 Objects” • http://hdf.ncsa.uiuc.edu/HDF5/papers – Rules for mapping high level HDF4 objects to HDF5 • How to describe HDF4 objects in HDF5 • How to interpret HDF5 objects as HDF4 objects • HDF4-to-HDF5 conversion software (later) • Space Research, Inc. Explorer 1.1 – reads both HDF4 and HDF5 University of Illinois at Urbana-Champaign - 12 - HDF
  • 13. HDF5 Activities in 2000 • • • • • • HDF5 1.2.2 library release Fortran 90 & C++ API HDF5 Abstract Data Model XML Document Type Definition (DTD) HDF5 tools Support for users and application developers • HDF5 Tutorial • Searchable, printable documentation University of Illinois at Urbana-Champaign - 13 - HDF
  • 14. Tools & Utilities • NCSA – – – – Java wrapper for HDF5 H5View: Java browser/Editor for HDF5 H5gen: XML-to-HDF5 file generator (Java) H5dump & H5ls • Others – – – – VisAD data adapter for HDF5 (Java toolkit) HDF Inspector/Explorer Open Data Explorer (IBM) Ensight University of Illinois at Urbana-Champaign - 15 - HDF
  • 15. H5View University of Illinois at Urbana-Champaign - 16 - HDF
  • 16. H5View • Java-based tool for browsing and editing • Display structure of file • Display content of objects • Create and delete objects • Modify values of objects and attributes University of Illinois at Urbana-Champaign - 17 - HDF
  • 17. HDF5 XML DTD • A flexible standard language that can describe an HDF5 file in precise detail – Datasets, dataspaces, datatypes – Groups and links, structure of the file – Values of the attributes and data • http://hdf.ncsa.uiuc.edu/HDF5/XML University of Illinois at Urbana-Champaign - 18 - HDF
  • 18. H5Gen: XML HDF5 • Reads an XML description of an HDF5 file • Generates the corresponding HDF5 file • Validates XML description vs. HDF5 DTD University of Illinois at Urbana-Champaign - 19 - HDF
  • 19. Some uses of XML Archive XML documentation of metadata & structure XML to HDF5 (H5gen) HDF5 to XML Generate, validate, reconstruct HDF5 files Description in XML using HDF5 DTD XML to HTML Catalog records in XML View HDF5 files using a web browser Data location services XML to Java Java to XML HDF5 file - 20 - Java viewers,editors, University of Illinois at Urbana-Champaign other tools HDF
  • 20. Focus areas for 2001 • • • • • • Support Terra & Aqua Get ready for Aura Support HDF-EOS 3 Enhance HDF5View Refine XML DTD & design tools around it HDF5 converters – HDF5 XML – HDF4-to-HDF5 – Others (e.g. GIF HDF5) University of Illinois at Urbana-Champaign - 21 - HDF
  • 21. Focus areas for 2001 • • • • • • • • Expand list of applications and users Facilitate access to other tools & software Get vendors on board Performance testing and tuning Extend API with ease-of-use functions Clusters and other new environments Implement a thread-safe version HDF5 advanced tutorial University of Illinois at Urbana-Champaign - 22 - HDF
  • 22. Thank you! HDF • HDF website – http://hdf.ncsa.uiuc.edu/ 5 • HDF5 Information Center – http://hdf.ncsa.uiuc.edu/HDF5/ • HDF Helpdesk – hdfhelp@ncsa.uiuc.edu • HDF users mailing list – hdfnews@ncsa.uiuc.edu University of Illinois at Urbana-Champaign - 23 - HDF

Notas do Editor

  1. &amp;lt;number&amp;gt;
  2. Format and software for scientific data. HDF5 is a different format from earlier versions of HDF, as is the library. Stores images, multidimensional arrays, tables, etc. That is, you can construct all of these different kinds structures and store them in HDF5. You can also mix and match them in HDF5 files according to your needs. Emphasis on storage and I/O efficiency Both the library and the format are designed to address this. Free and commercial software support As far as HDF5 goes, this is just a goal now. There is commercial support for HDF4, but little if any for HDF5 at this time. We are working with vendors to change this. Emphasis on standards You can store data in HDF5 in a variety of ways, so we try to work with users to encourage them to organize HDF5 files in standard ways. Users from many engineering and scientific fields