Difference between revisions of "Workshop Abstracts"
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Not all pressentors submitted an abstract. The order here is the order of presentation.
Not all pressentors submitted an abstract. The order here is the order of presentation.
===Customizing and Extending Hyrax===
===Customizing and Extending Hyrax===
Latest revision as of 00:19, 20 March 2007
Abstracts for the Winter 2007 OPeNDAP Developer's Workshop. Not all pressentors submitted an abstract. The order here is the order of presentation.
- 1 Customizing and Extending Hyrax
- 2 Harnessing the power of the Server 4 Back-End Server modular framework
- 3 Numerical Grid Computations with the OPeNDAP Back End Server(BES)
- 4 OPeNDAP Server 4 Back-End Server Authentication and Authorization
- 5 Software Development and Security at NOAA
- 6 The THREDDS Data Server and OPeNDAP security
- 7 BMRC's OPeNDAP data service, how far can it reach?
- 8 Using an RDF framework to carry metadata for datasets
- 9 SWEET-- an upper level ontology for Earth and Space Sciences
- 10 Data Access Protocol meets Python
- 11 The Matlab OPeNDAP GUI Suite
- 12 OPeNDAP: User Versus Programmatic Access
- 13 Poster: Enhancing Access to NASA Satellite Data OGC Web Services using OPeNDAP.
- 14 OPeNDAP at ERD with suggestions for future development
- 15 IPRC data transport, LAS and EPIC server
- 16 OPeNDAP Developments at the Goddard Earth Sciences DISC
- 17 OPeNDAP in European oceanography data management
- 18 The ROSES ACCESS OPeNDAP/OGC Gateway Project
- 19 Server-side OPeNDAP Analysis - A General Approach Utilizing Legacy Applications through TDS
- 20 Server-side Data Reduction and Analysis with Script Workflow Analysis for MultiProcessing (SWAMP)
- 21 Server side Functions for Geo-spatial Selection
- 22 Dap4cor -- A Dapper-like server for CORIOLIS in-situ data centre
- 23 Managing large in-situ datasets with Dapper
1 Customizing and Extending Hyrax
James Gallagher and Nathan Potter
The OPeNDAP 4 Data Server, Hyrax, can be extended in several different ways. First, because the server is composed of two interacting processes, either of those can be replaced with components which provide new functionality. In addition, both the front-end process, named 'OLFS', and the back-end server, named 'BES', can be extended by writing handlers. These handlers can be used to perform many different tasks. For example, reading a new file type or building a gateway to another data system could be accomplished by writing a new handler for the BES. A new network protocol could be supported by writing a new handler for the OLFS. In this presentation, both will be covered, with an emphasis on the OLFS.
2 Harnessing the power of the Server 4 Back-End Server modular framework
The design and development of the OPeNDAP Back-End Server (BES) of Server 4 was driven by two different projects whose data infrastructure is implemented as a multi-tier client-server architecture. The first project being Earth System Grid (ESG) and the second project being the Coupling, Energetics and Dynamics of Atmospheric Regions (CEDAR). Within these two projects we required a framework that was extensible and flexible, allowing us to add new types of data responses, having the server handle multiple types of data (netCDF and FITS for example), being able to aggregate the data using different aggregation methods, reporting on data access for metrics purposes, providing authentication and/or authorization for data access, and more. This led us to the development of the BES. In order to demonstrate the full capabilities of the BES, how it fits in the revised Server 4 architecture and how it differs from earlier releases of OPeNDAP servers, we present here the Hello World module.
3 Numerical Grid Computations with the OPeNDAP Back End Server(BES)
Jose H. Garcia
OPeNDAP Server 4 architecture provides an extensibility mechanism known as OPeNDAP modules, which can be designed to serve data or to do server side processing. This coupled with the powerful Back End Server (BES) and the light and independent front end allows the design of new systems that extends the realm of OPeNDAP functionality. In specific, the Community Spectro-polarimeter Analysis Center (CSAC) projects presents a very intense computational problem of the type known as scatter-gather. We have developed a computer grid for the CSAC project that involves the use of multiple OPeNDAP servers across 20 processors with a light front end system designed to scatter the problem and to gather the individual solutions. We present the complete module development as well as the architecture currently servicing CSAC.
4 OPeNDAP Server 4 Back-End Server Authentication and Authorization
The Coupling, Energetics and Dynamics of Atmospheric Regions (CEDAR) and the Earth System Grid (ESG) projects rely on OPeNDAP Back-End Server (BES) for the purpose of data distribution. Each of these systems requires different forms of authentication and authorization. To facilitate these different requirements, as presented in use-cases for each of the systems, we have enhanced the modular design of the BES by including security for establishing connections. In order to achieve this, we have combined the Point to Point Transfer (PPT) protocol used by the BES with the Secure Socket Layer (SSL) handshake protocol. The design, implementation and resulting architectures are presented.
5 Software Development and Security at NOAA
John Relph and Kenneth S. Casey
While seeking to tap into the ever-growing capabilities of community-developed applications like OPeNDAP's Server4 and the THREDDS Data Server, NOAA must also meet its responsibilities for strict standards of IT security. NOAA IT security policies related to the development and deployment of applications on NOAA web sites will be presented and discussed. Hopefully, a clearer understanding of the requirements will eventually result in broader and more rapid deployment of these technologies at NOAA and an enhanced ability to meet the needs of the user communities.
6 The THREDDS Data Server and OPeNDAP security
Unidata is implementing "restricted access" to TDS datasets served through OPeNDAP. Our design goal is to make configuration easy for the simple case, and also to allow anyone to plug in their own code into the TDS to do whatever they need. We will present use cases and their HTTP message exchanges, and try to charactorize their tradeoffs on the server and client.
7 BMRC's OPeNDAP data service, how far can it reach?
The Australian Bureau of Meteorology Research Centre (BMRC) has identified OPeNDAP technology as a key component to its external data services for research users and in support of the international GODAE and Tsunami program.
The BMRC has built an external OPeNDAP service with limited storage and number of data sets. We have a vision to extent the OPeNDAP service to our large internal storage systems and operational data archives, as well as to integrate with WMO information systems and APAC data grids.
However, concerns over user authentication, data access privileges, and resource management must be addressed to provide a secure and robust environment for our computers and users, especially to be accepted as an operational resource in the future. How far can we allow OPeNDAP to reach into our operational systems?
8 Using an RDF framework to carry metadata for datasets
We have been using an RDF framework to gather and operate on dataset metadata. The goal is to interoperate between metadata conventions that are attached to data as they travel in different formats, as well as translating the metadata to match search schema and concepts.
In particular, we will show how one might connect OPeNDAP/netCDF data with CF convention metadata to MMI, SWEET, and IRI's conceptual ontologies and how those ontologies can be used for finding data. A similar mechanism facilitates translation between alternate metadata conventions.
We hope this example will provide some insight into how OPeNDAP might transport semantics with the same flexibility that it transports numerical data.
9 SWEET-- an upper level ontology for Earth and Space Sciences
10 Data Access Protocol meets Python
Roberto De Almeida
Pydap is an implementation of the Data Access Protocol (DAP) written from scratch in the Python programming language and based on the latest DAP 2 draft specification. The module comes with a DAP client with support for authentication and caching, allowing Python programs and scripts to access any DAP-served dataset through array-like objects. It also comes with a modular DAP server that runs in a variety of environments and that can be easily extended to support different data formats and new response types.
In this talk I will present a short introduction of how to install, deploy and use pydap both as a client and as a server, covering typical usage cases. I also plan to show examples of how pydap can be extended, focusing on the existing Web Map Service (WMS) and Google Earth interfaces.
11 The Matlab OPeNDAP GUI Suite
This presentation summarizes a set of Matlab GUIs that is being developed for satellite-derived surface ocean properties. The surface properties are divided into 5 groups: sea surface temperature, vector winds and wind stress, sea surface height, precipitation and ocean color. In addition a GUI has been developed for HYCOM data of the North Atlantic. The GUIs all have the same look and feel and all return variables in similar structures. A set of functions has been developed that can be used for basic operations on the returned structures. The GUIs are all available on the download page of the OPeNDAP web site under "Matlab Toolbox". These GUIs all call a low level function that generates the OPeNDAP URL, acquires the data and restructures them on return to render them in a form that is consistent for all of the GUIs in the set. This function can be called from scripts as well; i.e., the data may also be acquired and restructured without human intervention.
In addition, PMEL has developed a Matlab GUI for in situ data. I assume that they will discuss their system separately.
12 OPeNDAP: User Versus Programmatic Access
13 Poster: Enhancing Access to NASA Satellite Data OGC Web Services using OPeNDAP.
In order to facilitate the remote access to geographically distributed data sources and tools, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is developing standards-based, Open Geospatial Consortium (OGC) Web Services, e.g., Web Map Service (WMS) for selected data sets that it archives. These services, which give alternative ways to acquire and explore remotely sensed data, offer a practical, cost-effective solution for integrating information distributed among user systems. Spatial-temporal data queries are sent directly to the OGC-compliant servers, the requested Web Services are triggered using OPeNDAP to fetch the data, and the rendered data are directly served back to the clients on the fly. GES DISC OGC Web Services can be easily integrated into any OGC-compliant clients such as Google Earth. Current data sets served at the GES DISC through its WMS (as rendered maps or images) include Tropical Rainfall Measuring Mission (TR! MM) Gridded Rainfall (Near Real Time, V6) and Atmospheric Infrared Sounder (AIRS) Brightness Temperature. OPeNDAP allows WMS to be easily extended to serve other GES DISC data sets of interest to the public, to enhance the access to NASA satellite data.
14 OPeNDAP at ERD with suggestions for future development
ERD in colloboration with the West Coast node of Coastwatch is serving over 5Tb of data online and this amout is growing weekly. Just about all the data is accessible through OPeNDAP in some form, from gridded data through the NetCDF handler, aggregated gridded data through the TDS, in situ data through the OpeNDAP DRDS and through Dapper/Dchart and in-house some new servics using Pydap.
i will present a brief overview of how we are using OPeNDAP, and based on both our own experiences, as well as suggestions from user input, cover features/additions/extensions that we we feel are necessary for OPeNDAP to grow and gain wider acceptance.
15 IPRC data transport, LAS and EPIC server
The International Pacific Research Center (IPRC) at the University of Hawaii engages in climate research specific to the Asia-Pacific region. Within the IPRC, we maintain a data center for climate data. This data center, the Asia-Pacific Data-Research Center (APDRC), was originally established to provide the computational, data management, and networking infrastructure necessary to make data resources readily accessible and usable to researchers at the IPRC. We've since expanded this to include researchers outside the IPRC as well as more general users. In this presentation we will give an overview of our data server system that relies on OPeNDAP for data transport, LAS and EPIC for web-based data viewing. We have also employed various aggregation schemes to help serve remote data sets.
16 OPeNDAP Developments at the Goddard Earth Sciences DISC
The Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes Earth Sciences satellite data to the research community. Beyond that, we we also provide data services rnaging from simple subsetting up to complex server-side analysis workflows. Though the GES DISC has been deploying DODS / OPeNDAP servers since the turn of the century, recent developments within the GES DISC and EOSDIS at large have elevated the importance of OPeNDAP. For example, the GES DISC will be relying more on OPeNDAP as a key infrastructure component beneath the Giovanni analysis tool, and to support certain end-user communities. With increased reliance on OPeNDAP comes an increased dependance on improvements in performance, cataloguing, metrics reporting and customizability. Hopes are being pinned on the new Server 4 architecture to solve some of these issues, with collaborations and contributions among the community to aid the rest.
17 OPeNDAP in European oceanography data management
IFREMER is involved in distributed data management through many different European oceanography projects. These projects aim at setting up infrastructures for European ocean observation data management (Seadatanet, Cersat), at setting up core services for ocean monitoring and forecasting (Mersea) or fulfilling specific requirements for thematic usage (Interrisk, Humboldt : oil spill monitoring â¦). In these projects OPeNDAP is a de facto standard for data access in distributed systems. As examples we will review the effective and foreseen usages of the OPeNDAP protocol in the Seadatanet and Mersea projects.
The Seadatanet project (http://www.seadatanet.org) aims at setting up a pan-european network federating 48 marine data centres. In this project, OPeNDAP will be used :
- to define features (specific models) for the managed data types (vertical profiles, under track observations, ...)
- to access metadata and populate catalogues
- to access and visualize data.
In order to assess interoperability with equivalent networks, Seadatanet is very concerned in all OPeNDAP tentatives on marine in-situ observation conventions studies.
The Mersea project (http://www.mersea.eu.org) aims at setting up a virtual distributed ocean forecasting centre federating results from the main European operational observation and forecasting centres. In this distributed system, OPeNDAP (usually TDS servers) is used by every data providers for data dissemination. It is useful as a low level service used by more advanced services such as visualization. It is also planned to use OPeNDAP servers in order to build a distributed download service. This latest function has to implement access restriction and single sign on over the distributed servers. OPeNDAP is usually used as a B2B protocol (business to business) more than a B2C (business to client). To improve end-users access to the OPeNDAP data flow some initiatives are starting in the Mersea framework. A simple OPeNDAP client with a simple GUI assistant to build the request and save the data as netCDF files is now being developed. This latest software will enable the Mersea download service authentification.
18 The ROSES ACCESS OPeNDAP/OGC Gateway Project
This presentation will introduce the current status and future work of the ROSES ACCESS OPeNDAP/OGC gateway project. The gateway project addresses the interoperability of two data system infrastructures that are widely used by different segments of the Earth science research and applications community. The first are the systems and components that have been developed within the Earth science community to use a family of geoscience protocols, including OPeNDAP, netCDF/http, and the thematic Real-time Environmental Distributed Data Services (THREDDS) data catalog in accessing Earth science data collections. The second use the set of interface specifications developed by the Open Geospatial Consortium (OGC) to access geospatial data collections. The approach of this project is to develop a gateway that allows a user of a client component based on one of the infrastructures to have direct access to the collections of a data provider employing a server based on the ! other.
19 Server-side OPeNDAP Analysis - A General Approach Utilizing Legacy Applications through TDS
Roland Schweitzer, Ansley Manke and Steve Hankin
Within the OPeNDAP community the GrADS Data Server (GDS) was a pioneer [Wielgosz, 2003] in introducing server-side analysis capabilities. GDS server-side calculations have proven to be enormously popular because they permit data-intensive calculations (e.g. climatological averaging) to be performed on fast data resources local to the server greatly reducing the volume of traffic across the Internet. Within the Live Access Server (LAS) project we adopted the GDS code framework and URL syntax in the development of the Ferret Data Server (FDS) [Rogers, 2004]. Through this server LAS was able to guarantee a consistent geo-referenced and COARDS-standardized OPeNDAP access to the gridded data served by LAS.
In recent work we have ported the FDS functionality to the flexible framework that is available through the Unidata THREDDS Data Server. (We refer to the new server as F-TDS.) We developed a Ferret I/O Service Provider (IOSP) for the Java netCDF library. Ferret is a legacy, command-line analysis and graphics package that reads netCDF (COARDS and CF-1.0), ASCII and various binary file formats. Through Ferret directives (âcommandsâ) one can define new virtual variables which represent the result of some analysis operation applied to one or more of the data variables. By registering the Ferret IOSP with the THREDDS Data Server (TDS) a Ferret script which reads netCDF data and defines virtual variables then becomes an OPeNDAP data set. All of the variables (the real and virtual variables) defined by the script are visible to OPeNDAP clients â seamlessly through the netCDF API.
Much of the power of the netCDF API is that it allows applications to 'see' the full coordinate domain of a dataset, but to delay the reading of the data until the client specifies the precise subset of interest. A special character of Ferret is that it allows this approach (so-called 'delayed mode'?) to be applied to virtual variables. It performs the analysis calculations on-demand, only on the sub-set of the data requested.
The Ferret IOSP and THREDDS Data Server combination can also be used to enable on-the-fly server-side analysis. Data access information for multiple data sources and the Ferret commands to define virtual variable can be embedded into the OPeNDAP URL for this server. This information is parsed on the server; a new script is dropped into the scan area being monitored by TDS and the new data set with its virtual variables is immediately available via the TDS.
The techniques that we have employed are readily applicable for integrating broad classes of legacy applications (Ferret, GrADS, NCL, CDAT, Matlab, etc.) as OPeNDAP server-side computation engines. Other efforts such as SWAMP [Wang, 2007] demonstrate the community's interest in OPeNDAP server-side capabilities. We think it would be a good idea to develop a common syntax for communicating the underlying mathematics of the server-side functions. Having a common syntax would simplify the work for client writers and users who want to take advantage of server-side analysis available from GDS, the Ferret IOSP/TDS and other frameworks and servers. We would appreciate some suggestions, comments and volunteers toward nailing down a server-side analysis framework.
Joe Wielgosz, Brian Doty, The Grads-Dods Server: An Open-Source Tool For Distributed Data Access And Anaysis, 19th Conference on IIPS
Richard Rogers, Steve Hankin and Ansley Manke, The Ferret DODS Server, 20th Conference on IIPS
Daniel L. Wang, Univ. of California, Irvine, CA; and C. S. Zender and S. F. Jenks DAP-enabled Server-side Data Reduction and Analysis, 23rd Conference on IIPS
20 Server-side Data Reduction and Analysis with Script Workflow Analysis for MultiProcessing (SWAMP)
Daniel L. Wang
Despite the inexorable advance of faster, better, and cheaper computing hardware, terascale data reduction and analysis remain elusive for most. Massive amounts of netCDF data remain underutilized due to scientists' limited bandwidth and computational capacity. Our strategy relocates computation closer to data sources to minimize bandwidth usage and increase efficiency. We apply our server-side analysis framework, the Script Workflow Analysis for MultiProcessing (SWAMP) system to specify and perform computational workflows. Instead of running locally, scientists' netCDF Operator (NCO) data analysis scripts are processed and sent via Data Access Protocol (DAP) to a modified OPeNDAP server, where they are parsed, optimized, scheduled, and executed. Instead of receiving raw input data to be computed locally, scientists distribute computation and merely receive the reduced output data, while leveraging their legacy script-based analysis methods. Our benchmarks quantify the reduced bandwidth and improved execution time. Local computation and bandwidth requirements are drastically reduced, freeing the scientist to perform exploratory analysis and discovery in wider scopes and finer resolutions, and reducing time to discovery.
21 Server side Functions for Geo-spatial Selection
22 Dap4cor -- A Dapper-like server for CORIOLIS in-situ data centre
CORIOLIS is an operational global ocean in-situ data centre. As such, CORIOLIS collects, does quality assessment and disseminates datasets. The vertical profiles datasets are fully managed in an Oracle database. In order to answer operational data centres (mainly ocean forecasting centres) needs, CORIOLIS extracts on a regular basis many netCDF files from the database. The datasets are usually in a standard format (ARGO) but, depending on the users needs, the contents and update frequencies differ. The netCDF files are made available through an ftp server.
In order to avoid maintaining so many extraction scripts and replications of datasets in netCDF files and to improve the data center interoperability, we have decided to set up an OPeNDAP interface on the CORIOLIS database. For internal usage it centralizes the extraction facility, for external users it gives a standard interface for interactive or batch extraction.
After studying the DAPPER solution from PMEL, it has been decided to keep the DAP profile data model but to develop a specific implementation based on our Oracle database.
The server called DAP4COR is a web application running under tomcat. It is based on the java DAP 1.1.7 API. The most of work has been spent by, on one hand translating OPeNDAP requests criteria into SQL requests, on the other hand setting up a profile interface which reads the database tables and serializes into a DAP response.
For accessing the server, a pool of MATLAB scripts and a Dapper to netCDF conversion tool have been developed. The further developments will aim at improving the server delays of response and integrating, in addition to vertical profiles, moorings and trajectories data type (following the dapper observation data convention).
Server : http://www.ifremer.fr/dap4cor Documentation and tools : ftp://ftp.ifremer.fr/ifremer/coriolis/tools/dap4cor
23 Managing large in-situ datasets with Dapper
Joe Sirott Dapper is an OPeNDAP enabled Web server that provides access to millions of atmospheric and oceanographic observations. This talk discusses some of the real-world problems that occur when using the OPeNDAP protocol to serve large in-situ datasets and methods for overcoming some of these difficulties.