Workshop on design of scientific portals
KNMI, Netherlands, November 17th to 19th, 2014.
This meeting was organised jointly by the CLIPC and IS-ENES2 projects.
The programme (see below) involved presentations related to the architecture and design of portal(s) distributing scientific data and information related to climateclimate
Climate in a narrow sense is usually defined as the average weather, or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is 30 years, as defined by the World Meteorological Organization. The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system., particularly with regard to climate. These led to discussions and brainstorming of architectural choices and the role of different technologies. Participants of the meeting were technology developers and interested parties. Focus was on the integration of technologies into a service.
Presentations are available below via the download links behind the presentation.
| November 17th, 2pm to 6pm | |||
| Plenary session:1 Documentation | |||
| 14:00 | Welcome | Wim Som de Cerff, KNMI | |
| 14:05 | Overview: CLIPC objectives and approach | Martin Juckes, STFC | Download |
| 14:20 | CLIPC architecture sketch and intro to discussion | Wim Som de Cerff, KNMI | Download |
| 14:40 | ES-DOC | Mark Greenslade (remote) | Canceled |
| 15:00 | CHARMe | Stephen Pascoe, STFC | Download |
| 15:20-16:00 | Break | ||
| 16:00 | ESGFESGF The Earth System Grid Federation (ESGF) is an international collaboration with a current focus on serving the World Climate Research Programme (WCRP) Coupled Model Intercomparison Project (CMIP) and supporting climate and environmental science in general. The ESGF grew out of the larger Global Organization for Earth System Science Portals (GO-ESSP) community, and reflects a broad array of contributions from the collaborating partners. Search |
Stephen Pascoe, STFC | Download |
| 16:20 | Data Referencing and cataloguing | Martin Juckes, STFC | Download |
| 16:40 | Use of vocabularies in EMODnet and SeaDataNet | Peter Thijsse, MARIS | Download |
| 16:50 | Vocabulary services in EMODnet, SeaDataNet | Adam Leadbetter, BODC | Download |
| 17:10 | Discussion | ||
| November 18th: 9am to 5:30pm | |||
| Plenary session 2: Data access | |||
| 9:00 | MyOcean Data Access and portal | Thomas Loubrieu, IFREMER | Download |
| 9:20 | EMODNet/SeaDataNet | Peter Thijsse, MARIS | Download |
| 9:40 | Preparations for C3S | Baudouin Raoult, ECMWF | Download |
| 10:00 | ESGF & MARS | Prashanth Dwarakanath, LIU | Download |
| 10:20 | ESA ngEO | Garin Smith, Magellium | Download |
| 10:40 | Break | ||
| 11:00 | Climate4impact | Maarten Plieger, KNMI | Download |
| 11:20 | Visualising the robustness of climate changeclimate change Climate change refers to a change in the state of the climate that can be identified (e.g., by using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer. Climate change may be due to natural internal processes or external forcings such as modulations of the solar cycles, volcanic eruptions and persistent anthropogenic changes in the composition of the atmosphere or in land use. Note that the United Nations Framework Convention on Climate Change (UNFCCC), in its Article 1, defines climate change as: 'a change of climate which is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and which is in addition to natural climate variability observed over comparable time periods'. The UNFCCC thus makes a distinction between climate change attributable to human activities altering the atmospheric composition, and climate variability attributa info: The concept of climate signal maps. |
Juliane Otto, Climate Service Center 2.0 |
Download |
| 11:40 | The VERCE Science Gateway: Interactive seismic simulations across HPC clusters and federated data archives |
Alessandro Spinuso, KNMI | Download |
| 12:00 | The ECOMS User Data Gateway | Antonio S. Cofiño, Uni. Cantab | Download |
| 12:20 | Discussion | ||
| 12:30 | Lunch | ||
| Plenary session:3 Data quality control |
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| 14:00 | QC for climate model data | Heinz-Dieter Hollweg, DKRZDKRZ Deutsches Klimarechensentrum / German Climate Computing Centre |
Download |
| 14:20 | Compliance checking for archive data | Martin Juckes, STFC | Download |
| 14:40 | QA4ECV: a traceable quality assurance system for multi-decadal ECVs | A. De Rudder, IASB-BIRA | Download |
| 15:00 | Core-Climax | Jörg Schulz (EUMETSAT) | Download |
| 15:20 | Break | ||
| 15:50 | Transformations | ||
| 15:50 | MyOcean, Quality | Thomas Loubrieu, IFREMER | Download |
| 16:10 | A modular WPSWPS OGC Web Processing Service framework based on pyWPS |
Stephan Kindermann, DKRZ | Download |
| 16:30 | The CEDA WOS service | Eduardo Damasio da Costa, STFC | Download |
| 16:50 | Icclim/ocgis: a python library for calculating climate indices | Christian Pagé, CERFACS | Download |
| 17:10 | Close | ||
| November 19th, 9am to 12:30 | |||
| 9:00 | Plenary: review objectives of breakout groups | ||
| 9:30 | Breakout - Implementing WPS; also WCS, WCPS (SODA,) - Visualisation, including visualisation of uncertaintyuncertainty Lack of precision or unpredictability of the exact value at a given moment in time. It does not usually imply lack of knowledge. Often, the future state of a process may not be predictable, such as a roll with dice, but the probability of finding it in a certain state may be well known (the probability of rolling a six is 1/6, and flipping tails with a coin is 1/2). In climate science, the dice may be loaded, and we may refer to uncertainties even with perfect knowledge of the odds. Uncertainties can be modelled statistically in terms of pdfs, extreme value theory and stochastic time series models. - Knowledge base and metadatametadata Information about meteorological and climatological data concerning how and when they were measured, their quality, known problems and other characteristics. |
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Download |
| 11:00 | Coffee | ||
| 11:30 | Feedback and discussion | ||
| 12:30 | End of meeting | ||