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CDM & TDS Data Server: Earth & Ocean Sciences Meet GIS

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the machine learning that it does have some the new assigned to the case is so we would go on John that data and and use
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famous sort of for 3 within around about 25 year and still were probably unique within the NSF for being funded for engineering rather than research and that is lower famous for 1st following the real time data feet from the you as whether service and we should that off and to basically universities to a teaching meteorology graduate level causes and researchers who what real time data some of the real time but we have the whether Prediction models from the National and whether service model Sandra and and satellite data real time are data a lot of when observations all that is data that the National Weather Service use in their own for cast of has made in the given as defeat in which he Adaptive to qualify organisations we also supported visualization packages and jam packed in my tightest are are old school utilization Pratt at a packet that used widely in where the prediction community and I'd the integrated data viewers are community data on a which to is the National Weather Service and visualization and were were working with that seeing if we can use it to provide a safe to support to are to are community and the 3rd thing were famous for the Nets city a file for match which is basically a serialisation arrest storage for match kind of state for trade and 77 you get the data model just multi-dimensional race but we added these are a tricky value Metadata which turned out to be a really good idea and them and we do it and I know Machine Independent from independent and way so it's part of all across all kinds locked up for this is a big event in 96 widely used in sight to be data particular climate data that the eyepieces for for example puts all their data to do the model in a comparisons for that for the big climate change and size or a five year so
at this project started by deciding to job implementation for reading writing at city of files and then we added the Open de protocol to allow a remote access I data on somewhere else and read from where you client is this was also the very big events in the brand new 2 thousand leasing are community to not have to have files local to their machine at some point we realise it was really important all this was the Epi icily that a single each year in which you can access the Nets I have an open that files more less transparently and and so we started to add at the files for mad and we ended up getting all file for that are where the odd are community and a lot of other to and that includes the each year 5 family and that the the great grid and them is special for mapping in meteorology and the 0 some other specialise 1 women buffer from the W motivate 1 0 specialized memory As seen before the next red made are for maths other kinds of greater for men satellite data published miscellaneous data
and after we not after a while we were doing that we built basically an abstract data model by combining the 2 models between at City of opened up in each of 5 and see this as this is the sort of state data my was a really important way to think about how you do works and everybody does that they just may be don't realise the during and the created after data model the The the write down of the don't write down and so spread around them when we think about what an abstract data model is as well to the piano and the Piazza by India that data model to the city from language so once you've abstracted to data my and and start wording at the the date of the pro other languages so this data model became the basis for a on excursion that City for which is a file for mad that we build on top of each year 5 5 from a gave us a lot and capabilities and so I used the word Seaham libraries sometimes and as a synonym for the Nets who of Java library because when unity of job I think that's something from the city but in fact it's were what we really need the at a bill that Trinity ophiolite really is the Nexia 8 idea extended at Apia on top of local budget different file for me and this library this I am libraries used in last job applications Pugh job so
that it does to the trades data server in which the stadium libraries 1 of the key components and here we got a number of data services that people can access data this is the ideal I data feed and mention that before its that the real time data coming from such a from the way the service and we British real time we put on silly survey up 3 days server uses through a container also it will be about catalogues may be and you can figure staff with the Configure alive that the data server what to say about the user sees client version of that and that tells a much would what's available on the server
An important thing that we recognise eventually was that are are older technology which Nazi of each ideas and older technology and opened Abbas another 1 that's all index Baystate access so I'm so here is here is an example you out in which a getting some data from from opened at kind and use index based a year you based this lighting in subsidies multi-dimensional array of the new better thing to do is to working in in order to space and for example though GCSE W S CIA's Protocols working Kaunas space so the user doesn't have to understand the political caught Stacey and say what he wants the server knows what that means and served out the set said that he wants and and so that's important
and another way to say the same thing as when you have a sad day if out when I got in that file at the lowest level you that a bag of fights and conservative key period to keep he and if you think of it throughout city effort or opened up which he that is a collection of multi-dimensional array is in the file and then the 3rd level the the best level to use it is when you imagine that when you really got is a collection of objects in the file and you can sense that those objects and important space to give me that set profiles which are in the founding by saying over Great Britain something so here they are
Katisha for this year and is all the difference file for match and there we call this a plugin rocketed restricted the Blue things that place where you can plug in your own third party component what that means that you can play the game as it means that you can write your own software's and work with the system without touching are and is set to understand the players are in the new can drop in works so busy architecture at the lowest level we can access all these all this early is different kinds of data and make it available to the next of which Shiite that the data access at the next level we need in order to another in order
to do that do the corridors system and access we need to build up order system so we need to understand what the jurors order systems are designed to be data so there is a layer in which there was something which understands the and if we don't have had if we can understand your data you can plug in your own Caudan system builders and that you have an idea object was about coronet systems and at the top we then turned into objects of which we coffee to types more lessons analogy to the GCSE feature tight and are particular abstract model so that's the general and South detective that 3 different places you can talk to you data through 3 different essentially that build on top of each other a Case of
threads status server its applaudable Waquet texture uses spring 3 Quinnell annotations which means that again you can drop in your Web services that below that use this use this framework without having to get commission from us to change a code or in French Dakota for because I'm inseam as also got this component mentioned he's Kaunas system builders for order transforms beaches and this is a new thing that we've been were slowly moving to this this job real service provider means used illuminated the new job got the job file inside the Waugh and in the class Lhota finds your finds it components and automatic loads of so
opulent job with downloadable were filed on the uses of this sort of the main components of the server that they might be different than you might expect so we gritty says culprit these catalogues which it is documents and and also you there may be a 1st time and this is the list of the datasets and the and points it's not data it's not a search of search inquiry facility it's really just the were are the that describes what's on the server intended to be interested in the search engines which which number search engines have been including she'll caudle and it's a place to add to your catalogue basically to help the search for help Search find datasets then we created and we have a number of Web services and and into the standard services or go with the news that specialises in we specialise in these candidate of files so I'm 1 important thing about bird science datafiles that they don't look like to the G data they allways time they often have vertical coronets the most complicating we've done the 6th dimensional for cast models lies numerical for Catherine like every 6 hours every 3 hours even every 1 hour and they have 4 cast dimensions you get to time dimensions that Runtime that before the model was right and that the forecast the hour at which is run out to to see 3 space to time and sometimes deal 7 ensemble dimensions have more they have a 6 dimensional dataset and that doesn't fit into traditional G there often real time and there for changing and or change in real time means a change real time this means it is disconsolate coming and changing just means at every so often you might get an update on and this happens a lot in real and but data and 1 of the decisions we made long though is that we work is a database of some of what you use a database and a guest 1 answer is lower doing what you can do without a database of needed database great that's assault from for working with turbines sometimes Petabytes of scientific data in which put even databases not options so what can you do in the case that such a threat the for doing the best we can do without it and the other thing that allows you to do is modified had Metadata using an instant using and similar to that in the sector and it led to create a virtual the virtual datasets from collections of files this is where the spending my views on here is an
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drill down into the city case that you see the various Metadata that you presumably added to and that in this case that all but 2 Defra points possible ways of accessing that said the W system W mess there somewhere
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usually have and Web services and you can do a cheeky file transfer mean you can just see the date as a bag of fights and transferred your machine you can use open Dax opened apt to get index level access and where your basically setting multi-dimensional race we created this thing a subset services in which can do coronet level accessing get back at city of files and a bunch other for to arrest him the site simple as possible rest 8 p eye for doing that stuff and then we've got the standards that the mass and the CIA and the mass was created by John Oradea University ready and and it said it that yesterday's these 3 ones are all third party plugins here on which we were ordered Debussy server and it's still back on 1 point at 1 time and the reasons because occupancy use a match without a lot of pressure unrelated on time this is a brand new 1 as a way of prototype or opened include the and it also has made a data services are usually the 1st catalogues it's also got a service that was written by 1 of the 3rd party in which it basically publishes the Metadata and that that published Exum ommatidia can get sucked into certain history systems a Case
said under show a few the unique things about the threat status server the when you work with side to the data you have a hot problem so here as is a couple of technology developed his also most from and and see Melott is just Nexen or a precipitation the Metadate inside in this city of file but the cool thing about it is that you can essentially rap existing files and fix Metadata that you need before back to put them some important information or you you you can change the military in the file that rewriting the file and and you can bet and seem of directly and the tedious Cadillac so the TVs will serve that view that file out as if you had re written the data and the kind as a but and seamount here is is demands
Imelda fixes Texas and data so you got a file there is the name of the file and a you decided that he won at the at tribute and you want to remove your password from and here is a very loyal has a where names given the name and he added and unit to hear added and after being called units which correctly says and to serve as an example of changing in adding modifying the Metadata inside of existing file and and
an example of the changing something about using and female inside TVs so that datasets can point to a certain location scams all the data and old subdirectories in the so of this just as it took every file that was in the year and added this activity which is this particular 1 is actually useful of so that this is a funny storey that to go on tour and never put away to manage your data sermon out to users and fix things without to without having to re read the data
lasting a macho use just and and the new features that we've added in the last year so this is this is saying this is a piece that you could also put into grids configuration catalogue in this particular 1 said take a Case this is the finding abatacept his and meditative for that it is that it's giving it a you are Elvis's out at the deal that the uses will see that and it said that it's a great 1 but this is good when data the although the services that find the but much here all the service name also adds up probably a list of polyptychs the wanted and and documentation to but this year is the year where powerful so I'm tape In this directory although subdirectories and and then applied this regular expression of files and and that's been the Micheletti and and the Rolex collection of this in this case grid records and through into a bag and figure out what the multi-dimensional how to build it into a multi-dimensional nets seediest like things and this is this is a hot thing to do where and and its pre were trying to what were trying to scale deceptive very large collections and which allowed people are very large collections of things like the files and and the end this line says and because it's the changing said when you start at the way he started the TVs Galinsky and lessons and building this thing and then at 3 with this as but something like that at 3 in the morning going going ResCap and build again because maybe changed Group animals to allow the user to send me a trip to tell when changed so this handles changing datasets this is a way to elegantly describe a large collection of data trade into a virtual that the and we begin at are Metadata to yet thanks
acadians summary we have a surfer meteorological an ocean data and it's really a backhand components for lodges system it's not a polished his data caudle things really intended be back and is used a lot in large data centres in the West End in around your and it's essentially data translated as subset by the data says the native for Matt were not stopping at into a database and were word scaling working on Scalia large collection which causes continuing problems to new in work and the sauce is indeed have we have she tracking injured we do annual trainee workshops and community supported the no answer with houses for committee will help answer and we have sought to and and we use it to make the idea datastream available mean that we need a dog food which cost just means that you use the stuff that you produced to see if it actually work and within a clip on the answers to some examples but maybe we should just the launch by the
way were hiring the wants to move to pulled a Colorado them I know it's a bit them their yesterday made on the driveway and the but and it's a great place to live here but if you like bicyclists Arandas some but like so you can mix of 2 0 2 2 4 4 4 3 or where to you go
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Metadaten

Formale Metadaten

Titel CDM & TDS Data Server: Earth & Ocean Sciences Meet GIS
Serientitel FOSS4G Nottingham 2013
Autor Caron, John (Unidata/UCAR)
Davis, Ethan (Unidata),
Madry, Lansing (Unidata)
Lizenz CC-Namensnennung - keine kommerzielle Nutzung - Weitergabe unter gleichen Bedingungen 3.0 Unported:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen und nicht-kommerziellen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben
DOI 10.5446/15518
Herausgeber FOSS4G, Open Source Geospatial Foundation (OSGeo)
Erscheinungsjahr 2013
Sprache Englisch
Produktionsort Nottingham

Inhaltliche Metadaten

Fachgebiet Informatik
Abstract Different geoscience disciplines have developed sophisticated domain-specific cyber infrastructures for data storage, manipulation, and visualization. NetCDF, HDF, and GRIB are multi-dimensional array-based data formats widely used in meteorology and oceanography. However, these formats are not fully compatible with the visualization and manipulation tools supported by Geographic Information Systems (GIS), which caters to the discrete vector features and 2D raster formats commonly used in the geography, hydrology, and cartography. By providing a higher level of abstraction and enabling spatial, rather than indexed, data access, the Unidata Common Data Model (CDM) facilitates integration of NetCDF, HDF, and GRIB data into GIS tools, fostering interdisciplinary communication. The THREDDS Data Server (TDS) utilizes the CDM to work efficiently with large, dynamic collections of observational and model data. The TDS organizes these collections into unified, logical datasets, simplifying their access and dissemination. TDS datasets are exposed via the WMS and WCS Open Geospatial Consortium specifications, with support for time and elevation standard dimensions. Alternatively, TDS datasets are accessible through specialized web services that provide subsetting capabilities. The NetCDF Subset Service allows for spatial subsetting, while OpenDAP subsets by index. Finally, metadata discovery systems such as Geoportal and GI-CAT harvest TDS catalog metadata. The TDS ncISO service also serves catalog metadata directly as ISO documents, enabling text searches and exposing a CSW interface on TDS instances through these discovery systems. The CDM & TDS are OpenSource projects (https://github.com/Unidata/thredds) with strong community support. Members have contributed key features, including the ncISO and WMS implementations. Moreover, many interdisciplinary Web-GIS applications have already been successfully developed combining TDS web services with resources from other spatial data infrastructures. Coupled with Unidata's governing committees, the projects provide a unique framework that establishes quality standards and ensures that development meets community needs

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