Bridging the gap between simulation and Gis
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Bridging the gap between simulation and Gis
Formal Metadata
Title 
Bridging the gap between simulation and Gis

Alternative Title 
Geospatial  Bridging Simulation Gis

Title of Series  
Author 

License 
CC Attribution 2.0 Belgium:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor. 
Identifiers 

Publisher 

Release Date 
2016

Language 
English

Production Year 
2015

Content Metadata
Subject Area 
00:00
NPhard
Multiplication sign
Materialization (paranormal)
Set (mathematics)
Water vapor
Parameter (computer programming)
Computer simulation
Mereology
Dimensional analysis
Information engineering
Triangulation (psychology)
Mathematics
Estimator
Different (Kate Ryan album)
Physical system
File format
Computer simulation
Bit
Open set
Connected space
Type theory
Arithmetic mean
Data management
Process (computing)
Bridging (networking)
Triangle
Summierbarkeit
Right angle
Freeware
Thermal conductivity
Resultant
Spacetime
Asynchronous Transfer Mode
Web page
Metre
Point (geometry)
Interpolation
Open source
Connectivity (graph theory)
Field (computer science)
Element (mathematics)
Population density
Data structure
Computing platform
Condition number
Task (computing)
Focus (optics)
Polygon mesh
Assembly language
Gender
Neighbourhood (graph theory)
Mathematical analysis
Cartesian coordinate system
Affine space
Approximation
Particle system
Word
Software
Personal digital assistant
Network topology
HTTP cookie
Musical ensemble
Local ring
06:33
Data management
Process (computing)
INTEGRAL
Planning
Water vapor
Computer simulation
Mereology
Coprocessor
Junction (traffic)
Physical system
07:02
Point (geometry)
User interface
Theory of relativity
State of matter
Computer simulation
Parameter (computer programming)
Instance (computer science)
Computer simulation
Power (physics)
Particle system
Type theory
Arithmetic mean
Process (computing)
Average
Stagnation point
Personal digital assistant
Pressure
Resultant
08:52
Context awareness
INTEGRAL
View (database)
Multiplication sign
Modal logic
Range (statistics)
Source code
Set (mathematics)
Propositional formula
Parameter (computer programming)
Computer simulation
Mereology
Information technology consulting
Formal language
Estimator
Mathematics
Sign (mathematics)
Bit rate
Different (Kate Ryan album)
Square number
Constraint (mathematics)
Theory of relativity
File format
Software developer
Structural load
Data storage device
Computer simulation
Sound effect
Bit
ACID
Instance (computer science)
Proof theory
Process (computing)
Summierbarkeit
Sinc function
Resultant
Asynchronous Transfer Mode
Point (geometry)
Link (knot theory)
Event horizon
Field (computer science)
Attribute grammar
Element (mathematics)
Centralizer and normalizer
Term (mathematics)
Internetworking
Googol
Selectivity (electronic)
Tunis
Computer architecture
Polygon mesh
Interface (computing)
Polygon
Graph (mathematics)
Mathematical analysis
Planning
Database
Basis <Mathematik>
Vector potential
Particle system
Vector field
Visualization (computer graphics)
Personal digital assistant
Network topology
Communications protocol
00:07
hi my name is Hugo miss CIA work for the Estonia and this talk was originally proposed by 1 of my colleagues of ensemble or but unfortunately couldn't come today so i'm gonna speak on his behalf an so we like to present you know how we try to bridge the gap between estimation and GIS so i'm gonna have to police about uh what's a kind of simulation we are interested in what kind of open source tools have for simulation engineers exists so far and what's are at what point are we now and what is missing and so what do we propose or what to do we how refocusing of so just so you song of the words about so a simulation of the kind of solution we are interesting so suppose you have some dynamic model of physical low and you want to unusually is modeled by use of a diet this differential equations and that depends on time and then on space and you want to solve its on particle all the main of interest and usually analytical solutions cannot be used either because they do not exist or not too hard to evaluate so the idea is to cut down the the global problem into smaller and simpler problems and so on on smaller subdomains communities and the means of space which are cold affinity amounts so we are focused on on this particular type of summation not all other types of summation but this covers lots of applications so this is an example of extracted extracted from the which the page so on the left and so suppose this is an approximation of the problem into the so let's say we have to kind of materials probably like conductivity wire on the rights and some minimal ferromagnets each of things and sharing between and we want to compute the magnetic field of this domain and so the 1st step would be to a 2 jets to partition the space into a of agreement 1 this is a triangulation and so in each 1 of these set of piecewise parts of the space you can then run and executes than a simpler problem and on the right you can then computes and visualize the results of this as a continuous field which is here minus so we so you have to match the protease you partition the space to to form a mesh and the you can and you have values that are attached to each node that can be scholarly you and each node has a specific connectivity is specific neighborhood and it showing in this case triangle often it element is used to interpolate values so in this point you have a value and that can be in wonderment dimension to deal with the on the more and just to be sure we understand so and this is where a representation of in its elements of where on each node you can have different gender values and sum and there is some some kind of interpolation values of in the and so the the the hard task of simulation is that there's lots of of questions on their own so How to discretize space is a is a is a hard question because in the sports guy example you can see that the density of the for English and is not the same everywhere because you have probably in the people running the those that surround this ferromagnetic thing than than the some uh much more things to to to visualize so this is 1 wrong problem how to interpolate values and is also a a problem but can be linear interpolation and a lots of all uh a kind of interpolation how to assemble local solution and of course which kind of parameters for the model to use cookies so this was the the summation of and we are going to focus on a particular case of this kind of situation in the field of GI is data so basically everything that is that's that is run at the state of of some meters or some kilometres and so where we have data wizard your references in its sold it's could be whether for forecast and I can see what condition management and so on and we found that there is already a lot of open source simulation tools components of open source information engines and models around lots of them and you can even find a mode used to simulate small generic things like a mechanical structure of the formation and so on but the problem is that this is this is some kind of from my books that were people focus on the computation parts and it's really likes a connection between this between GIS insulation and the the solution tools on a tree integrated into GIS software so what we already did that is to take all of this kind of model in an engine called upon it for the water management and integrated the interlinkages so why changes because it's generated so rights made sure it's extensible unlikely of as we use this was so just to today is with is a system of ligands and it's very powerful and we are thinking of about the the the processing Pollock's or where you it's kind of emitted from books where you can have lots of all the special analysis thing the 3 D is coming we are actively working on it and of course it's free and open source so our mission is to turn introduced into a assimilation platform so I'm gonna show you a little bit of once we done so far on this
06:33
it what's not and so this is g g so OK with some layers of the lead on on the left which represents a a a water management system with the pipes and junctions and so forth and so on and the what's we've gone is to integrates a planning to call simulation process so it's going balance and
06:56
it's part of the processing unit will books
07:03
so we can call you we regular here that the processing looks if we don't know this this looks it's it's very powerful it's kind of 2 looks after looks is so we can and only feature there is also to look at the presented this morning and lots of 4 . 2 boxes and In particular 1 of this is about it's planning where you can lounge this relation so the we just have to is to declare what's your opening what what's show which assimilation have the what is the parameters of simulation and its we generate automatically this user interface and then you can lounge this relation and get the results back we a bit of propose special postprocessing OK and many of you have some new kind of layers of will present the results of this relation and so this is in this case it's a 1 the simulation because you assimilate what's the inside pipes and you can see in red where basically all the problems of the problem of the pressure of stagnation and so on it Ramanujan averaging types of data are based on this Our results you cannot access to the yet to some internal states and therefore is instance what to the pressure on this particle of points of what is the meaning I think it's the the the history of pressure that biodiversity and
08:51
so so what what we have been able to do without this
08:55
to with introducing and in an something integrated to run the simulation tune selection parameters and his was the results and of course because it's in the case of a Q of GIS interface we we can make the link with although as data sources and processing is which is what we are interested in so our mission now is to continue to bridge the gap between these 2 worlds as so what about so you mentioned sets of so this mission this kind of solution MeSH concepts and of course we will try Willighagen to create a new and just you stand that's so we like to show how what's our Hall 1st felt about that so rather than a nation sets let's call it a vector field and the requirements would be something suitable for both simulation and GIS well think we that would be a real able to carry an arbitrary values on nodes the 1 D 2 D 3D uh it's it would not be just a soup of polygons but it would have a topology go constraints the way to store interpolation functions and so this is something that's has to be seen as GIS layers when needed when wanted special analysis and I the simulation mesh when you want to use it with the simulation engine the OK during the events so for instance the that just a proposition if we want to see the the vector fields in terms of GIS concepts we can say that's nodes can be represented by a point clear with some special attributes elements definite elements could be represented by a polygon layer which we have to connect these 2 layers nodes and and and and elements by some kind of topological constraints so maybe some triggers a database or something like this and we have to find a way to restore interpolation function somewhere so the overview of the architecture we're trying to to propose something like this where we have the central notion of vector field here and probably within a database something like but here is of special lights and some of the the the red squares here would be the HCI about 2 I think that interior about to request the time to modify to will find them another fall for instance changes to visualize this vector fields and to be able to read them and also to be able to tune the estimation parameters and also to cold the simulation engines that could be eventually at a remote so it's a I know about this submission will of course it's means that we have to model the the difference emission parameters domains Ivan Definition range In so that we can generate widgets for for the final users and this is something really are closely related to the process in the works of changes for the is just parts and editing um the idea would be to use the standouts editing mode of tutors for instance but with some postprocessing to ensure the topology constraints are respected and this could be used to to do some special analysis and for the misery parts and probably would start with something standouts that's we would need uh something light and emissions or graphic effects so many we have to introduce some kind of hope stack opened in the stack and about the simulation execution and I think in the 1st step could be just an executive all launched in red so it has to be sold so as a as as a protocol aware of the solution engine can be somewhere on the internet all of the mission so when it's use something like WP is for that and when we when we look at so a rating concepts that exists we we found that too 2 interesting things that the the the concept of topology that existing audience and in special lights house something very close but they all the some have probably to generate far as because they are generally graphs and we want to model the continuous fields so but that could be the basis for something better and there is also another point of view on the crayfish playing for changes that is made by and for consulting and they have implemented a vector field in introduce which is very interesting but unfortunately submit to specific to were through particle origin but it looks like this so you have that you can loads the results from from assimilation this is the the thing in blue and it's appears with a new kind of later on which is not a little delay on the 2 rustily or something in between which is implemented uh thanks to the planning layer the ability of candidates the but said it's too specific to this popular formats so the idea would be to have very these to to pave the way to have an so solutions to make the link between simulation engineers in all the able to store and you and visualize vector fields for simulation and to communicate with the simulation engines and that could be used to of course use existing models an engine like like it is as it is done with that of the processing to looks can conic preexisting as special to works and of course to it could be in a set of thinking I and protocols to develop new um simulation engines so we felt so that that's it would be interesting to to to share our proof of the lecture and so it's about about it because we are going to start to work on it we have done some the trace something already but we are going to continue on that so if you have ideas and remarks on that's what we're going to to discuss with you this and there's lots of potential had to use simulation models and inspected we think it's it lacks a bit of integration with the with the GS the thank thank you if the a you know that the language I the idea I I I I I I should no necessary times relation it's a on is it the and since all of the realtime simulation all longterm simulation because the creation um be I think it's a more longterm solution that's necessary realtime summation it commune shops value but not something sign in I