Karlsruhe Institute of Technology (KIT)Institut of Computer Vision and Remote Sensing (IPF)Geodetic Institut (GIK)
multiGIWorkshop on
Multidimensional Geoinformationadvances in spatial information sciences towards modeling geo-processes
ORGANISED BYKarlsruhe Institute of Technologie (KIT)Prof. Dr.-Ing. habil. Stefan HinzDr.-Ing. Christian LucasInstitute of Computer Vision and Remote SensingEngler Str. 776128 Karlsruhe
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Programm MultiGI
14. Oktober 201014. Oktober 201014. Oktober 201014. Oktober 2010
time slot speaker moderator
10:00 - 12:00 registration
12:00 - 12:30 opening Prof. Breunig / Dr. Lucas Prof. Breunig / Dr. Lucas
12:30 - 13:30 keynote Prof. Frank
13:30 - 14:00 coffee-break*
14:00 - 18:30 with coffee-
break*
modeling of uncertain and fuzzy spatial information Prof. Pebesma Prof. Dransch
14:00 - 18:30 with coffee-
break*
potential of unstructured spatial information Prof. Freksa Prof. Habel
14:00 - 18:30 with coffee-
break*
temporal aspects of spatial information Prof. Breunig Prof. Zipf
20:00 - ... get together
15. Oktober 201015. Oktober 201015. Oktober 201015. Oktober 2010
08:00 - 12:00with coffee-
break*
ontologies for spatial information Prof. Kuhn
08:00 - 12:00with coffee-
break*Computational Challenges in GIScience Prof. Egenhofer Dr. Abecker
08:00 - 12:00with coffee-
break*aspects of abstraction in spatial information Prof. Sester Dr. Kazakos
12:00 - 13:00 lunch-break and coffee-break*
13:00 - 14:30 youth forum1 / round table2 1Dr. Lucas / 2Prof. Breunig1Dr. Lucas / 2Prof. Breunig
14:30 - 15:00 resumé Dr. Lucas
* the coffee-breaks are sponsored by
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participants List
Name InstitutProf. D. Dransch German Research Center for Geosciences, HU BerlinProf. M. Breunig Geodetic Institute, KIT
Prof. M. Sester Institute of Cartography and Geoinformatics, HannoverDr. W. Kazakos DISY, KarlsruheDr. A. Abecker Research Center Informatics (FZI), Karlsruhe
Prof. A. Zipf Geoinformatics, University of HeidelbergProf. A. Frank Department of Geoinformation and Cartography, TU Wien
Prof. M. Egenhofer Spatial Information Science, University of MaineProf. W. Kuhn Institute for Geoinformatics, University of Münster
Prof. Ch. Freksa Informatics, University of BremenProf. C. Habel MIN Faculty, Department of Informatics, University of Hamburg
Dr. B. Jutzi Institute of Computer Vision and Remote Sensing, KIT Dr. Ch. Lucas Institute of Computer Vision and Remote Sensing, KIT
Dr. J. Wiesel Institute of Computer Vision and Remote Sensing, KITS. Keller Institute for Regional Science, KITK. Poser German Research Center for Geosciences
Dr. T. Usländer Fraunhofer IOSB, KarlsruheProf. P. Bluhm Institute for Applied Geosciences, KIT
T. Brüggemann Building Lifecycle Management, KITDr. R. Schweitzer Geowissenschaftliches Landesservicezentrum, RP Freiburg
K. Helle Institute for Geoinformatics, University of MünsterP. Weiser Department of Geoinformation and Cartography, TU Wien
D. Richter Institute of Computer Vision and Remote Sensing, KITA. Abdalla Department of Geoinformation and Cartography, TU Wien
I. Wechselberger Department of Geoinformation and Cartography, TU WienM. Maniyar Institute for Geography and Geoecology, KIT
Prof. E. Pebesma Institute for Geoinformatics, University of MünsterT. Soylu Institute for Regional Science / ISL, KIT
Dr. N. Paul Geodetic Institute, KITA. Degbelo Institute for Geoinformatics, University of Münster
R. Sassa Institute for Meteorology and Climate Research, KITDr. J. Scholz Department of Geoinformation and Cartography, TU Wien
Dr. S. Tyagunov CEDIM, IMB, KITDr. A. Chymyrov KSUCTA, Bishkek, Kyrgyzstan
Dr. J. Handwerker Institute for Meteorology and Climate Research, KITC. Wolf Student Geoecology
Dr. P. Bradley Institute of Computer Vision and Remote Sensing, KITF. Pires de Castro Universidade Federal do Paraná / IBGE
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KeynoteProf. Andrew Frank Department of Geoinformation and Cartography, TU Wien
GIS research started with conferences in the late 1970s. Theory and practice has greatly advanced over the 30 years since but also the technical environment has made in-credible progress. I will first review the technology challenges posed today and how they change assumptions for research; then, I look at some consequences and conclude with the presentation of 3 research topics we work on.
Some changes in IT relevant for GIScience over the past 30 years:• CPU speed increased more or less follow-
ing Moore's law; but for the past few years cycle times remain the same, but more CPU cores become available. How to use them?
• Computer connections and networking emerged with the Open System Intercon-nect standard;
• since then, the www has exploded with connections even to mobile devices.
• Relational database theory promised cen-tralized implementations to help with GIS; today we suffer from their limited flexibil-ity and their need of connectivity.
• GPS was a dream, now it is available out-doors at negligible cost in most mobile de-vices.
What are the consequences?• Most of the languages currently used to
program GIS are not suitable for auto-matic parallelization; it is likely that a ma-jor redesign will be necessary soon, which will have effects on GIS and its industry. I assume that pure functional languages parallelize automatically.
• Relational databases as currently used for GIS are not suitable for mobile applica-tions where connectivity is not always as-sured; new database designs, geared to-wards replication and parallelism appear (e.g. the ones used by Google for their search engines).
• Spatial access methods cannot be built into but must be grafted on top of data-base engines.
• GIS was mostly for administrations, but the interesting and lucrative development are in the commercial sector today!
I will conclude with presenting two research topics we currently work on:• Storage of geometry using simplicial
complexes is theoretically clean, but prac-tice uses shape files without topology; a new approach AHD with BIGINT allow-ing to recompute topology and storing ge-ometry as polytopes. It prepares GIS for more than 2 dimensions and time and supports level of detail access.
• Personal geographic information or “spa-tial personal information management” (spatial PIM): the email clients, our ad-dress books and the electronic calendars we carry around in our mobile phones are spatially blind; can GIS technology help?
• Understanding queries from users depend on context. Recent research formalizes context and allows transformation of meaning of terms.
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Modelling uncertain and fuzzyspatial information
Prof. Edzder Pebesma Institute for Geoinformatics, University of Münster
In this talk, the two most common ap-proaches for dealing with uncertain spatial information will be discussed: probability theory and fuzzy set theory. The first as-sumes that there is a crisp, real world about which our knowledge is limited, and ex-pressed by probabilities; the second assumes that the world does not adhere to our crisp concepts (categories), and that a degree of adherence (fuzzy membership) is in place to express this.It will look into how these two formalisms work out when we apply it to a multivariate spatial and spatio-temporal setting. Typi-cally, joint, multivariate modelling is in place to extract essential messages from groups of variables. Multivariate relation-ships in the spatial or spatio-temporal do-main need to be addressed and quantified
when more generic where? or how much? quenstions need to be addressed for larger regions or periods than that of basic meas-urements (typically moments, pixels, points).The talk will also address the usefulness of Frequentist versus Bayesian approaches, and address different sources of uncertainty such as aleatory (variability), epistemic (lack of knowledge) and possibly ontological (lack of agreed definitions). Finally it will be ar-gued that a comprehensive framework for quantitative assessment of uncertainties will add at least one dimension to the dimen-sionality of the problem at hand. First ef-forts for a markup language to describe un-certain data in spatial and spatio-temporal applications, UncertML, will be discussed.
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Potential of UnstructuredSpatial Information
Prof. Christian Freksa,FB3 – Informatics, University of Bremen
Written, spoken, and gestural communica-tion about space does not follow fixed forms that could easily be mapped into canonical formal representations of spatial relations. Similarly, maps, sketches, and other dia-grams exhibit a multitude of specific spatial relations that are too numerous to be di-rectly used for storing or retrieving informa-tion in spatial information systems. These sources of spatial information therefore tend to be perceived as unstructured or chaotic.In my statement, I will promote a cogni-tively oriented perspective on information about space and on spatially encoded in-formation: rather than advocating a single canonical structure or format for represent-ing spatial information, I propose to allow for multiple frameworks and reference sys-tems. These include absolute and relative, external and internal, quantitative and qualitative, precise and approximate, user-centered and global representations that may be involved. Depending on the task to be solved, representations may have to be transformed from one framework to an-other. Certain information may get lost in the transformation process, as not all frameworks are equivalent.Mental concepts and human language permit exploiting a multitude of different structures to convey spatial information and
humans are able to interpret a large variety of structures and formats. Each structure may have specific advantages with respect to the kind of information to be conveyed. To be useful for communication, interpret-ers of human language descriptions of space must be able to map these to their own conceptualizations. Some mappings may be more sensible than others; semantic representations and compatibility models are helpful in determining promising candi-dates for structure mapping. We can view maps and sketches as entities, which consist of multiple structures, only some of which will be interpreted in any given situation.I will address the question whether or to what extent Geographic Information Sys-tems can benefit from a ‘cognitive ap-proach’ to knowledge representation. To this end, I will compare requirements, tasks, representations, properties, and solutions of technical and natural ‘spatial information systems’. I will emphasize the role of do-main knowledge and meta-knowledge that provide much power to problem solving in natural systems; this knowledge is still lack-ing in most technical approaches. I will il-lustrate some of my points by means of a concrete spatial information system.
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temporal aspects of spatial information in GIS
Prof. Martin BreunigGeodetic Institute, Karlsruhe Institute of Technology
Humans perceive the world in space and time. From a given spatial and temporal point (spatio-temporal position) we look in different spatial directions such as before, behind, left, right, above, below and we look in the temporal directions before (future) and after (past). We can measure the spatial and temporal distance from one spatio-temporal position to another. We can also measure (horizontal and vertical) spatial an-gles from a given spatial position. Topologi-cally we can observe spatial and temporal neighboring objects of a given spatio-temporal object. To get a better idea of space and time, respectively, it is interesting to examine the analogies and the differences between space and time. In some aspects the “4th dimension” can be treated analo-gously to the first three dimensions, but in others this is definitely not the case.“To dive into research” concerning tempo-ral aspects of spatial information in GIS, discrete and continuous time, also periods of time, should be considered as well as inter-polation between two given states of an ob-ject and time in databases.Hitherto processing and analysis capabilities for spatio-temporal data or objects are poorly developed inside GIS. However,
temporal queries based on temporal predi-cates and spatio-temporal operators, time series analysis, process analysis, and simula-tion are important instruments for the ex-amination of geo-scientific and planning processes and should be part of next gen-eration GIS. One of the open questions is which new temporal concepts have to be in-troduced in GIS and how they fit into exist-ing data structures and operations.The identification of important classes for temporal applications will help to find these new temporal concepts. Certainly interfaces to numerical and analytical process model-ing will play a role in these efforts. Also the visualization of spatio-temporal processes has to be further developed and adapted to geo-scientific requirements.Without any doubt time (in GIS) is an excit-ing topic that will employ many GIS re-searchers from now on during many years and decades.
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Ontologies – capturing the semantic dimensions of geoinformationProf. Werner KuhnInstitute for Geoinformatics, University of Münster
Ontologies are now routinely used for dis-covering and integrating geodata and geoservices on the web. They specify how producers and users of geoinformation use certain terms in some domain. For example, a hydrology ontology may specify whether a term like river is used for a body of flowing water (as in the Water Framework Direc-tive), for a river bed that occasionally carries water (as required in southern Europe) or with a flag for both possibilities (as in Ger-many’s ATKIS object catalogue). Users looking for data or services can then express their needs in these terms, independently of data models, and logical reasoning tech-niques can match the stated needs to exist-ing information sources. The technological ingredients to define, encode, and use on-tologies are available and widely used for geoinformation as well as other applica-tions, such as e-commerce or social net-works. Yet, the notion of ontologies still leads to confusion and even resistance in theory and practice. For example, there is a widely held misconception that ontologies are meant to standardize terminologies, while they serve the exact opposite purpose, namely to allow
an information community to keep their use of terms and relate it to others. Further-more, the proliferation of ontologies for this and that on the web, without much of a common basis, raises serious concerns about how to mediate between them: with so many ontologies, are we still confused (about the meaning of terms), but on a higher level ? In my presentation, I will briefly introduce the basics of ontologies and their use through examples. Then, I will show how to generalize the notion of reference systems, familiar to geoinformation specialists, from spatial and temporal data to all dimensions of geoinformation (space, time, theme). A core ingredient of this approach is the idea of grounding ontologies in physically ob-servable properties, just like coordinate and time reference systems are grounded in ob-servable monuments and events. The re-search program around Semantic Reference Systems, as pursued at MUSIL, will serve to illustrate current and future challenges in dealing with the semantic dimensions of geoinformation.
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Computational Challenges inGIScienceProf. Max EgenhoferSpatial Information Science and Engineering, University of Maine
Geometric models for geographic objects have reached such a level of maturity that they are commonplace in database systems, supporting querying and other analytical operations over very large datasets. At the same time the analytical models for distrib-uted phenomena -also known as fields-typically offer only tailored implementations for highly specialized models. I will make the case for a generic field data model, which covers not only spatially distributed phenomena, but anything that is based on <position,value> tuples. Much like the rela-tional data model, which serves as a consis-tent and comprehensive foundation for any data in tabular format, a field data model should provide a similarly encompassing or-
ganizational rationale with appropriate op-erations to create, query, and manipulate generic fields. The computational chal-lenges include the specification of a sound, generic field data model, the implementa-tion of generic field management systems, and the analytical operations to model ob-jects within the realms of such fields. As a backbone for any sensor-streamed field data, a field management system would en-able a uniform interface.
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Aspects of abstraction in spatialinformation
Prof. Monika Sester Institute of Cartography and Geoinformatics, University of Hannover
Perceiving and inspecting information at different levels of abstraction seems to be a concept inherent in human cognition and communication. Consider e.g. the way newspapers are written or stories are told: usually a coarse-to-fine approach is used to guide the reader from the overview to the details. This concept is also very relevant for spatial cognition, where we inspect a spatial situation from far, before we come closer to view the details.
At a technical level of spatial information processing, abstraction or generalization re-fers to the reduction of the information to be stored, processed and visualized. Meth-ods for the abstraction of spatial data have been developed in the context of computer graphics and cartographic generalization. In cartography, the primary goal was to produce 2D maps in different scales. In re-cent years, the automation needs of NMAs
have considerably triggered the commercial development and use of automatic gener-alization processes.
Research issues in the context of spatial data abstraction are e.g.:• 3D-generalization of city models• Development of standards for visualiza-
tion of generalized 3D objects (similar to 2D)
• Selection of adequate scales for processing and analysis
• On-the-fly generalization • Multi-scale representation of spatial ob-
jects (ideal: seamless scale) • Integration of semantic and geometric ab-
straction
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Important Addresses
conference venue Jordan HörsaalEngler Str. 7 (Geb. 20.40)76128 Karlsruhe
accommodation Hotel Berliner HofDouglasstrasse 776133 Karlsruhe
get together Badisch BrauhausStephanienstr. 38-4076133 Karlsruhe
taxi call Karlsruhe 0721 944 144
Important Facts about the KIT
The Karlsruhe Institute of Technology (KIT) is an academic research and education insti-tution resulting from a merger of the university (Universität Karlsruhe (TH)) and the re-search center (Forschungszentrum Karlsruhe). It is located in the city of Karlsruhe, Ger-many. The university was also known as Fridericiana and was founded in 1825. In 2009, it merged with the former national nuclear research center founded in 1956 as the Kernfor-schungszentrum Karlsruhe (KfK). One of nine German Excellence Universities, the KIT is one of the leading technical universities in Germany, ranking 6th in Europe in terms of scientific impact.
Conference WLan account
For the 14th and 15th of october every participant get an free WLan account. The login name and the password is given by the table in the conference folder.
Please connect the vpn/web/belwue hotspot and open your browser. You will be asked for the login name and password from the table. Please fill in.
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Quelle: OpenStreetMap, █ Badisch Brauhaus, █ Hotel Berliner Hof, █ conference venue
14
15
KOORDINATIORDr.-Ing. Christian Lucas
Karlsruhe Institute of Technologie (KIT)Institute of Computer Vision and Remote SensingEngler Str. 776128 Karlsruhemail: [email protected]: 0721 608 3676
url:www.multiGI.kit.edu
16
