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GI Product Development
Gerhard Navratil
Workshop in connection withGeomatics 2011, Teheran, May 14 2011
Gerhard NavratilWorkshop GI Product Development
Contents
• Motivating Examples
• GI Product Design– Value of a GI Product– Data Requirements– Legal Aspects– Costs of a GI Product
• Implementation?
Gerhard NavratilWorkshop GI Product Development
Motivating Examples
• Course concept used for several years at– Vienna University of Technology – Surveyors– Technikum Wien (University of Applied
Science) – Intelligent Transportation Systems
• Results from student work
Gerhard NavratilWorkshop GI Product Development
Mobile GIS to Optimize Information Flow in Case of Emergency (1)
• Fast reaction can save lives
• Information in essential
• Requires cooperation between organizations
Use of new communication and information technology
Philipp Nitsche
Gerhard NavratilWorkshop GI Product Development
Mobile GIS to Optimize Information Flow in Case of Emergency (2)
Gerhard NavratilWorkshop GI Product Development
CLIENT SERVER
DB
XML, CAPalert
XML, GMLinfo
XML, GMLjob form
maps
5
TETRA
Terrestrial trunked radio TEDS: up to 500 KBit/s For emergency- and
rescue services 2-way authentification Direct connection
without telephone network possible
Potential use of different frequencies
Push-to-Talk
Technical Concept
Mobile GIS to Optimize Information Flow in Case of Emergency (3)
Gerhard NavratilWorkshop GI Product Development
Benefits:
Mobile GIS to Optimize Information Flow in Case of Emergency (4)
Gerhard NavratilWorkshop GI Product Development
Emergency Calls for Elderly People
• Increasing percentage of elderly people in Europe
• Many living alone
• How to help them when they need help?
Susanne Pröstl
Gerhard NavratilWorkshop GI Product Development
Existing System 1
• Bracelet with sender• Connection to telephone line• Pushing a button creates connection to
emergency response center• Handsfree equipment for ommnunication• If not possible: Person of trust informed
Costs: Rent: 27.50€/month
Gerhard NavratilWorkshop GI Product Development
Existing System 2
• Additional sensor around the neck
• Automatic detection of fall
• Automatic alarm
Costs: 33.90€/month
Gerhard NavratilWorkshop GI Product Development
Extensions
• Built like a mobile phone• Positioning by GSM-Positioning• Relaying position to person of trust or
ambulance• Finding shortest route• Communication via telephone
But: Is it allowed to transfer the position to a third party?
Gerhard NavratilWorkshop GI Product Development
Personalized Traffic Information System (1)
What is the current situation?
• many traffic information services available– anachb.at– ÖAMTC– ASFINAG (road pilot)– ÖBB (Scotty), Wiener Linien (Qando) etc.
a lot of information available
but not personalized
Peter Votzi
Gerhard NavratilWorkshop GI Product Development
Personalized Traffic Information System (2)
• provides information depending on the user needs.
• filters “unnecessary information”– users need only information affecting their
trips– trip routes are often the same, e.g., family
visitstell the user only what he wants to know
Gerhard NavratilWorkshop GI Product Development
How does it work
• user data needed:– trip routes– trip times– service channels
• traffic events affecting the routes are transmitted to the user– route edges subtend affected edges– travel time exceeds a threshold
GIS operations, functions needed
from where to where to you go and when?
how do you want to receive the information?
Gerhard NavratilWorkshop GI Product Development
What data are needed?
• a common reference system (GIS)– road network, ways, points of interest,
addresses
• traffic information
• travel time
Gerhard NavratilWorkshop GI Product Development
What functions are needed?
• geocoding, routing, a map
• service interface
• service broker
easy user interface
provide the information
receive traffic information,compute personalized results
Gerhard NavratilWorkshop GI Product Development
Where to get data?
• Requirements– up to date, multimodal– can be used as reference system
• ALERT-C/TMC, chain age (linear reference)
– routing graph
• commercial data providers?
• solution: OpenStreetMap– up to date, open license (attribution, share alike)– Replication
too expensive, old, not multi modal, license issues
Gerhard NavratilWorkshop GI Product Development
How do design? Architecture
• PostgreSQL + PostGIS
• pgrouting, osm2pgrouting
• osmosis
• UMN MapServer
• Openlayers
• Apache Web Server, Asterisk, Sendmail
storage
routing
map rendering, OGC services
replication
client map
web server, phone & sms gateway, email gateway
all components are open source no license fees!
Gerhard NavratilWorkshop GI Product Development
ArchitectureTraffic Information
Source
Service Broker
datex2 push
DatabasePostgreSQL, PostGIS
reference system, user data, gis data
MapServer
Web Server
Replication osm
SMS gateway E-Mail gateway
routing engine
Website
Gerhard NavratilWorkshop GI Product Development
Which standards to use ?
• OGC– Web Map Service (WMS)– Web Feature Service (WFS)– Simple Features (database)
• EASYWAY – Datex2 or TPEG
Gerhard NavratilWorkshop GI Product Development
Tons of other examples
• Tourist guides
• Support for Alzheimer patients
• Finding paths without crosswind
• Bus-stop optimization
• Fire protection system – are there still humans in a burning building?
• …
Gerhard NavratilWorkshop GI Product Development
GI Product Design
• What is the information content for the user?
• What is the value for the user?
• What data are necessary?
• Access method?
• How can the information be extracted?
• What are the costs of this service?For the producer and for the user!
Gerhard NavratilWorkshop GI Product Development
Information Content
Amount of data transferred through a channel can be measured (e.g., in Bits – one binary decision) (Shannon and Weaver 1949)
Useful to determine storage space etc.
But is it useful for information content?
NO: Measures the amount of data, not the effect of the message
Gerhard NavratilWorkshop GI Product Development
Example: Same Route Information? [1]
Kirchberg am Wechsel to Gloggnitz
• Follow the road to Otterthal
• In Otterthal turn right towards Gloggnitz
• Follow the road through Schlagl and Graben
• Cross under the Semmering highway
• Follow the road into the town of Gloggnitz
Gerhard NavratilWorkshop GI Product Development
Example: Same Route Information? [2]
Your route from Kirchberg am Wechsel to Gloggnitz: The total distance is 13.1 km. To drive this distance will probably take 00:21 (hh:mm).
• 00:00 On LH134\Markt 4,1 km 4,1 km• 00:06 Turn right on LH134\Otterthal 6,6 km 10,6 km• 00:16 Turn right on LH134\Graben 430 m 11,0 km• 00:16 Turn right on LH134\Graben 770 m 11,8 km• 00:18 Turn right on B27\Semmeringstrasse 650 m 12,5 km• 00:19 Turn right on Hoffeldstrasse 500m 13,0 km• 00:20 Turn right on Sparkassenplatz 50 m 13,0 km• 00:21 Turn left on Sparkassenplatz 128 m 13,1 km
Gerhard NavratilWorkshop GI Product Development
Pragmatic Information Content
Shannon & Weaver: Transmission
Frank: Pragmatic Information Content
Assessment of information contentmust include the decision that isbased on the data.Relative measure:better decision = more (better) information
Gerhard NavratilWorkshop GI Product Development
Necessary Discussion for a GI-Product
• What is the information necessary for good decisions?
• Level of redundancy?
Gerhard NavratilWorkshop GI Product Development
Value for the User (1)
Products must have a benefitBenefit of GI-product may be (Krek & Frank 1999)
• Reduced time to make a decision• Improved decision• Reduced risk
Problem: Cost of data increases with quality
Cost
Quality
Gerhard NavratilWorkshop GI Product Development
Value for the User (2)
Quantification of value? Value chain:The value chain concept according to Porter (1985) suggests
that the activities in transforming raw materials and other inputs to final goods can be viewed as a collection of complementary and sequential tasks, each adding value to the final product.
USERS
Producer 1 data collector
Producer 2 Producer N dataintegrator
specialistGeoinformationproduct
(Krek & Frank 1999)
Gerhard NavratilWorkshop GI Product Development
Costs in the Value Chain
USERS
Producer 1 data collector
Producer 2 Producer N dataintegrator
specialistGeoinformationproduct
fixed cost + marginal cost = total cost
high low, zero(sunk cost)
Gerhard NavratilWorkshop GI Product Development
The Value Chain Paradox
USERS
Producer 1 data collector
Producer 2 Producer N dataintegrator
specialistGeoinformationproduct
VALUElow high
Gerhard NavratilWorkshop GI Product Development
Value for the User (3)
How much is a client willing to pay?
Maximum is determined by
• the benefit
• reduced by the costs of accessing the GI product
Price = Maximum No gain for the user
Price < Maximum
Gerhard NavratilWorkshop GI Product Development
What Data are Necessary
Analysis of information leads to required data
Example: Car navigation requires at least• Street network• Speed limit• Restrictions (turning, weight, height, etc.)• Address information
Missing data leads to services that do not work – how often do you specify your destination by coordinates?
Gerhard NavratilWorkshop GI Product Development
Why is Data Quality Important?
• Data deviate from the ‚correct‘ values
• Reason (Morgan & Henrion, 1990)
– Incompleteness– Disaccord between different data sources– Linguistic uncertainty– Variability– Registration of physical data
Gerhard NavratilWorkshop GI Product Development
Description of Data Quality
• Lineage
• Accuracy
• Completeness
• Logical consistency
• Currency
• Semantic accuracy (Guptil & Morrison, 1995)
Gerhard NavratilWorkshop GI Product Development
Storage of Data Quality: Metadata
Metadata = Data on DataDefined in standards (e.g., ISO TC 211, 2002)
Should be connected with data and contain
• Identification
• Data quality (without semantics)
• Data organization (e.g., vector - raster)
• Information on classification, attributes
• Distribution path, contact, liability
Gerhard NavratilWorkshop GI Product Development
Problems With Metadata
• Typically not collected or not updated
• User do not understand them (Boin & Hunter, 2007)
• No rules for 3D-data (compare Sargent, Harding & Freeman,
2007)
Gerhard NavratilWorkshop GI Product Development
What is Quality?
„degree to which a set of inherent characteristics fulfils requirements “ (ISO9000)
Requirements depend on application
Simple if only one type of application is possible (e.g., fire arms)
What about geographic data?
Gerhard NavratilWorkshop GI Product Development
Observation and Measurement
Observations used to determine properties of the physical world
Result measured in different scales– Nominal scale: Names only– Ordinal scale: Includes order– Interval scale: Includes differences– Rational scale: Includes absolute zero
Gerhard NavratilWorkshop GI Product Development
Total error
Difference between a measurement value and the real value.
The total error consists of systematic and random error (bias).
Gerhard NavratilWorkshop GI Product Development
Systematic error(relates to instrument or conditions of measurements)
Difference between the mean of measurements and the true value.
Systematic errors are determinate errors which affect the accuracy of measurements.
They are caused by instrumental-, human-, environmental- or other effects and can be reduced by using control observations and specific observation methods.Instrumental effects e.g. can be reduced by calibration.
Gerhard NavratilWorkshop GI Product Development
Random error(relates to set of measurements)
Difference between a measurement and the mean of measurements.
The random error is an indeterminate error (noise) and affects the precision of measurements.
Random errors scatter measurements above and below the mean and can be reduced by averaging a set of measurements if the sample set is large enough.Random errors are assumed to be normally distributed.
Gerhard NavratilWorkshop GI Product Development
Random and Systematic Errors
precision:random errors
correctness:systematic errors
resolution
Gerhard NavratilWorkshop GI Product Development
Gross error
Undetected mistakes that cause a measurement to be very much farther from the mean measurement when compared to other measurements.
Gross error
Gerhard NavratilWorkshop GI Product Development
Accuracy
Correctness of a single measurement, calculated from total error.
In spatial datasets we can distinguish between positional accuracy and attribute accuracy. Positional accuracy is often divided into vertical and horizontal accuracy (which can differ significantly) and between relative and absolute positional accuracy.
Attributes can be measured on four measurement scales: nominal, ordinal, interval and ratio. Error descriptions are different dependent on the used scale.
Gerhard NavratilWorkshop GI Product Development
Precision
Reproducibility of the same measurement value.
A statistical measure for precision is the standard deviation.
Other common definition for precision:
number of digits used to report a measurement, not necessarily related to accuracy!
Gerhard NavratilWorkshop GI Product Development
Accuracy and precision
Measurements taken from the same position represented by the center of the circle.
Left: successive measurements have similar values, they are precise. But measurements are far from the real value and are therefore inaccurate.
Right: Precision is lower but accuracy is higher.
A B
Gerhard NavratilWorkshop GI Product Development
Vagueness
Arises due to poor definition and can be caused by poor documentation fuzziness of objects.
Criteria:“Is boundary crisp and well defined?”
“Is the assignment of a particular label to a given zone robust and defensible?”
Gerhard NavratilWorkshop GI Product Development
Fitness for Use (1)
A function that allows the user to evaluate the fitness of the data for his particular application.
Product use decision
Difficult: definition of useful output
Gerhard NavratilWorkshop GI Product Development
Fitness for Use (2)
Can I use a data set to solve a specific problem? (Chrisman, 1984)
Gerhard NavratilWorkshop GI Product Development
Fitness for Use (3)
A data set is useful if its use leads to a feasible decision
What is the definition of ‚feasible‘?
Example: Shop size
Gerhard NavratilWorkshop GI Product Development
Classification
Data are typically classified (organized in classes)– e.g., land use, language
regions, etc.
Requires a definition– What is the definition of
a forest?
(Comber, 2007)
Gerhard NavratilWorkshop GI Product Development
Uncertainty
Reasons for uncertainty? (Fisher, 1999, 2003)
• Vagueness (spatial extent of a mountain?)
• Ambiguity (variations in the interpretation of classification rules)
• Discord (different classifications – e.g., land use/land cover)
Not considered in standards! (Goodchild, 2007)
Gerhard NavratilWorkshop GI Product Development
Where are the single buildings?
(Förstner, 2007)
Gerhard NavratilWorkshop GI Product Development
Semantic Loop
Gerhard NavratilWorkshop GI Product Development
Increasingly Challenging
• Data sets for the personal need
• Data transfer to colleagues
• Data transfer to colleagues outside of the subject area
(Goodchild 2007)
Gerhard NavratilWorkshop GI Product Development
Problem
Traditionally: Map scale describes qualityreduction in scale = reduction in quality
Typical map scales for different applications
Digital maps: Data separated from map scale
Idea: Scale introduced during the observation process – carried forward as quality indication?
Gerhard NavratilWorkshop GI Product Development
Tiered Ontology (1)
Ontology: Describes the conceptualization of the world in a particular context(Guarino 1995, Gruber 2005)
Ontology for information system: Description of conceptualization and processes (reality and information p.)
Ontology used here: Tiered ontology
Gerhard NavratilWorkshop GI Product Development
Tiered Ontology (2)
• Tier 1: Point observationvalue from the properties found at a point in space and time: v=p(x,t)
• Tier 2: (Physical) ObjectsRegions with uniformity in property
• Tier 3: Social ConstructionsConstructs relating physical objects to abstract concepts, e.g., money (Searle 1995)
Gerhard NavratilWorkshop GI Product Development
Information Process
Transforms information
obtained at a lower tier
to a higher tier
Gerhard NavratilWorkshop GI Product Development
Observation of physical properties at a point
Physical process
Links reality (tier 0) to tier 1
Realization is imperfect– Random disturbance– Area observation, not point observation
Systematic bias can be eliminated no further consideration
Gerhard NavratilWorkshop GI Product Development
Object Formation (1)
Also called granulation (Zadeh 2002)
2 Steps:– Form boundaries– Summarize properties
Meaningful things (Gibson 1986)
Gerhard NavratilWorkshop GI Product Development
Object Formation (2)
Often spatially cohesive solids which move as a single piece
In Geography objects do not move uniform properties used to define (overlapping) objects
Increases the imperfection of data – summary instead of detailed description
Gerhard NavratilWorkshop GI Product Development
Boundary Identification
Uniform regions
Select property and property value, define threshold Object boundary
Gerhard NavratilWorkshop GI Product Development
Descriptive Summary
Summary of properties of the space within the object boundaries
Typical functions: Sum, maximum, minimum, average
Examples: Weight of a movable object, rainfall on a watershed, maximum elevation in a country (Tomlin 1983, Egenhofer & Frank 1986)
Gerhard NavratilWorkshop GI Product Development
Classification
Mental classification – relating objects to actions, e.g., using affordances (Gibson 1986, Raubal 2002)
Interactions assert conditionsDifferentiation between objects that fulfill
the conditions and those that do not: Distinction
Distinctions are partially ordered – form a taxonomic lattice (Frank 2006)
‚drinkable‘ is a subtaxon of ‚liquid‘
Gerhard NavratilWorkshop GI Product Development
Random Effects in the Observations
No perfect observation by physical sensor perturbation of the observation
Modeled by Gaussian distribution
Effects on– Object formation– Classification – fuzzy membership (Zadeh 1974)
Gerhard NavratilWorkshop GI Product Development
Effect on Object Formation
Statistical error propagation: Gauss‘ Law
Summary value: Similar influence
Gerhard NavratilWorkshop GI Product Development
Scale in Observation
Physical observation instruments are small but not infinitely small
e.g., pixel sensor in camera: 5/1000mm – integrates photons arriving in this region
Size effects in the observations are unavoidable scale element
Gerhard NavratilWorkshop GI Product Development
. ε)k(ε)dεt)f((x,=t)v(x,
+ε
ε
ε)dεt)f((x,=t)v(x,
Physical Point-Like Observation
v=p(x,t) is not possible
with covering size and time interval
Convolution with a kernel k():
Formal model for the real observation
Convolution with a Gaussian kernel produces an average effect on the signal
Gerhard NavratilWorkshop GI Product Development
Sampling Theorem
Observation density is finite Sampling
Danger of artefacts, e.g., Nyquist Law (sampling twice as frequent as highest signal frequency)
Well known for audio signals – applies to all dimensions including sampling in geographic space
Gerhard NavratilWorkshop GI Product Development
Scale of Observations
• Size of smallest objects detected:Extent vs. scale
• Effects on uniformity:Variation in property value vs. threshold
• Effects on attribute values:Difference max/min vs. average
• Effects on object classification:Class distinction by size (large/small building)
Gerhard NavratilWorkshop GI Product Development
What Follows?
Physical observations differ from point observations– Random perturbation of the result– Finite spatial an temporal extent
Tier ontology allows to follow the effects– Random variation probability distribution– Finite extent convolution
Well designed systems: Influences have comparable size scale
Gerhard NavratilWorkshop GI Product Development
Influences on Data Quality
• Technical limitations (data capture
• Legal restrictions(society needs)
• User needs
Data quality
Technical limitations
Legal Restrictions
User needs
Gerhard NavratilWorkshop GI Product Development
Technical Limitations
Higher quality higher costs
Absolute Limite.g. approximate relativeuncretainty of the definition of the unit length ‚meter‘: 2,5*10-11
Other examples: Satellite images, GPS
Quality
Costs
maximum quality
new technology
Gerhard NavratilWorkshop GI Product Development
Legal Restrictions
Laws influence data quality by– Influence on data capture processes (e.g.,
cadastre, statistics)– Access restrictions
Weak constraints (laws can be broken)
Examples: Demographic data, data from spatial planning
Gerhard NavratilWorkshop GI Product Development
User Needs
Assumption: Large number of users/important users higher data quality available
Indication: Data capture within communities (e.g., mountain-bikers, hikers, etc.)
Examples: Topographic maps (military), nautical charts
Gerhard NavratilWorkshop GI Product Development
Legal Aspects for GI Products
• Copyright
• Data protection
• Liability
Gerhard NavratilWorkshop GI Product Development
Copyright: Definitions
• Copyright: Protects the rights of the authorBasis: British/American tradition, concentration on economic rights (exploitation rights)
• Usage right: Allows possession and (personal) use
Gerhard NavratilWorkshop GI Product Development
General Definition of Copyright
The right to copy; specif., a property right in an original work of authorship (including literary, musical, dramatic, choreographic, pictorial, graphic, sculptural and architectural works; motion pictures and other audiovisual works; and sound recordings) fixed in any tangible medium of expression, giving the holder the exclusive right to reproduce, adapt, distribute, perform, and display the work.
(Black‘s Law Dictionary, 2004)
Gerhard NavratilWorkshop GI Product Development
Austria: Intellectual PropertyRight (1)
• Definition author: Person creating something unique (text, graphics, design, music, software, etc.)
• Several authors: co-authors• Test of co-authorship: Is the contributor‘s effort an
original expression that could quality for copyright protection? (Blacks Law Dictionary, 2004)
• Intellectual Property Rights expire– 70 years after the death of the author (USA: 50 years)– 70 years after creation if authors are unclear After that freely usable
Gerhard NavratilWorkshop GI Product Development
Austria: Intellectual PropertyRight (2)
• Intellectual Property Rights include– Right of reproduction– Right of distribution– Broadcast right– Presentation right– Provision right
• Intellectual Property Right ALWAYS stay with the author!
• Only parts can be given away
Gerhard NavratilWorkshop GI Product Development
Ensembles (Sammelwerke)
• Combination of individual contributions to an ensemble are copyright protected if– it constitutes a creation process– the selection of contributions could have been
done differently
• The ensemble is protected by copyright
• But: The individual contributions are still protected by copyright!
Gerhard NavratilWorkshop GI Product Development
Free Work
• Not protected by copyright
• Examples: Laws, decrees
• Topographic maps of the Austrian surveying authority (BEV) are no free work!
Gerhard NavratilWorkshop GI Product Development
Exploitation Right (Nutzungsrecht)
• Transfer of the rights from the author to a third party
• May happen automatically– e.g., employee writes a text for his company– Important for universities, research centres
(exclusive exploitation right? – patents)
Gerhard NavratilWorkshop GI Product Development
Computer Programs
• Work as protected by copyright law if it emerged from an intellectual creation process– Code to access a TXT file is not protected– New method/algorithm to solve a specific type
of equation system is protected• Covers source code as well as materials
created while developing the program• Employer has unlimited exploitation right if
created during office hours
Gerhard NavratilWorkshop GI Product Development
Copyleft (Slang)
• Specific software license model• Allows users to modify or incorporate open-source code
into larger programs on the condition that the software containing the source code is publicly distributed without restrictions
• Freeware: Software that is made generally available with express or implicit permission for anyone to use, copy, modify, and distribute for any purpose, including financial gain – includes open-sourceFree refers to usage rather than price!
(Blacks Law Dictionary, 2004)
Gerhard NavratilWorkshop GI Product Development
Databases
• Databases are treated like ensembles
• No protection if there is only one way to do it, e.g.,– Law database– Probably: addresses, contour lines
Gerhard NavratilWorkshop GI Product Development
Conclusions Copyright
• Protected are display format and selection
• No protection if published in form of laws or decrees or if there is no freedom of geometry (boundaries of administrative units)
• Problematic: Contour lines
Gerhard NavratilWorkshop GI Product Development
Personal Data Protection
• Right on confidentiality of personal data• Privacy law: Restricts public access to personal
information such as tax returns or medical records (Blacks Law Dictionary, 2004)
• Informational Privacy: A private person‘s right to choose to determine whether, how, and to what extent information about oneself is communicated to others, esp. sensitive and confidential information (Blacks Law Dictionary, 2004)
• Exceptions:– Publicly available data– Aggregated data (if they cannot be re-connected
with a person!)
Gerhard NavratilWorkshop GI Product Development
Definitions
• Personal data: Data on persons whose identity is known or can be determined
• Indirectly personal: Connection to person cannot be made by legal methods– May be completely impossible– May be possible using illegal means
• Sensible data: Special protection (e.g., racial and ethnic origin, religion, sexual preferences, political or philosophical opinion, health status)
Gerhard NavratilWorkshop GI Product Development
Liability
• The quality or state of being legally obligated or accountable; legal responsibility to another or to society, enforceable by civil remedy or criminal punishment. (Blacks Law Dictionary, 2004)
• Austria: Liability if you publicly announce that you are an expert – even if you have no adequate education!(ABGB § 1299)
Gerhard NavratilWorkshop GI Product Development
Suthradhar vs. Natural EnvironmentalResearch Council (1)
• British Geological Survey (department of the NERC) works on deep wells (from 1984)
• In 1991-92 the BGS creates a hydro-geologic study on groundwater in Bangladesh
• Within the study tests of the water on bacteria and some toxins (aluminium, ferrite, iodine)
• 1993 detection of arsenic in the ground water of neighbouring areas
• Fault of the experts?
Gerhard NavratilWorkshop GI Product Development
Suthradhar vs. Natural EnvironmentalResearch Council (2)
Problem: Original study not for drinking water but how to optimally design tube wells to avoid deterioration
Study described as reconnaissance study
Results of study applied to creation of wells for drinking water
Misuse of data
No liability
Gerhard NavratilWorkshop GI Product Development
When We Have the Data …
• How can we access it?
• How can we make sure that the communication works?
Gerhard NavratilWorkshop GI Product Development
Access Methods (1)
Communication Channels
• Textual• Graphical• Verbal
Gerhard NavratilWorkshop GI Product Development
Access Methods (2)
Limitations of the users?
• Language• (Color) Blind• Deaf
Gerhard NavratilWorkshop GI Product Development
Access Methods (3)
Data access
• online/offline• Mobile phone/PC• Time of access?
Gerhard NavratilWorkshop GI Product Development
Information Extraction
How to perform each step?
• Collect the data
• Process the data (e.g., using a GIS)
• Create the product
• Deliver the product through the selected channel
Gerhard NavratilWorkshop GI Product Development
Feasibility
• Number of potential customers?
• Market penetration?
• Earnings with each customer?
• Will the system be cost-effective?
• Return on investment?
Gerhard NavratilWorkshop GI Product Development
Example: Lunch Menus (1)
Problem description• I go to lunch each day and have to make a decision for a
specific restaurant• Selection based on menu (changes daily) and personal
preference• Menu only visible when I am at the restaurant
possible detour if I do not like the menu
Solution• GI-product showing me the current menus and the
locations of the restaurants
Gerhard NavratilWorkshop GI Product Development
Example: Lunch Menus (2)
Design• User group: people working at the Vienna
University of Technology and nearby offices• Access: online via Internet
Necessary data• List of restaurant with addresses• Menus of the restaurant (typed in manually)• City map
Gerhard NavratilWorkshop GI Product Development
Example: Lunch Menus (3)
Costs• Simple computer (€ 1000)• Internet access (€ 30/month)• Power supply (€ 30/month)• Data input (2h/day, € 15/h € 600/month)
Number of potential customers• Employees of Vienna University of Technology:4000• Other employees: 1000
Market penetration?• Assessment: 2%
Gerhard NavratilWorkshop GI Product Development
Example: Lunch Menus (4)
Value of the information?• Cost of a lunch € 5 – 14• Tip: € 0.5 – 1.0• Assessment of value for better decision: € 0.5
Is the service profitable?• Costs: € 1000 + 660/month• 100 customers/day 2000 queries/month
income € 1000/month
Not yet included: Programming, marketing, office rent, organization, etc. probably not profitable
Gerhard NavratilWorkshop GI Product Development
Implementation
• Depends on the technology used
• Changes rapidly
• Should be based on standards and standard protocols (e.g., GML)
• Should consist of independent modules (re-use)