Feedback on Project Draft (HW 4)
- General Comments :
A few comments apply to multiple papers.
These comments are summarized below:
- A. Consider formatting your papers and reports like the
papers in the reading list.
Show page numbers, section numbers, figure
numbers, table numbers in your paper.
Consider using latex (or its graphical counterpart LyX, see www.lyx.org)
to compose your papers.
It will check for many of the stylistics problems and help you
focus on technical writing.
It is easy to learn and we can get short tutorial from fellow
graduate students.
If you use HTML or
MS Word instead of latex, be sure to use appropriate features
to support cross-reference, citation, numbering of sections/ figures etc.
Group G4's draft paper is an example of the desired format.
- B. Include a list of refernces at the end of papers.
Every reference should identify authors, title, publication forum
(publisher, conference/journal/book, volume, number, url, ...), date of
publication etc. so that readers can locate them easily.
- C.
Cite the sources (entries in your list of references) near the text
referring to relevant concepts/contributions.
Clearly identify text quotations, figures or tables from sources.
- D. Use figures and table to highlight key messages in your paper.
- E. Avoid using white-paper-ish material from commercial websites
and marketing literature. Focus on technical material from
research conferences, journals, books, etc.
- General Comments on Survey Papers
- F. A common format for survey paper are those
used by ACM Computing Survey.
Follow similar formats for your papers.
Provide a table of content and a list of figures and tables
to help readers navigate the paper.
- G. Use a classification diagram to show the overall grouping
of the ideas in the literature. Explain the criteria used
for classification. Define the classes and then provide general
summary of ideas for papers belonging to each class. Do not
provide summary of individual papers.
It will also help you identify future work by looking for combinations
not explored by any papers yet.
- H. Recall that presentations on survey papers
will include motivation,
major problems in the area, key results, open problems, and
key sources.
Survey paper should clearly identify these components
as well. Abstract, introduction and conclusion should highlight
the major problems and key results.
- General Comments on Reports on Implementation Projects
- I. Recall that presentations on projects should follow
the format of paper analysis.
Candidate sections include motivation, problem definition, key issues and
alternative ways of resolving those, related work and their limitations,
your approach, validation, conclusions (key contributions),
and future work (assumptions and potential extensions).
Project report should clearly identify these components
as well. Abstract, introduction and conclusion should highlight
the major contributions.
- J. It is important to identify the key design decisions,
alternative ways of resolving those, chosen approach to resolve those
and justificationof the chosen approach.
Justification of chosen approach relates to validation and may use
validation methodologies such as theoretical / experimental comparison
with other approaches, case studies, examples etc.
- G1 : Privacy
- Focus: geo-privacy guidelines/policies
- Technical feedback:
References include few peer-review papers from
conferences and journals.
- Readability and Organization:
Consider numbering the sections
and formatting the paper like a technical paper.
See general comment in this area.
Consider adding a couple of figures and tables to high key
ingradients of geo-privacy problems and policies.
- Strengths: Describes many cases of geo-privacy violations.
Proposes a geo-privacy policy.
- Areas for improvements:
Consider provideing a classification scheme to organize the
survey of geo-privacy violation cases. This may become the
core contribution of the paper. In addition,
consider examining recent papers (
hong ,
armstrong ,
minch ,)
to complete the literature survey.
- G2 : Report draft not available as of 4/16/04 (4pm)
- Focus:
- Technical feedback:
- Readability and organization:
- Strengths:
- Areas for improvements:
- G3 : Privacy
- Focus: Survey of geo-privacy policies.
- Technical feedback:
Literature survey focusses on commercial viewpoint and will
benefit from inclusion a few academic papers. Key contribution
of the paper is the identification of WLIA policy as a common
policy across commercial web-sites. It will be useful to evaluate
WLIA policy against geo-privacy guidelines from an independent
source, e.g. an academic paper.
- Readability and organization:
Fairly well-written. Easy to follow and read. Has a couple of
tables and figures.
Consider numbering the sections and adding an abstract.
- Strengths:
It is good to see a summary of WLIA policy as it summarizes
the thoughta and discussions of a large number of industry
players.
- Areas for improvements:
It may be useful to
provide a simple table or figure to summarize the relevant
parts of this policy.
Consider comparing /evaluating WLIA
policy with the basic requirements listed in academic papers,
e.g.
hong , and
minch .
- G4 : Indexing
- Focus: Indexing spatio-temporal data for association rule mining
- Technical feedback:
Group has received detailed technical feedback face to face.
Overall a strong paper. Do consider providing schema for the
table on which SQL query (section 3.1) is defined. Problem
definition of choosing indexing method is often defined by specifying
the dataset, a set of queries, and asking for a data-structure which
minimizes average response time of the given queries.
Consider looking at the CCAM (Liu/Shekhar TKDE) paper for an example.
- Readability and organization:
Paper is well-formatted. Please do consider adding an abstract
and affiliations of the authors.
Also check why page 13 of the document was not readable.
Make sure thatthe font size is at least 10.
- Strengths:
Validation via experimental and anlytical cost models.
Consider publishing this paper ina referred conference on
either data mining or spatial databases.
- Areas for improvements:
It will be useful to add a short subsection to describe the
application domain (e.g. Earth Science, global climate analysis)
which is the source of the data. It is important to list overall goals
(e.g. study the impact of El Nino on plant growth around the world)
of Earth Scientis before mentioning the computer sc. tools (e.g. association
rules) that may be used.
Do provide a few citation to the application domains.
Also provide citations to paper showing the usefulness of CS tools (e.g.
associations) to the application domain objectives.
A picture (e.g. map) of the data set will also be nice.
- G5 : Spatial Associations
- Focus: Survey of papers on spatial association rule mining
- Technical feedback: The paper provides a concise description of
the spatial association rule concepts and the families of algorithms
to mine those.
- Readability and organization:
It is an easy to read short paper. Consider adding an abstract, a
couple of figures/tables and formatting references in a standard style
as discussed in the general comments.
Consider expanding the paper to provide examples to illustrate the main
points, e.g. difference between spatial association rules and traditional
association rules. It will be wonderful to identify the spatial association
rules disciered by different algorithms from a common spatial data sets.
- Strengths: Concise summary.
- Areas for improvements:
Consider identify a few limitations of the state of the art in spatial
association rule mining. It may possibly be done via identifying a
classification scheme and showing the sub-classes which are not covered
by current algorithms.
For example, are current methods adequate for processing line-strings
or polygonal features ?
- G6 : Outliers
- Focus: Survey of outlier detection tests and algorithms
- Technical feedback: It is a broad paper and covers a variety of
datasets. It will be helpful to have a couple of figures and
tables to provide a summary of the techniques.
- Readability and organization:
Easy to read paper which uses a historical organization of the
papers in the literature.
- Strengths: Glossary of key terms is helpful to readers.
- Areas for improvements:
Consider identify a few limitations of the state of the art in outlier
detection. It may possibly be done via identifying a
classification scheme and showing the sub-classes which are not covered
by current algorithms.
For example, are current tests adequate for categorical attributes ?
- G7 : Spatial join
- Focus: Join algorithms which produce results as soon as some rows in
each table are received.
- Technical feedback:
Lists contributions and provides data to back those up.
- Readability and organization:
Well formatted papers. Consider checking the page lay out.
Consider reducing left/right
margins and increasing bottom margin.
Page 14 did not display properly.
Motivation for the problem is quite general. It will help to cite
specific application domains or users who can benefit.
- Strengths:
Provide experimental evaluation of the proposed algorithm.
- Areas for improvements:
Consider explaining the need for new algorithms beyond
traditional spatial join algorithms, e.g.
nested-loop, for solving the problem at hand.
Provide an example to motivate the need for new algorithms.
- G8 : Taxi-routing
- Focus: Assigning trip-request to taxis
- Technical feedback:
Paper defines the problem and the proposed solution clearly.
It uses a simple metric, e.g. fraction of requests served within
a time-limit, as the measure of the solution quality.
It may be useful to consider complementary measures related to
solution quality, e.g. trip length or trip time.
- Readability and organization:
Well-written paper. Clearly identify the problem, the solution
approach, and contributions. Provides experimental evaluation of
the proposed algorithms.
- Strengths:
Paper defines a new problem or processing transactions related to
taxi-cab requests.
Discussion of the strengths and weaknesses of the proposed
algorithms.
Consider refining the paper and submitting to a peer reviewed
forum.
- Areas for improvements:
Consider simplifying the problem by ruling out sharing of cabs
by multiple passengers. Is the simplified problem solvable in
polynomial time ?
Consider expanding the experiment design to include competing
taxi routing algorithms, e.g. those based on genetic algorithms.
This paper proposes a heuristic method. Evaluation of heuristic
methods typically include comparison of solution quality with those
achieved by optimal methods. In addition, one may consider identifying
design decisions which can increase the fraction of requests
completed. Evaluation of choices for those design decisions are
valuable.
- G9 : Decision Trees
- Focus: Incorporate neighborhood texture info. in decision tree learning
- Technical feedback:
Well-written paper. Defines the problem and approach clearly.
Provides experimental evaluation of proposed approach with a real
dataset.
- Readability and organization:
Well formatted and easy to read.
- Strengths:
Use of software implementation and real-data set for evaluation.
- Areas for improvements:
Consider justifying the approach of dividing information gain by
texture measures. What is the intuition behind this approach?
Can it be formalized to prove that such an approach would reduce
salt and pepper noise? Are their other approaches to incorporating
context information, particularly auto-correlation in the class
labels? How do those compare with the proposed approach ?
It may be useful to compare the residual error maps for
ID3 and the proposed approach.
- G10 : Routing
- Focus: Impact of link failure on a transportation network
- Technical feedback:
Please complete the experimental result at your earliest
convenience.
- Readability and organization:
Please use the general comments to revise format of the paper.
- Strengths:
- Areas for improvements:
- G11 : Data models
- Focus: Spatio-temporal data models for NHGIS
- Technical feedback:
Paper clearly defines the problem, and proposed approach.
It compare alternative table schemas.
- Readability and organization:
Consider moving the class diagrams (page 4-9) to an appendix to
improve the readability of the paper. A summary class diagram
(spanning about 0.5 page) of the entire model may kept in the
main body. Consider keeping Table 3 seems on one page.
It may be useful to simplify Tables 3 and 4 possibly by decomposing
those into summary and detail tables.
- Strengths:
Classification diagram (Figure 1) of the related literature.
Detailed class diagram of the proposed models.
Tables 1 and 2 provide a good summary of the queries.
Appendices provide details of the queries.
- Areas for improvements:
Tables 3 and 4 use qualitative labels, e.g. simple, expensive,
difficult, etc. Consider provide crisp, if possible quantitative,
definitions of these terms.
It may also be help to provide explanations of a few of the table
entries in the main body of the paper.
Feedback on Project Proposal P4, P5
- General Comments :
The proposal (P5) is a union of the answers to questions P1, P2, P3 and P4.
This you should include the list of readings, summary of readings from last homework in the
proposal instead of creating new ones.
- Group 1 :
You have chosen a timely topic of growing importance.
However, the reading list is a bit short.
Summary of reading is still missing
even though you have created a fairly long list of
examples of privacy violations related to location data.
May be useful to look at arguments presented in the relevant court cases
to identify the principles and guidelines to determine privacy classes of
location data ? For example, home and office addresses are ususally public information,
however hotel room number is usually not public. Pictures of homes listed in MLS are public
information, but paparazzi's may not be allowed to pictures of a private backyard without
permission. What principles differentiate the these privacy classes ?
Consider adding a statement in your proposal to differentiate your proposed work
from that of group 3. For example, one group may focus on policy (e.g. laws, ethics)
and other on implementation mechanisms (e.g. technologies).
Consider reviewing papers on privacy frameworks from following if your paper is proposing
a framework for geo-data privacy:
GIS and privacy article ,
UMN student data confidentiality policy ,
privacy links ,
privacy laws ,
LBS and privacy ,
health info. privacy ,
privacy frameworks: (
1 ,
2 ,
),
general privacy workshop .
- Group 2 :
Well-focussed proposal.
May consider adding a paper or two on detecting outliers based on
non-numeric (e.g. category values) attributes.
Add citations to the papers/books describing WEKA.
References need to provide more information, e.g. publishers, year, etc. Look at the references
at the end of the published papers in our reading list for guidance.
- Group 3 :
You have chosen a timely topic of growing importance. However,
the reading list in the proposal is primarily focussing on the location based services (LBS)
offered by different vendors in various countries. Consider including
in-vehicle navigation devices (e.g. GM Onstar, and similar 3rd party devices)
as well. Are you planning to examine the privacy statements for these vendors and comparing
those?
If many vendors do not provide specific privacy statements about customers' location
information,
you may consider adding other papers to the reading list. Relevant papers
may do some of the following:
(i) classify different kinds of location information with respect to privacy
(ii) legal precedents and guidelines for determining the privacy classes
for different kinds of personal information.
(iii) describe court ruling related to location privacy, e.g. look at the
court cases involving use of aerial imagery in Baltimore and California
Incidentally, I like the reading list in your answers to P2 and P3 better.
Why are those not included in your proposal (ie.g. answer to P4 and P5) ?
Consider adding a statement in your proposal to differentiate your proposed work
from that of group 1.
Consider reviewing papers on privacy frameworks from following if your paper is proposing
a framework for geo-data privacy:
GIS and privacy article ,
UMN student data confidentiality policy ,
privacy links ,
privacy laws ,
LBS and privacy ,
health info. privacy ,
privacy frameworks: (
1 ,
2 ,
),
general privacy workshop .
- Group 4 :
Detailed feedback provided in meeting with the group. Proposal is well-focussed.
- Group 5 :
Summary of readings is still not in desirable format. It is summarizing each paper
individually. Try rewriting the summary of reading using a common classification scheme
as discussed in the feedback for problems P2 and P3.
In fact, the classification scheme of the papers in the related literature is the
key contribution of survey papers and it is crucial for your group to develop a
classification scheme.
Proposal and report should be written in 3rd person. Current draft has many sentences in the
first person. Do include the problem statement, summay of readings, etc. from previous
homeworks into your proposal.
- Group 6 :
Proposal is reasonable. Detailed feedback provided in face to face meetings.
- Group 7 :
It will be useful to provide a crisp problem definition as discussed in the office
hours on Tuesday March 30th. The objective function, e.g. time to produce top K tuples
in the join result, may be used to compare the proposed work with the related work.
Ideally, a dominance zone of the proposed approach in terms of selected
parameters, e.g. K, may be provided using analytical and/or experimental means.
Incidentally, the proposal has references to other spatial join algorithms including
tree-matching, space partitioning, plane-sweep, etc. but does not include text
to summarize those. Comparison of the proposed approach with the classical spatial-join
algorithm is needed.
- Group 8 :
Articulation of innovation relative to related work needs more work. Define the
"decision type problem" and "optimizing some type of cost metric" to bring the
novelty of the proposed approach better.
Note that formal comparison of algorithms for a given problem often requires
identification of an "objective function", which tend to be some kind of a "cost metric",
solution quality, computational response time, throughput (transactions per second) etc.
- Group 9 :
Well-written proposal.
Consider reviewing the work of Carla Brodley (Purdue) on use of decision trees for classifying
remotely sensed images.
- Group 10 :
Well-focussed proposal. Consider examining a simulation based appraoch to analyzing
probablistic failure scenarios for routes. For example, one may assume a time-based
probability distribution (e.g. poission) of edge failure events for the edges in the roadmap.
Given alternate routes, one may carry out monte carlo simulations to generate the failure
events during the traversal of the routes, compute alternative paths and travel time
after the failure events, and assess expected travel time via each route.
One may limit the failure scenarios to single failure event during the traversal of each path,
or to a fixed failure rate per unit time of path traversal.
This simulation approach has been used to evaluate reliability of computer systems
and performance of servers, e.g. operating systems, network protocols.
This approach is also used in determining the behaviour of transaportation
networks for heavy demand in software packages such as DYNASMART and DYNAMITE.
- Group 11 :
Excellent categorization of related work. Well-written proposal.
It may be useful to talk about the process of identifying the frequent queries on NHGIS.
Will you be interviewing users? Are there different categories of users?
Are there other ways of identifying frequent queries?
Feedback on Projects P2, P3
- General Comment 1 : Please write a single narrative
summarizing all the papers instead of writing one paragraph per
paper. Try to design a common classification scheme or framework
to explain the work from all the paper.
- General Comment 2 : Some project topics seem shared by multiple groups.
It is desirable for the groups with common topics to coordinate their
efforts.
- Group G1: Feedback provided in office hours. Please try to include the
court cases involving the city of Baltimore using aerial imagery for revising property
tax. Another interesting case related to a Hollywod personality and aerial imagery.
Consider examining the following papers relating to health information and HIPPA:
(a) M. P. Armstrong et al, Geographically Masking Health Data to Preserve
Confidentiality, Statistics in Medicine, 18, pp. 497-525.
- Group G2: Summary and list of reading on spatial outlier is reasonable.
- Group G3: Summary of reading is not in the desirable form.
See the general comment.
The list of readings is quite large and it may
be possible to shorten it after defining the focus of the project.
- Group G4:
Please post pdf documents inplace of postscript.
Nice categorization of indexing methods for spatio-temporal data.
The list of reference is reasonable. It may be useful to look at the chapter
on spatio-temporal indexing in the chorochronous workshop proceedings in our
reading list.
- Group G5: See general comment. In addition, the summary of reading list
does not summarize all the papers listed in the reading list.
Have searched DBLP and cite-seer?
- Group G6: The list of reading a bit broad. Consider focussing on outlier detection
techniques and their application in identifying anamolies in maps.
- Group G7:
Can not locate either a list of readings or a summary of the
readings. Good summary of related work. However, the list of readings
is a bit short. It may help to examine other spatial join algorithms including
tree-matching, space partitioning, plane-sweep, etc. and evaluate those for
for the problem at hand.
- Group G8: List of readings and the summary look reasonable.
Text summarizing the related work is in the right form and has addressed
the general comment.
- Group G9:
Can not locate either a list of readings or a summary of the
readings.
Feedback provided in the office hours. Please expand the reading list to include
papers (e.g. those by C. Brodley) on use of decision trees for classifying remote
sensing imagery.
- Group G10: See general comment. Current literature survey is a list of summary of
individual papers. Please rewrite it to create a classification structure to describe
entire literature in a paragraph or two.
- Group G11:
See general comment.
Nice categorization of logical data models for spatio-temporal data.
Feedback on Web-pages
General Comments :
- Page format : Group G2 has an easy to follow format for the overall web page.
It is recommended that each group follow a similar style.
Feedback on Paper Analysis Slides
General Comments :
A few comments apply to multiple papers. These comments are summarized
below:
- A. A cover slide should include a citation (e.g. title, author, publication forum,
year, etc.) to the paper you are presenting. Cover slide should also include information about
the team, including the names of members, group's webpage url, etc.
Motivation slides should either
list application domains
or long-standing open problems in the field of spatial databases.
- B. Use phrases instead of complete sentences.
Each phrase should be 6 to 8 words. You may omit articles and
reword phrases to reduce the number of words. Remember the slides
are providing highlights and you would be able to fill in the details
in the oral presentation.
- C.
Limit the amount of text on each slide to 6 to 8 phrases.
Too much text forces the audience to read the text
and prevents them from listening to you.
Consider covering parts of the slides with too much text
during presentation.
- D.
Put a slide on "outline" listing the major groups of slides.
Know the number of slides in each group.
Time your presentation to know the amount of time you spend in
presenting the slides in each group. This will allow you to complete
the presentation on time.
- E.
Problem statement slide should identify four things:
inputs (what information is given),
outputs (what solution is to be found ),
objectives (how does one judge the quality of solution),
and constraints (which assumptions can be made on inputs and environment).
Problom definition should be
stated in a way that allows solutions other than
what authors have proposed. This is fundamental
to understand and critique any paper without being biased by the
assumptions/biases of the authors.
Many research papers will have a section on problem statement identifying
these components. Others will list assumptions in scope, experiment design,
proofs of theorems and lemmas, proposed algortihms/methods etc.
If this information is missing, you should try to come up
with best guesses for these components.
- F.
Key concepts should be defined and explained. Consider using examples
and figures in explaining the key concepts.
Use examples from paper. In addition you may ad new examples.
You may refer to figures in the
papers by proving figure numbers and page numbers.
Figures should be simple with few (e.g. half a dozen) components.
Consider using 3 to 5 slides on key concepts since audience should
understand these well to appreciate rest of your analysis.
- G.
A validation methodology allows researchers to back up their claims in an
objective manner. It allows readers to reproduce the results and conclusions
of the authors. This is a fundamental requirement for science and
scientific methods. Common methodologies used in computer science research
include the following:
- Software protoypes and implementations for use by a user community.
Papers often quote popularity of the system and testimonials from
users. Example include first implementations
of Unix, Ingres, mosaic, terraserver (paper 21),
Geominer (paper 3) etc.
- Experimental evaluation of design decisions using a prototype of a
simulation model (e.g. queuing model, algebraic cost models).
Example include papers 8, 14, etc.
It is useful to provide some details of the experiment design,
e.g. benchmark data/queries,
fixed/variable parameters, candidates evaluated and simulation model.
- Theoretical proofs of correctness, computational complexity,
Examples include papers 10, 15 etc. Nature of the proof (e.g.
contruction, contridiction, reduction...) may be discussed.
- Examples, detailed examples, case studies of real usages are used
for concepts where more formal validation may be difficult or
too early to do. Data modeling papers often use this.
Other examples include harvard case studies.
- Surveys of experts and statistical analysis
- Assumptions, Rewrite Today:
It is good to add the these two slide to
distinguish between the conclusions of authors and your conclusions.
Comments on individual groups
- G1: Cyber-infrastructure
Slides are not posted as of 2pm on 2/11/04.
- Coverpage slide:
- Motivation slide: Missing. Describe a few applications of cyber infrastructure. See
general comment A.
- Problem Statement: Missing. Try to define the problem, cyber-infrastructure is
trying to solve using general comment E.
- Contributions: Missing. List a couple of contributions of this report, e.g. definition
of the concept of cyber-infrastructure and recommendations to identify
generic research challenges/issues.
- Key Concepts: Reasonably well done. It may help to add more detailed example, pictures
etc.
- Validation Methodology: Missing. Use general comment G.
- Assumptions: Missing slide. Does the report report capture the notions discussed
in national geo-spatial infra-structure, e.g. base maps need for emergency response?
- Rewrite Today: Missing. Think about adding
Try to analyze if the report recommendation
captures cyber-infrastructure needs of geo-spatial applications, e.g. EOS-DIS, Digital Earth,
Spatial location sensing, etc.
- G2: SQL/SDA
- Coverpage slide:
- Motivation slide: revise as per general comment A.
- Problem Statement: Revise "Find" part to replace SQL/SDA by "extensions to SQL".
Refine objectives to include "ease of expressing spatial questions".
Refine constraint to include OGIS data types and operations.
- Contributions: missing
- Key Concepts: Key concepts are to the main concepts behind the approach proposed by the
author. Try to explain the nested FROM clause and how it is used to model spatial properties.
- Validation Methodology: See general comment G. Does this paper use a set of examples?
Does it use language specification tools, e.g. grammars? Dis it perform user studies to evaluate
the ease of expressing spatial queries ?
- Assumptions: Missing slide
- Rewrite Today: Missing slide
- G3: - MOSTD 2.3 LBS (Mokbel et al.)
- Coverpage slide: Cite the paper being presented.
- Motivation slide: See general comment G1. List applications of LBS.
- Problem Statement: missing
- Contributions: missing
- Key Concepts: Explained in details using several slides. It will help to provide pictures
and concrete example.
- Validation Methodology: missing.
- Assumptions: Missing. You may use parts of last two slides for this purpose.
- Rewrite Today: missing.
- G4: Access Methods for spatio-temporal databases
- Coverpage slide: Complete citation of the paper being presented by providing name of the
book, authors, etc.
- Motivation slide: Missing.
- Problem Statement: Reformat using general comment E.
- Contributions: Quite good. List specific contributions, e.g. survey, classification schemes etc.
- Key Concepts: Good details of R-tree and Quad tree based methods with pictures.
- Validation Methodology: missing.
- Assumptions: Slide has too much detail. It may best to refer to the tables/figures in
the paper on the slide. You need not reproduce those. The slide should be used to list
a couple of major assumptions, e.g. do they assume that the object is not deformable?
- Rewrite Today: missing. May use material from the last slide. Also check if the literature
survey is uptodate using cite-seer and DBLP.
- G5: SQL/SDA
Link does not work as of 430pm on 2/11/04. Please check permissions, url etc.
Oral feedback on paper copy of the slides was provided on 2/19/04.
- Coverpage slide:
- Motivation slide: Provide specific application domain of spatial query languages.
The paper itself may list some.
- Problem Statement:
- Contributions: It is useful to list the contributions claimed in paper. However, do
provide your opinion if you agree with the claimed contributions or not.
- Key Concepts: It may be useful to compare the spatial model (e.g. data types, operations)
of this paper with OGIS model. Highlight and explain the differences.
- Validation Methodology:
- Assumptions: Missing slide.
- Rewrite Today: Identify a couple of improvement to the basic solution presented in
the paper.
- G6: Geo-spatial data authorization
- Coverpage slide: Very good.
- Motivation slide: missing
- Problem Statement: revise using general comment E.
- Contributions: missing
- Key Concepts: Quite good. Detailed description with multiple slides.
- Validation Methodology: missing
- Assumptions: Last slide seems to address it.
- Rewrite Today: Missing. Consider looking at the book titled "Spying With Maps: Surveillance
Technologies and the Future of Privacy - University of Chicago Press, Mark S. Monmonier" to
think out other related problems and to evaluate the solutions proposed by the author.
- G7: Direction as an object
- Coverpage slide: Reasonable.
- Motivation slide: List a few concrete application domains.
- Problem Statement: missing
- Contributions: missing
- Key Concepts: Several slides. Consider adding a few pictures and concrete examples.
- Validation Methodology: missing
- Assumptions: Missing
- Rewrite Today: missing. It should include you own ideas beyond those listed in the future
work section of the paper.
- G8: 9-intersection model
- Coverpage slide: Good.
- Motivation slide: missing. List a few application domains.
- Problem Statement: Follow the general comment E.
- Contributions: Expand to a full slide. Identify sub-contributions.
- Key Concepts: Quite detailed. Do put in the figures. Exercise slide is a nice touch.
- Validation Methodology: Use a category listed in general comment G.
- Assumptions: Provide a little more detail. For example, provide an example
3D object relationship that is not covered by the model presented in this paper.
Similarly, provide more details of the implication of finite precision on the
model presented in this paper.
- Rewrite Today: Reasonable. Consider the choice of validation methodologies as well.
Would you use a different methodology?
- G9: Colocation mining
- Coverpage slide: reasonable
- Motivation slide: missing. Provide a few concrete application domains.
- Problem Statement: Reformat using general comment E.
- Contributions: Quite good. Do bring it before key concepts.
- Key Concepts: Several slides. Consider adding examples for each concept.
- Validation Methodology: missing.
- Assumptions: Missing
- Rewrite Today: missing
- G10:
- Coverpage slide: missing.
- Motivation slide: Quite reasonable. Consider adding applications (e.g. mapquest) that
everyone can related with.
- Problem Statement: Reasonable. Consider refining "objective" by specifying a measure, e.g.
cost, distance, travel-time, etc.
- Contributions: Good.
- Key Concepts: Quite good. Nice to see examples.
- Validation Methodology: Slide 11 shows this information. However, it will be nice to
describe it at a high level using a category from general comment G.
- Assumptions: Missing slide
- Rewrite Today: missing
- G11: Ontology and spatio-temporal databases
Format the slides using powerpoint or other slide-making software
for presentation.
- Coverpage slide: Reasonable. Do cite the book as well.
- Motivation slide: missing. List a few application domains.
- Problem Statement: Reformat using general comment E.
- Contributions:
- Key Concepts: Quite good. Consider adding examples.
- Validation Methodology: Reasonable. Do relate to categories listed in general comment G.
- Assumptions: Elaborate a bit by providing examples where social reality and physical
reality are identical.
- Rewrite Today: Quite nice. May consider expanding the list of revisions by looking at other
validation methodologies, e.g. case studies.