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Group member:

IT: Fabian Moreno IM: Jesus Mario Verdugo IM: Enrique Batani

Meeting of the 14th Oct 2014:

Brainstorming to find ideas on open data service:


  • Application area
  • Buses are empty for certain time schedules on a daily basis.
  • Optimize costs of transport
  • Reach areas and streets that currently don’t have public transportation routes.
  • Restrictions
  • Maintain SLA.
  • Not reducing the frequency of time table.
  • Offering as much seats as needed.
  • Maintain or reduce user price.
  • Work methodology
  • Feasibility study
  • Value proposition
  • Assigning different bus sizes to different routes or time frames.


  • Application area
  • Problem. uncertainty to decide what to study
  • Needs. Improve assertiveness of career choosing
  • Restrictions
  • People chooses money rather than their fields of interest
  • Depending on the career the courses are more expensive.
  1. People is limited to study something that offers them a job where they live.
  2. Local recognition of the area of studies
  3. Perceived difficulty of the area.
  4. Misconceptions of the careers.
  5. Preparation for the admission tests.
  • Beurocracy and corruption in the admission process
  • Work methodology
  • Feasibility study
  • Value proposition

A platform to advice high school new graduates to find the right career based on certain criteria, such as afinity, average salary of graduates, number of vacancies available in the labor market, programs offered in universities, and tuition fees.


  • Detect and prevent corruption in politics
  • Identify signs or traces of corrupted activity.
  • Information gathering must be free
  • Value proposition
  • Raise of flags when identifying suspicious behavior
Outcomes of meeting

After evaluating the possible projects and their impact in the society we decided that the topic “Politics” with our proposal to raise flags in possible corruption cases is the most relevant.

  • Finalize reading all training material in Open Data.
  • Identify more opportunities for the political model.
  • Working method selection.

Our next meeting is on 16.10.2014.

Meeting of the 16th Oct 2014:

Today's meeting was to present the results to the teacher and get feedback on which way to proceed based on the proposals of business ideas using Open Data.

Results of the meeting

  • The outcome of the meeting was to discard the transportation project since there are currently many other projects related to that issue.
  • Second comment was to identify carefully who would be the possible customer for the transparency project (politics).
  • Last comment was to identify carefully which information we want to show and if we wanted to keep students motivated, because if we show that job salaries by area of studies we would be influencing the choice of the students by the money, which is what we want to prevent.

Our next meeting is on 27.10.2014.

Meeting of the 27th Oct 2014:

Organizing presentation based on elements of elevator pitch
  • problem
  • solution
  • customer
  • segment
  • finance
  • team
  • competitors
  • milestones
Further development of Politics


  • Corruption
  1. Definition
  2. Types of corruption

Conflict of interests, Influence peddling, Purchases, Fake name registering.

  • Transparency
  1. Corruption


  • Algorithm
  1. Definition

Politics, Patterns

  1. Input: open data
  2. Output: flags
  • System
  1. software
  2. machine
  3. propietary
  4. closed


  • Common good
  • People
  • Values
  • Reducing time in analysis for corruption
  1. Avoid losing time where there is no risk of corruption
  2. Look for corruption only where there are flags
  • Customers and monetization
  • monetization
  1. contractor
  2. politicians

Warn about their mistakes and risk movements, Advise on their competitors.

  1. media


  • Affected
  1. Politicians
  2. Administration
  3. Third parties
  • Other measures
  • Constraints
Work on hook arguments for elevator pitch

Corruption is one of the leading concerns in the . But, what if we could identify these signs and backtrack over its trace until we can determine whether a suspicious behavior is an actual act of corruption? we know about the corruption from the media, but what about the corruption we never get to hear from?

  • Add more elements for elevator pitch.
  • Add supportive statistics.
  • Review more information about NABC.
  • Work on better hook arguments

Our next meeting is on 29.10.2014.

Sources of Opendata
  • Civil registration
  • Registration of companies
  • Tax Offices
  • Institutes of statistics
  • Budget and salary of Politicians and public workers

* Depending on the country the sources and their URLs vary.

Meeting on 29.10.2014
Outcome of the meeting

Statistics that support model:

  • Research has shown us that people's perceptions offer a reliable estimate of the nature and scope of corruption in a given country. By its nature, corruption is secretive and complex.
  • The perceptions of country analysts, business people or the general public form the basis of our corruption indices, the Corruption Perceptions Index and the Global Corruption Barometer of the Transparency Organization are two reliable sources to measure the global corruption.
  • Global Corruption Barometer 2013 (Results of a Transparency International survey of more than 114,000 respondents in 107 countries)

Key Findings:

  • 27% report having paid a bribe in the last 12 months when interacting with key public institutions and services
  • The police and judiciary are seen as two most bribery-prone
  • Two out of three people believe that personal contacts and relationships help to get things done in the public sector in their country
  • 54% think their government is largely or entirely run by groups acting in their own interest rather than for the benefit of the citizens
  • Nearly 9 in 10 surveyed say they would act against corruption
  • The majority of people said they would be willing to speak up and report an incident of curruption
  • Two-thirds of those asked to pay a bribe say they refused
  • 53% of the people surveyed think that corruption has increased or increased a lot over the last two years.
  • Political parties were seen to be the most corrupt institution, scoring 3.8 on the scale of one to five
  • 54% consider their government to be ineffective at fighting corruption
  • 67% believe that ordinary people can make the difference in the fight against corruption
Sources of information

Development of Idea

Corruption is one of the leading concerns in the democratic world. Its perception varies among countries but there is one constant: most of the corrupting actions undergo unnoticed and are not prosecuted. Authorities can act against corruption once suspicious actions are known. Unfortunately most of these actions will never be investigated. But, what if we could automatically identify these signs and backtrack on their traces until we can determine whether a suspicious behavior is an actual act of corruption?

People with different levels of power can exploit the vulnerabilities of the system to benefit other than the common good. Politicians, public workers, contractors… all are subject to behave inappropriately. They can abuse the system in different ways, namely by conflict of interests, influence peddling, fake name registering or purchases. Once they are caught an investigation begins to trace all the cables connecting their suspicious behavior.

We have an idea to invert this flow. Suspicious behavior is analyzed to raise flags that would lead to further investigation. This is automatically done by an algorithm that takes data from different sources as the input to our system and analyzes it dynamically to produce reports that give the details of the mentioned suspicious behavior and their connections. This input is mainly based on open data offered by public institutions but will also be improved by pattern analysis so that the system refines its accuracy and improves its output over time.

This system is proprietary and is managed by our organization. We offer the reports in exchange for money to those interested in the information we can provide. We have the ownership of the machines and software and it will never be public knowledge given its closed nature.

We offer different value propositions depending on the customer segmentation. Potential customers are: Government

  • Unordered List Item
  • Public instituions
  • Media
  • NGOs
  • Concerned third parties

Our system reduces the costs of time and effort for our customers when it comes to investigation. It also saves common wealth by reducing inadequate spendings.

There is not clear competence in this market, but there are environmental factors that would potentially constrain the scope or deployment of our system. Some politicians would not like to be analyzed because they can feel threatened. Some others would not agree with this systematic approach.

Our next meeting is on 29-NOV-14 with the professor.

Meeting of the 29th Oct 2014:

Today's meeting was to present in the elevator pitch format the presentation with the development of the ideas to get feedback and be able to tune our material for the final presentation to the teacher and classmates one week after this day.

Results of the meeting

Following points were taken as feedback from the teacher:

  • Presentation was out of time by exceeding 2 minutes of time but the idea was good.
  • Suggestions were raised to offer related products for preventing the corruption to happen by analyzing the possible flags of a decision to be met before it's taken.
  • We were encouraged to look for environmental sustainable applications using open data with the algorithm.
  • Reinforce the point of the result of the application rather than in the algorithm that calculates everything.
  • Next meeting to prepare 1 slide only to present for the elevator pitch, but we all will present 15 minutes presentation with other students, for the second presentation we may use more slides.

Our next meeting is on 03-NOV-14.

Next meeting on 03-NOV-14

Meeting on 03-NOV-14

  • Prepare elevator pitch presentation
  • Prepare 15 minutes presentation
  • Rehearse presentations
Final presentation on 03-NOV-14

Final date of presentation was updated to the 13-NOV-14

Final presentation on 13-NOV-14

Please find the file for the presentation below.


From the selling pitch presentation we got the following results:

Green (Buying) - 5/6

Red (Not buying) - 1/6

  • The arguments on which this negative response was based were wrong since the opposite concepts were explained during pitch and as a response from our team the concepts were mentioned again for the student and audience to clear any doubt.
  • Arguments:
  1. People will need training. Fact: No training needed since customers only get the report.
  2. Why to trust the results ?. Fact: The report doesn't tell you to trust or not if it's corruption, it only indicates which happenings are suspicious (and why), the “flags” should be analyzed so the customer tells by his judgement and knowledge.

Workload was splitted evenly and all members participated in all meetings.