Paris trip advisor 1909: Difference between revisions
Jump to navigation
Jump to search
Line 38: | Line 38: | ||
== | == Project Plan and Milestones == | ||
=== Milestone 1: Concept (4 Nov) === | |||
* | === Milestone 1: Concept (up to 4 Nov) === | ||
*First brainstorming and first sketch of ideas | |||
*Exploring the sources and the map | *Exploring the sources and the map | ||
*Elaboration of the overall | *Elaboration of the overall concept | ||
===Milestone 2 : Data extraction (9 Nov)=== | ===Milestone 2: Data extraction (9 Nov)=== | ||
* Scheduling and | *Scheduling and drawing up the project plan | ||
* | *20% of the data extracted and annotated | ||
*Verification of the data quality | |||
===Milestone 3 : Design and Data Processing (14 Nov) === | ===Milestone 3: Design and Data Processing (14 Nov) === | ||
* Selection of features | * Selection of features |
Revision as of 08:34, 13 November 2018
The project aims to digitalize the Plan des plaisirs et attractions de Paris created by Le Nature in 1909, and to augment it with the information contained in the Guide dés plaisirs à Paris. The services that would be provided are the display of cultural places in the map that have linked pages with individualized further information, the segmentation on the map of different types of entertainment and an "exploratory mode" which would tell a narrative on a specific moment in 1909 in Paris.
Motivations
Recreating a cultural geography of Paris at the beginning of the 20th century
Ideas
- Mapping places on the map to their information on guide:
- Show pages containing the name of the place
- Adding more information about places
- Compare each attraction to the contemporary place
- Image of building in past and now
- Giving a general view about attractions in Paris in 1909:
- Show restaurants, bars, theaters in different groups to see the distribution of them.
- Show information about opening hours and prices
- Mapping narrative of guide to route on the map.
- Show routes and walking tours
Resources
Principal Resources
Additional Resources
Data extraction
Reading guide to extract engaging narratives to recommend users
Solution
Implementing a website with a database using Python, Django, and PostgreSQL to:
- Entering information about places manually to store in database
- Exploring map UI and use services
Project Plan and Milestones
Milestone 1: Concept (up to 4 Nov)
- First brainstorming and first sketch of ideas
- Exploring the sources and the map
- Elaboration of the overall concept
Milestone 2: Data extraction (9 Nov)
- Scheduling and drawing up the project plan
- 20% of the data extracted and annotated
- Verification of the data quality
Milestone 3: Design and Data Processing (14 Nov)
- Selection of features
- Improvement of map
- Design prototype on paper (wireframes)
- Finding the best technical way to show clickable points corresponding to places, to their location on the map image.
- Prepare midterm presentation
Milestone 4: Database implementation (28 Nov)
- Develop a web app for entering pieces of information:
- Initialization of Django application
- Design and Implementation of the database in SQL
- Deploy the first version of the web application: The Developed website will be deployed on a public URL and team members will have access to input extracted information to the database.
- Extraction of rest of data
- Implementation of database
- Entering information to the app database
Milestone 5: Development of the platform (14 Dec)
- Design final product
- Design entry story
- Find and Add more metadata about places
- Refactoring the github repository to submit
- implementation of services on the web app:
- Show basic map and description about project
- Implementation of UI to explore the map and places
- Add search and filter functionality
- Show information about each place
- Add a specific page for recommendations
- Add feature of commenting/ Liking
Milestone 6: Presentation (19 Dec)
- Prepare final presentation
- Write report
- Deployment of the final version of the web application for public usage
Team
- Alina, Maryam, and Paola