Tag Archives: geodata

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Fashion Index Weekly Update

During this semester, we have been working on collecting collection of python and Instagram scripts and interacting with database.

We added the “game” function, which will be an ethos of our website, based on bootstrap. The game refers to the indexing page on the website as well. We believe the index page will show a curatorial power to the users. The game will let the participation. In this respect, our group is aiming to get more interactions. User engagement plays a critical role in this project.

We are planning to tag more and archive more images in order to have deeper historical contents. On the images, we have to attach longitude, latitude, time information, and URLs.

 

manhattan_nyfw_csv

We are thinking about how we can contribute to both fashion studies students and DHers. The way we collect images pulling out from Instagram, crowdsourcing, is a totally community facilitated process. We observe latent people in community and interest. Community building is an integral part because it will generate new types of communication among different users.  In the end, we will hit  other parts of fashion world e.g.) Paris, London, etc. Also, we try to moderate and curate the data.

We have been discussing the possibilities and prospects of our theme in terms of layer of interaction of fashion. What extend in concern of this field? and we are questioning the power of fashion world.

 

 

 

Fashion Index weekly update

All of our tem members have been working so hard during the break. We have also faced certain restrictions.

#Sprezzatura tag search was not working well with the NYC latitude and longitude data that we were looking for. We decided to choose a more fashion-themed tag that already pulled images from NYC. We made an alternative plan to focus on the tag #NYFW (New York Fashion Week). This would be our MVP (Minimum Viable Products).

excel files

Tessa highlighted the fields that will be relevant for CartoDB including Latitude/ Longitude and created time. She adjusted for NY time zone. She also included the image URL.

Minn updated Carto DB. He posted the images based on NYC open data. First, he custom designed the 5 boroughs of map on Mapbox then exported into CartoDB. Later on,  he filled 5 boroughs of New York with polygons. Lastly, he placed pins on specific areas.

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latlong

 

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