arthurmde / hackathon-ime-2017

Colab Research

This project was developed during the Hackathon USP 2017

Inspiration

We believe that collaboration is the key factor for impactful high-quality research. CollabReSearch is a platform to support you in the hard task of finding potential contributors to leverage your research and career!

What it does

Collab Research is a search engine to help you find potential contributors to leverage your research. The results are shown in a georeferenced map with 3 dimentions:

• Location - This can be seen in the map presented by the platform
• Relevance of the researcher publications in the area matched by the query string - This is represented by the color of the circle representing the researcher (Green > Yellow > Orange > Red)
• Productivity and citation impact of the researcher - Represented by the size of the circle representing the researcher (the bigger the circle, the higher his/her hindex)

The user can click on the circles representing the researchers to get more information about them, like

• hindex value
• Affiliation
• Total number of citations
• Areas of interest
• Links to Scopus and Google Scholar profiles
• Google Scholar profile picture

How we built it

Since we did not have any access to CNPq's Lattes data (unfortunately the date is not open for machines and require captchas to be accessed) we needed to use 3 different data sources to retrieve all the data needed to complete this prototype:

• Mendeley
• Scopus
• Google Scholar

First, we retrieve articles matching the queries entered by the user (relevance provided by Mendeley). Then we retrieve all the authors of those articles and give them points based on the number of views for the matching papers, also provided by Mendeley. Finally, we query Scopus (API) and Google Scholar (scrapper python lib) to retrieve more information about each researcher.

Since Scopus API is important to our process and it is quite slow, unstable, and expensive, we decided to display at most 10 researchers in the map.

We used the Python programming language to fetch our data and provide a back-end to our application using the Flask framework.

We used Google Maps API to plot our data and the Material Design Light library to make our front-end.

Accessing APIs

Scopus

You need a scopus API token, then you should

• create the ~/.scopus/my_scopus.py file with

`MY_API_KEY='YOUR_KEY_HERE'

Note that this API does not provide free access. Chances are you can create a token and access it from inside a University (we did it from Universidade de São Paulo)

Mendeley

You will also need a Mendeley API

Your config.yml should look like

accessToken: YOUR_ACCESS_TOKEN

Note that Mendeley API expires every 1 hour. There is a way to auto-refresh it, but we never got the time to implement such feature during the Hackathon.

License

Copyright 2017 The AUTHORS

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

AUTHORS

• Arthur Del Esposte
• Athos Ribeiro
• Lucas Kanashiro