A Notion template to help you keep track of the papers you read, their authors, your notes and more 🚀⚡🔥
This project was built as a Notion-based alternative to reference management softwares such as Zotero and Mendeley.
It is composed of the NoRA Notion template for you to build on top of, as well as NoRA-Tools to programmatically:
- 🔥 programmatically upload papers to your NORA library from arxiv, Elsevier Scopus, Springer, or HAL
- 🔥 move all your Zotero library to your NoRA library
The NoRA template provides you with a structure of interconnected databases to keep track of your research papers and notes. More specifically, the template contains the following databases:
🏗️ Projects📜 Papers👤 People🏢 Affiliations🤹 Conferences & journals🧲 Key topics
The inner workings of the template are quite straightforward, the best way to get familiar with it is probably to play with it 😉 !
The NoRA-Tools provide functionalities to programmatically upload data to your NoRA template. For now, the main functionalities are:
- uploading an arxiv paper (and associated metadata) to NoRA
- uploading an Elsevier paper from Scopus (and associated metadata) to NoRA
- uploading a Springer paper (and associated metadata) to NoRA
- uploading a HAL paper (and associated metadata) to NoRA
- uploading your whole Zotero library to NoRA
You can freely modify or extend the NoRA template. However, keep in mind that if you want to use NoRA-Tools after modifying some sensitive page fields, you will need to adjust your Notion configuration accordingly.
Simply duplicate the NoRA template to your personal Notion account.
First, install the NoRA-Tools locally on your machine.
# clone project
git clone git@github.com:drprojects/nora.git
cd nora
# create a 'nora' conda environment with required dependencies
conda env create -f nora.ymlNext, you will need to configure your NoRA-Tools to connect to your NoRA databases in Notion. To this end, follow the official guide to Create a Notion Integration. Following all steps in this page you will:
- Create an integration and get a Token
- For each database in the NoRA template:
- Share the database with your integration
- Save the database ID
You can then save the Token and the database IDs in the configs/notion/default.yaml file:
# Adapt to your own Notion library.
# See https://developers.notion.com/docs/create-a-notion-integration
token: "your_integration_token"
papers_db_id: "your_papers_database_id"
people_db_id: "your_people_database_id"
affiliations_db_id: "your_affiliations_database_id"
venues_db_id: "your_venues_database_id"
topics_db_id: "your_topics_database_id"⚠️ Want to modify some field names in NoRA ?️
By default, NoRA-Tools expect the attribute fields (eg column names in Notion) of your papers, people, etc. to have specific values.
If you want to adjust those, you will also need to adjust the configs/notion/default.yaml file:
# If you happen to modify your field names in Notion, update the
# following database-specific keys
person_keys:
name: 'Name'
affiliations: '🏢 Affiliations'
papers: '📜 Papers'
website: 'Website'
paper_keys:
name: 'Name'
authors: '👤 Authors'
abstract: 'Abstract'
topics: '🧲 Key topics'
url: 'URL'
to_read: 'Reading status'
year: 'Year'
venue: '🤹 Venue'
affiliation_keys:
name: 'Name'
venue_keys:
name: 'Name'
⚠️ Want to add your own 🤹 Conferences & journals ?️
By default, when parsing a paper from a remote database, NoRA-Tools will try to
figure out which 🤹 Conferences & journals to place it under. However, one
can hardly account for all possible conference and journal names, nor for all
the slight formatting differences used to describe how a paper was published.
Yet, we attempt to group the most frequent ones using a predefined VENUES
dictionary in src/utils/venues.py.
If many papers from your library are from a conference or journal absent from
this dictionary, and you would like them to be grouped under the same
🤹 Conferences & journals item, you can simply append your own entries in
VENUES, using the following format:
'lowercase_match_to_search_for_in_remote_metadata': 'shorthand_under_which_to_group'If you intend to upload papers from Elsevier to Notion, you will need to configure your NoRA-Tools accordingly. To this end, you will need to create an Elsevier API key.
You can then save your Elsevier API key in the configs/elsevier/default.yaml
file:
# Adapt to your own Elsevier account.
# See https://dev.elsevier.com
api_token: 'your_api_key'If you intend to upload papers from Springer to Notion, you will need to configure your NoRA-Tools accordingly. To this end, you will need to create a Springer API key.
You can then save your Springer API key in the configs/springer/default.yaml
file:
# Adapt to your own Springer account.
# See https://docs-dev.springernature.com/docs
api_key: 'your_api_key'If you intend to move your whole Zotero library to Notion, you will need to configure your NoRA-Tools accordingly. To this end, you will need to:
- Get your Zotero library ID by checking the UserID in your profile settings
- Create a Zotero API key in your profile settings
You can then save your Zotero library ID and API key in the
configs/zotero/default.yaml file:
# Adapt to your own Zotero library
library_id: 'your_library_id'
api_token: 'your_api_key'By default, the collections (eg folders) in your Zotero library will be used to
populate the Key Topics field of your papers in NoRA.
If you want to exclude some of your collections from this behavior, your can list
them in:
ignored_collections: ['collection name 1', 'collection name 2']If your machine has a proxy, you will need to configure your NoRA-Tools to use it.
To this end, specify your $HTTP_PROXY and $HTTPS_PROXY in the
configs/proxy/default.yaml file:
http_proxy: 'your_http_proxy'
https_proxy: 'your_https_proxy'From its arxiv ID:
python nora.py arxiv.id=2204.07548From its URL:
python nora.py arxiv.id=https://arxiv.org/abs/2204.07548From its title:
python nora.py arxiv.title="Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"From its PII ID:
python nora.py elsevier.id=S1569843222000656From its URL:
python nora.py elsevier.id=https://www.sciencedirect.com/science/article/pii/S1569843222000656From its DOI:
python nora.py elsevier.doi=10.1016/j.jag.2022.102863From its DOI:
python nora.py springer.doi=10.1038/d41586-019-02841-9From its URL:
python nora.py springer.url=https://www.nature.com/articles/d41586-019-02841-9From its HAL ID:
python nora.py hal.id=hal-03824190v1From its URL:
python nora.py hal.id=https://hal.science/hal-03824190v1From its title:
python nora.py hal.title="Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation"python nora.py zotero.upload=TrueNoRA is licensed under the MIT License.
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Copyright (c) 2023-2024 Damien Robert
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