Update README.md

README.md

@@ -3,11 +3,27 @@
 SuperCon 2 is the staging-area of [SuperCon](http://supercon.nims.go.jp), the 'de-facto standard' database of superconductors materials. 
 SuperCon 2, collect experimental data automatically extracted from scientific documents and provide a workflow to correct them efficiently and with high quality. 
 
-The SuperCon 2 interface and detailed in our paper: TBA
+The SuperCon 2 interface and detailed in [our latest paper](https://hal.science/hal-04198232) (currently in review).
 
 This repository contains:
 
 - The process to create the SuperCon 2 database from scratch, using [Grobid Superconductor](https://github.com/lfoppiano/grobid-superconductors) to extract materials information from large quantities of PDFs.
 - SuperCon 2 curation interface and workflow application for visualising and editing material and properties extracted from superconductors-related papers.
 - The documentation related to the usage of SuperCon 2, with notes, experiments and other information, acessible [here](https://supercon2.readthedocs.io/en/develop).
 
+Reference: 
+
+```
+@unpublished{foppiano:hal-04198232,
+ TITLE = {{Semi-automatic staging area for high-quality structured data extraction from scientific literature}},
+ AUTHOR = {Foppiano, Luca and Tomoya, Mato and Kensei, Terashima and Pedro Ortiz, Suarez and Taku, Tou and Chikako, Sakai and Wei-Sheng, Wang and Toshiyuki, Amagasa and Yoshihiko, Takano and Masashi, Ishii and Tomoya, Mato and Kensei, Terashima and Pedro Ortiz, Suarez and Taku, Tou and Chikako, Sakai and Wei-Sheng, Wang and Toshiyuki, Amagasa and Yoshihiko, Takano and Masashi, Ishii},
+ URL = {https://hal.science/hal-04198232},
+ NOTE = {working paper or preprint},
+ YEAR = {2023},
+ MONTH = Sep,
+ KEYWORDS = {materials informatics superconductors machine learning database tdm ; materials informatics ; superconductors ; machine learning ; database ; tdm},
+ PDF = {https://hal.science/hal-04198232/file/main.pdf},
+ HAL_ID = {hal-04198232},
+ HAL_VERSION = {v1},
+}
+```