first push for readme

README.md

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-# LinkedBooksReferenceParsing
+# LinkedBooksReferenceParsing: Annotations Dataset and CRF Parsing
+
+TODO Zenodo
+[![DOI](https://zenodo.org/badge/79789632.svg)](https://zenodo.org/badge/latestdoi/79789632)
+
+A dataset of annotated references (in both reference lists and footnotes) from journal issues and monographs on the history of Venice, created in the context of the [LinkedBooks project](https://dhlab.epfl.ch/page-127959-en.html). 
+
+Along the dataset of annotations, a framework to train your own parsers is provided, based on Conditional Random Fields. Feel free to use it to build your own parser, and if you improve on our results, please let us know!
+
+## Contents
+
+TODO
+
+* `LICENCE` MIT
+* `README.md` this file
+* `Plots.ipynb` a Python notebook to replicate figures 3 and 6 from the article
+* `dataset/`
+ * [citation_data.json](dataset/citation_data.json) the citation dataset among monographs on the history of Venice
+ * [data_description.md](dataset/data_description.md) describes in detail the contents of `citation_data.json`
+ * [directed_edges.csv](dataset/directed_edges.csv) the edgelist of the directed citation network. Sep. `;`, Quote `"`. Columns: `"Source";"Target";"Type";"Year"`
+ * [directed_nodes.csv](dataset/directed_nodes.csv) the nodelist of the directed citation network. Sep. `;`, Quote `"`. Columns: `"Id";"Bid";"Title";"Author";"LB";"Year";"Consultation"`
+ * [list_citing_monographs.csv](dataset/list_citing_monographs.csv) the list of parsed monographs, from which citations were extracted. Sep. `;`, Quote `"`. Columns: `"id";"bid";"title";"author";"year";"extracted unique citations"`
+ * [node_stats.csv](dataset/node_stats.csv) the in and outdegree distribution of each node in the network. Sep. `;`, Quote `"`. Columns: `"id";"bid";"title";"author";"lb";"year";"consultation";"indegree";"outdegree";"degree"`
+ * [territorio.csv](dataset/territorio.csv) basic information about all libraries in the Italian Library System (e.g. library code, coordinates. etc.). This data is openly available at <https://opendata.anagrafe.iccu.sbn.it/territorio.zip>.
+
+## Running the notebook
+
+Assuming that Python is already installed (tested with version 3.5.0), the following depencies need to be installed as well (it will take a moment):
+
+ pip install seaborn, jupyter, numpy, scipy, sklearn, sklearn_crfsuite
+
+Then launch the notebook server with
+
+ jupyter notebook
+
+A new browser/tab will open pointing at Jupyter's starting page.
+
+## Linked Books Team at EPFL, DHLAB
+Giovanni Colavizza, Matteo Romanello, Martina Babetto, Silvia Ferronato.
+
+## Acknowledgements
+This work would not have been possible without the help of several Italian institutions of culture. 
+In alphabetical order we thank: the Ca’Foscari University Library System and the Ca’Foscari University Humanities Library (BAUM), the Central Institute for the Union Catalogue of Italian Libraries and Bibliographic Information (ICCU), the European Library of Information and Culture (BEIC), the Istituto Veneto di Scienze Lettere ed Arti, the Marciana Library, the State Archive of Venice.
+
+The project is supported by the Swiss National Fund, with grants 205121_159961 and P1ELP2_168489.
+
+## Please cite as
+
+Giovanni Colavizza, Matteo Romanello, Martina Babetto, Silvia Ferronato. (2017). dhlab-epfl/LinkedBooksReferenceParsing: LinkedBooksReferenceParsing (version 1.0) [Data set]. Zenodo. TBD
+
+ @misc{colavizza_annotations_2017,
+  author = {Giovanni Colavizza, Matteo Romanello, Martina Babetto and Silvia Ferronato},
+  title = {{dhlab-epfl/LinkedBooksReferenceParsing: 
+  LinkedBooksReferenceParsing (version 1.0)}},
+  month = may,
+  year = 2017,
+  doi = {TODO},
+  url = {TODO}
+ }