update paper

paper/paper.bib

@@ -7,6 +7,17 @@ @inproceedings{gephi
 	year = {2009}
 }
 
+@article{cytoscape,
+  title={Cytoscape: a software environment for integrated models of biomolecular interaction networks},
+  author={Shannon, Paul and Markiel, Andrew and Ozier, Owen and Baliga, Nitin S and Wang, Jonathan T and Ramage, Daniel and Amin, Nada and Schwikowski, Benno and Ideker, Trey},
+  journal={Genome research},
+  volume={13},
+  number={11},
+  pages={2498--2504},
+  year={2003},
+  publisher={Cold Spring Harbor Lab}
+}
+
 @article{webweb,
 	title = {webweb: a tool for creating, displaying, and sharing interactive network visualizations on the web},
 	shorttitle = {webweb},
@@ -55,3 +66,11 @@ @inproceedings{graphviz
 	pages = {483--484},
 	file = {Citeseer - Full Text PDF:/Users/bfmaier/Zotero/storage/LS2KQZ99/Ellson et al. - 2001 - Graphviz {\textemdash} open source graph drawing tools.pdf:application/pdf;Citeseer - Snapshot:/Users/bfmaier/Zotero/storage/IXILUSLA/summary.html:text/html}
 }
+
+@online{developersurvey,
+	author = {Stack Overflow},
+	adress = {https://insights.stackoverflow.com/survey/2019?utm_source=so-owned&utm_medium=blog&utm_campaign=dev-survey-2019&utm_content=launch-blog},
+	title = {Stack Overflow Developer Survey},
+	year = {2019},
+	urldate = {2019-04-23}
+}

paper/paper.md

@@ -8,13 +8,13 @@ tags:
   - interactive
 authors:
   - name: Ulf Aslak
-    orcid: 0000-0000-0000-0000
+    orcid: 0000-0003-4704-3609
     affiliation: "1, 2" # (Multiple affiliations must be quoted)
   - name: Benjamin F. Maier
     orcid: 0000-0001-7414-8823
     affiliation: "3, 4"
 affiliations:
- - name : Centre for Social Data Science, University of Copenhagen, DK-1353 København K
+ - name : Center for Social Data Science, University of Copenhagen, DK-1353 København K
    index: 1
  - name : DTU Compute, Technical University of Denmark, DK-2800 Kgs. Lyngby
    index: 2
@@ -28,35 +28,19 @@ bibliography: paper.bib
 
 # Summary
 
-I'm just collecting some thoughts here
+Network visualization is an effective way to illustrate properties of a complex system. It is an important tool for exploring and spotting patterns, and is used by researchers and practitioners across many fields and industries.
+Currently, there exists a number of tools for visualizing networks. *networkx* [@networkx] is a popular Python package for network analysis which provides limited functionality for computing layouts and plotting networks statically. Layout computations are done in Python or using the php-based software *Graphviz* [@graphviz], which is slow. *Gephi* [@gephi] and *Cytoscape* [@cytoscape] are dedicated visualization and analysis software programs. They are both Java-based and runs desktop clients with a GUI, where users save and load networks as seperate files. *Webweb* [@webweb] enables interactive visualization for Python and Matlab networks using the d3.js [@d3] force layout. It's main purpose is exploration of network features and exporting one-time visualizations as SVG or HTML.
 
-* visualizing networks is an important part of communicating their structure
-* there already exist several tools to explore/visualize networks and their structure and properties.
-* "networkx" [@networkx] is the most commonly used Python package for network analysis
-* it provides visualization functions which are either slow or inconvenient as they
-  rely on third-party dependencies like "graphviz" [@graphviz], and use a
-  a variety of parameters. These parameters then have to be manually scanned, 
-  reproducing a new visualization for every changed parameter.
-* Gephi [@gephi] is mostly focused on both interactive analysis and visualization.
-  However, networks must be saved and loaded as separate files. Java has to be installed.
-  an automated view of a network which was previously manipulated in Python is not possbile
-* Webweb [@webweb] provides an interactive visualization for Python network objects based
-  on the force layout of d3.js [@d3], however
-  its main purpose is the interactive exploration of network features
-  and single-time visualizations:
-  the stylized network and visualization parameters may not be saved to be reproduced later.
-* Netwulf provides a simple interactive interface to stylize a network which was previously
-  manipulated in Python. 
-* Its philosophy is that network manipulation should be done programmatically (i.e. in Python)
-  but the efficient generation of a visually pleasing network representation should be
-  done manually
-* Its main purpose is to easily generate both a network visualization
-  and find the optimal visualization parameters to reproduce this visualization. To this end, both are 
-  saved to objects in the Python instance running Netwulf.
-* It further provides functionality to
-  redraw the visualization in Python using matplotlib [@matplotlib] to save it as a vector graphic
-  or image in arbitrary resolution.
-* more description
+For many users, these tools, although occasionally inconvenient and cumbersome to use, offer the necessary functionality to visualize networks in most desired ways. However, since a growing population of network researchers and practitioners are becoming Python users [@developersurvey], it is increasingly pressing that a fast and intuitive tool for network visualization exists.
+
+*Netwulf* is a light-weight Python library that provides an ultra simple API for interactively visualizing a network and returning the computed layout and style. It is build around the philosophy that network manipulation and preprocessing should be done programmatically, but that the efficient generation of a visually appealing network is best done interactively, without code. It allows users to:
+
+1. create a network, `G`, in either dictionary or *networkx.Graph* format, then calling `netwulf.visualize(G)`, to
+2. display it in a browser window as an interactive, manipulable, stylable network and 
+   1. post the final style and computed node-positions back to Python in dictionary format, allowing further manipulation, or redrawing with matplotlib [@matplotlib], or
+   2. saving the image directly to the desktop as a PNG file.
+
+The visualization component is implemented in JavaScript, relies on d3.js [@d3] for computing layouts, and uses canvas for rendering, which makes it the fastest tool for networks visualization in Python. 
 
 
 # Figures
@@ -68,3 +52,4 @@ I'm just collecting some thoughts here
 Both authors contributed equally to the software, documentation, and manuscript. B. F. M. is financially supported as an *Add-On Fellow for Interdisciplinary Life Science* by the Joachim Herz Stiftung.
 
 # References
+