Thoughts on a paper

docs/make.jl

@@ -103,6 +103,7 @@ makedocs(;
             "Peculiarities" => "explanations/peculiarities.md",
         ],
         "Source code" => literate_pages,
+        "Paper" => "paper.md",
     ],
     warnonly = true,
 )

docs/src/paper.md

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+# Paper
+
+This page will follow the JOSS template, but I'm just getting some ideas down that we can use later if required.
+
+## Statement of need
+
+!!! note
+    These are basically a bunch of ideas/lines that we can use, it's not fleshed out yet!
+
+Many full-featured geospatial libraries exist already - GEOS (and its predecessor JTS) being the main sources 
+from which libraries like GDAL, R's sf, Python's shapely and others obtain functionality.
+
+GeometryOps is able to integrate all of Julia's functionality like arbitrary float types and multiple dispatch.  
+This, along with being written in a high-level language like Julia, significantly lowers the barrier to entry
+for new contributors.  We are aiming to make impossible workflows (whether because of memory constraints, speed,
+or lack of good algorithms) possible, not merely for performance improvement!
+
+A guiding philosophy of GeometryOps is the ability to provide choice.  Consider the `segmentize` function - 
+users can choose whether to interpolate in linear (handled directly) or geodetic (handled by Karney's GeographicLib) 
+space.  This is not a functionality that is available in most other libraries, where one must instead choose the library
+(for example, s2 vs sf) or activate a global switch to toggle certain functionality.
+
+Another example of this philosophy is the `fix` interface.  Users can create their own fixes, relative to their needs, and hook
+those into an already known syntax.  Error messages can be customized and users can potentially even have them show plots indicating
+exactly where the error is.  No other geometry library (to my knowledge) offers this level of flexibility.
+
+GeometryOps also utilizes exact predicates to return geometrically correct answers, which even GEOS does not. 
+
+## Ongoing research projects
+- Subzero.jl (ice floe simulation, OOM better performance than Matlab, 3x better than LibGEOS with more accurate results) using polygon intersection
+- Alex Gardner's stuff (glacier tracking, statistics and forecasting) using polygonize and generic spatial predicates/set ops
+- Anyone else?
+
+## Citations
+
+- Core Julia packages: julia, ExactPredicates, GeoInterface
+- Foster 2019 paper (polygon clipping)
+- Hao-Sun paper (point-in-polygon)
+- Previous efforts in Julia: PolygonOps.jl, ...
+-