more work on dat paper

1 files changed, 14 insertions, 10 deletions

diff --git a/papers/dat-paper.md b/papers/dat-paper.md
index b4598dd..bfb3f0b 100644
--- a/papers/dat-paper.md
+++ b/papers/dat-paper.md
@@ -1,6 +1,6 @@
 # Abstract
 
-Dat is a swarm based version control system designed for sharing large datasets over networks such that their contents can be accessed randomly, be updated incrementally, and have the integrity of their contents be trusted. Every Dat user is simultaneously a server and a client exchanging pieces of data with other peers in a swarm on demand. As data is added to a Dat repository updated files are split into pieces based on Rabin fingerprinting and deduplicated against known pieces to avoid retransmission of data. File contents are automatically verified using secure hashes meaning you do not need to trust other nodes. 
+Dat is a swarm based version control system designed for sharing large datasets over networks such that their contents can be accessed randomly, be updated incrementally, and have the integrity of their contents be trusted. Every Dat user is simultaneously a server and a client exchanging pieces of data with other peers in a swarm on demand. As data is added to a Dat repository updated files are split into pieces using Rabin fingerprinting and deduplicated against known pieces to avoid retransmission of data. File contents are automatically verified using secure hashes meaning you do not need to trust other nodes.
 
 # 1. Introduction
 
@@ -12,7 +12,7 @@ Distributed file sharing tools like BitTorrent become faster as files become mor
 
 Decentralized version control tools for source code like Git provide a protocol for efficiently downloading changes to a set of files, but are optimized for text files and have issues with large files. Solutions like Git-LFS solve this by using HTTP to download large files, rather than the Git protocol. GitHub offers Git-LFS hosting but charges repository owners for bandwidth on popular files. Building a peer to peer distribution layer for files in a Git repository is difficult due to design of Git Packfiles which are delta compressed repository states that do not support random access to byte ranges in previous file versions.
 
-Science is an example of an important community that would benefit from better approaches in this area. Increasingly scientific datasets are being provided online using one of the above approaches and cited in published literature. Broken links and systems that do not provide version checking or content addressability of data directly limit the reproducibility of scientific analyses based on shared datasets. Services that charge a premium for bandwidth cause monetary and data transfer strain on the users sharing the data, who are often on fast public university networks with effectively unlimited bandwidth. Version control tools designed for text files do not keep up with the demands of large data analysis in science today.
+Scientists are an example of an important group that would benefit from better solutions to these problems. Increasingly scientific datasets are being provided online using one of the above approaches and cited in published literature. Broken links and systems that do not provide version checking or content addressability of data directly limit the reproducibility of scientific analyses based on shared datasets. Services that charge a premium for bandwidth cause monetary and data transfer strain on the users sharing the data, who are often on fast public university networks with effectively unlimited bandwidth. Version control tools designed for text files do not keep up with the demands of large data analysis in science today.
 
 # 2. Inspiration
 
@@ -58,19 +58,17 @@ WebTorrent implements the BitTorrent protocol in JavaScript using WebRTC as the
 
 ## 2.7 InterPlanetary File System
 
-IPFS also builds on many of the concepts from this section and presents a new platform similar in scope to the Web that has content integrity, peer to peer file sharing, version history and data permanence baked in as a sort of upgrade to the current Web. Whereas Dat is one application of these ideas that is specifically focused on sharing datasets but is agnostic to what platform it is built on, IPFS goes lower level and abstracts network protocols and naming systems so that any application built on the Web can alternatively be built on IPFS to inherit it's properties, as long as their hyperlinks can be expressed as content addressed addresses to the IPFS global Merkle DAG.
+IPFS also builds on many of the concepts from this section and presents a new platform similar in scope to the Web that has content integrity, peer to peer file sharing, version history and data permanence baked in as a sort of upgrade to the current Web. Whereas Dat is one application of these ideas that is specifically focused on sharing datasets but is agnostic to what platform it is built on, IPFS goes lower level and abstracts network protocols and naming systems so that any application built on the Web can alternatively be built on IPFS to inherit it's properties, as long as their hyperlinks can be expressed as content addressed addresses to the IPFS global Merkle DAG. The research behind IPFS has coalesced many of these ideas into a more accessible format and we look forward to being able to run the Dat protocol on top of the IPFS web platform.
 
-The research behind IPFS has coalesced many of these ideas into a more accessible format. We are still exploring how to best implement the Dat protocol on top of the IPFS platform.
-
-# 3. DESIGN
+# 3. Design
 
 Dat is a file sharing protocol that does not assume a dataset is static or that the entire dataset will be downloaded. The protocol is agnostic to the underlying transport e.g. you could implement Dat over carrier pigeon. The key properties of the Dat design are explained in this section.
 
 - 1. **Mirroring** - All participants in the network simultaneously share and consume data.
 - 2. **Content Integrity** - Data and publisher integrity is verified through use of signed hashes of the content.
-- 3. **Parallel Transfer** - Subsets of the data can be accessed from multiple peers simultaneously, improving transfer speeds.
+- 3. **Parallel Replication** - Subsets of the data can be accessed from multiple peers simultaneously, improving transfer speeds.
 - 4. **Streaming Updates** - Datasets can be updated and distributed in real time to downstream peers.
-- 5. **Secure Metadata** - Dat employs a capability system whereby anyone with a Dat link can connect to the swarm, but the link itself is a secure hash that is nearly impossible to guess and is never leaked by Dat itself.
+- 5. **Secure Metadata** - Dat employs a capability system whereby anyone with a Dat link can connect to the swarm, but the link itself is a secure hash that is difficult to guess.
 
 ## 3.1 Mirroring
 
@@ -108,7 +106,7 @@ If we get a lot of potential sources we pick a handful at random to try and conn
 
 The connection logic is implemented in a module called [discovery-swarm](https://www.npmjs.com/package/discovery-swarm). This builds on discovery-channel and adds connection establishment, management and statistics. You can see stats like how many sources are currently connected, how many good and bad behaving sources you've talked to, and it automatically handles connecting and reconnecting to sources for you. Our UTP support is implemented in the module [utp-native](https://www.npmjs.com/package/utp-native).
 
-So now we have found data sources, connected to them, but we haven't yet figured out if they *actually* have the data we need. This is where our file transfer protocol [Hyperdrive](https://www.npmjs.com/package/hyperdrive) comes in. This is explained in a later section.
+So now we have found data sources, connected to them, but we haven't yet figured out if they *actually* have the data we need. This is where our file transfer protocol [Hypercore](https://www.npmjs.com/package/hypercore) comes in. This is explained in a later section.
 
 Peer connections types are outside the scope of the Dat protocol, but in the Dat implementation we make a best effort to make as many successful connections using our default types as possible. This means employing peer to peer connection techniques like UDP hole punching [?]. Our approach for UDP hole punching is to use a central known hole punching server which is accessible on the public Internet. In our implementation we re-use our custom DNS server by adding to it special functionality to facilitate peer message exchange for the purpose of hole punching.
 
@@ -128,7 +126,13 @@ Content integrity means being able to verify the data you received is the exact
 
 A common issue in data analysis is when data changes but the link to the data remains the same. For example, one day a file called data.zip might change, but a simple HTTP link to the file does not include a hash of the content, so clients that only have the HTTP link have no way to check if the file changed. Looking up a file by the hash of its content is called content addressability, and lets users not only verify that the data they receive is the version of the data they want, but also lets people cite specific versions of the data by referring to a specific hash.
 
-## 3.3 Parallel Transfer
+Data storage and content integrity in Dat is implemented in a module called Hypercore. Given a stream of binary data, Hypercore splits the stream into chunks using Rabin fingerprints, hashes each chunk, and arranges the hashes in a specific type of Merkle tree that allows for certain replication properties.
+
+Hypercore is agnostic to the format of the input data, it operates on any stream of binary data. For the Dat use case of synchronizing datasets we wrote and use a file system abstraction on top of Hypercore called Hyperdrive. There are other abstractions you can write on top of Hypercore instead of Hyperdrive/Dat such as Merkle DAGs but these are outside the scope of this paper.
+
+Our content addressing scheme involves splitting 
+
+## 3.3 Parallel Replication
 
 ## 3.4 Streaming Updates