|author||Bryan Newbold <firstname.lastname@example.org>||2018-06-10 15:50:26 -0700|
|committer||Bryan Newbold <email@example.com>||2018-06-10 15:52:39 -0700|
actually commit old metadata collections post
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diff --git a/posts/merkle_design.md b/posts/merkle_design.md
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+Title: Design Considerations for Merkle-Tree Storage Systems
+Tags: tech, dweb
+## Features we Want
+Four semantic properties we might want from a universal
+**1. Deterministic file-level addressability, enabling file-level efficiency
+on-wire and at rest.** If every distinct file can be identified by only a
+single, reproducible name, then discovery, indexing, and de-duplicaiton is made
+easier. If the same file can end up with different names, then that file might
+be transfered or stored separately by default; this creates pressure for the
+application layer to support the concept of "many identifiers for the same
+file", and requires additional coordination at scale.
+**2. Simple chunk-level de-duplication between files and versions.** This means
+that if you have two large files with only a few bytes *changed* between them,
+you don't need both full copies, only data proportional to the difference. A
+special case is when an existing file is copied and modified; in this case the
+system can track the history and change. This is distinct from adding two files
+at the same time and detecting that there is a large degree of overlap.
+**3. Offset-independent, chunk-level du-duplication between files.** Stronger
+than #2, this method is efficient even if the different between two files is
+one of inserting (or deleting) and *offset* of bytes; the challenge of
+detecting that two files are identical except for an offset is harder than that
+of identifying the identical bytes at the same locations.
+**4. File-level Interoperability with legacy and future systems.** Can the
+system be used as a transparent "layer" by other systems? Eg, can a thin proxy
+be implemented on top of existing file-systems and blob stores? Can thin
+file-system and blob-store gateways be layered on top of the storage system? A
+common source of friction here is when generic, off-the-shelf full-file hashes
+like SHA-1, SHA-256, or BLAKE2b are not used in a common manner.
+This last one doesn't matter if you are planning on Total World Domination with
+no need for future upgrades.
+## Existing Implementations
+git nails #1 (at the cost of not having an upgrade path for the hash function).
+It contains implementation work-arounds for #2 and #3: an internal compression
+format allows storing and transmitting only the diffs between two versions of a
+file, instead of the file files themselves. This isn't baked in to the
+structure of the system though, and doesn't always work (in particular, seems
+to get skipped for large files). By using SHA-1, it gets very close to #4, but
+decided to prepend the length of a file to the file's contents themselves
+before hashing, so the git address of a blob does not match the usual SHA-1 of
+The Dat protocol provides a weak version of #2, but no existing implementation
+actually implements any form of de-duplication, even at the full-file level.
+Eg, if you delete a file from a Dat archive and then re-add it later, the file
+contents are duplicated in the content feed, even though the standard would
+allow pointing back to the previous copy.
+IPFS has a weak version of #1: the file digest is deterministic if the same
+software version and configuration is used,
+## Challenges in Implementing These Features
+Features #1 and #3 seem very difficult to reconcile. A frequent trick to
+compress deltas between files is to take history into account, but using
+history makes the resulting hash (name) history dependent. Robust,
+deterministic, content-aware hashing is supposed enable both features at the
+same time, which is exciting, but seems to have been abandoned by all existing
+implementations because it's too slow.
+## Tangled Hierarchies
+git and other versioned storage systems are like catnip to programmers:
+folks love to think about re-inventing "everything" on top of such a system. I
+think this is because git supplies specific semantic features people love,
+while being deeply entangled with files and file systems. Computer engingeering
+is All About Files, and git is both made out of files (look in .git; it's
+simple files and directories all the way down!) and accomodating files.
+- on UNIX systems, a block storage device is a fixed size bytestream; a big
+ file, if you will. File systems on top of this are like an archive file
+ format (eg, tar, zip).
+- disk partitioning schemes (like GPT) and volume managers (like LVM) are
+ basically the same thing as file archive formats (like .tar)
+- a hypercore feed (which Dat is built upon) is a single long append-only
+ bytestream: a growing file, if you will, and hyperdrive is a file system (or
+ file format) on top of that.
+There's a tangled hierarchy here, in the same way that (at least on UNIX), one
+can create any variation of:
+- a file...
+- in an archive file-format (like .zip)...
+- stored in a file-system (like ext4 or ISO)...
+- serialized into a binary file...
+- on another file system (perhaps NTFS)...
+- residing in a partition...
+- on a block device.
+If we had a super-duper merkle-tree mechanism for storing files, and a
+consistent way of serializing it to a single file, we write it directly to our
+disk block devices, backup and synchronize file systems efficiently, etc.
diff --git a/posts/metadata_collections.md b/posts/metadata_collections.md
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+Title: Bibliographic Metadata Dumps
+Tags: tech, archive, scholar
+# - does BASE link to fulltext PDFs? is that helpful?
+# - can we actually get academia.edu and researchgate.net papers? maybe?
+I've recently been lucky enough to start working on a new big project at the
+[Internet Archive]: collecting, indexing, and expanding access to research
+publications and datasets in the open world. This is perhaps *the* original
+goal of networked information technology, and thanks to a decade of hard
+work by the Open Access movement it feels like intertia
+[is building][nature-elsevier] towards this one small piece of "universal
+access to all knowledge".
+[Internet Archive]: https://archive.org
+<img src="/static/fig/ia_logo.png" width="150px" alt="internet archive logo" />
+This is a snapshot-in-time look at "what's already out there" regarding indexes
+of scholarly papers and books (aka, "things that get cited"). There are a ton
+of resources out there, and many of them are just re-aggregating or building on
+top of each other.
+Here's a table of index-only resources for papers. These are databases or
+corpuses of metadata that might include links/URLs to full text, but don't seem
+to host fulltext copies themselves:
+ <th>Record Count (millions)
+ <td>Total digital English language papers
+ <td>estimated, 2014
+ <td>Total open access
+ <td>estimated, 2014. Meaning "available somewhere"? MS academic had 35
+ <td>Number of DOIs
+ <td>Global; includes non-journals.
+ <td>CrossRef DOIs
+ <td>Primary registrar for journals/paper in western world
+ <td>BASE Search
+ <td>Data from OAI-PMH
+ <td>Google Scholar
+ <td>"records", not URLs
+ <td>Web of Science
+ <td>proprietary; 1 billion citation graph
+ <td>Only half (13mil) have abstract or link to fulltext
+ <td>Semantic Scholar
+ <td>10 to 20
+ <td>Sometimes mirror fulltext?
+ <td>Paper entries; Spring 2017
+ <td>computer science bibliography; Spring 2017
+A big open question to me is how many pre-digital scholarly articles there are
+which have not been digitized or assigned DOI numbers. Eg, how good is JSTOR
+coverage? I'm unsure how to even compute this number.
+And here are full-text collections of papers (which also include metadata):
+ <th>Fulltext Count (millions)
+ <td>one-file-per-DOI, 2017
+ <td>(2010; presumably many more now?). Crawled from the web
+ <td>Extracted fulltext, not PDF? Complete "gold" OA?
+ <td>PubMed Central
+ <td>Open Access. 2017
+ <td>OSF Preprints (COS)
+ <td>Internet Archive
+ <td>"Clean" mirrored items in Journal collections; we probably have far more
+ <td>physics+math. articles, not files, 2017
+ <td>JSTOR Total
+ <td>mostly locked down. includes books, grey lit
+ <td>JSTOR Early Articles
+ <td>open access subset
+Numbers aside, here are the useful resources to build on top of:
+**CrossRef** is the primary **DOI** registrar in the western (english speaking
+world). They are a non-profit, one of only a dozen or so DOI registrars; almost
+all scholarly publishers go through them. They provide some basic metadata
+(title, authors, publication), and have excellent data access: bulk datasets, a
+query API, and a streaming update API. This is a good, authoritative foundation
+for building indexes. China, Korea, and Japan have their own DOI registries,
+and published datasets end up in DataCite instead of CrossRef. Other holes in
+DOI coverage are "grey literature" (unpublished or informally published
+documents, like government reports or technical memos), documents pre-2000 with
+absentee publishers, and books (only a small fraction of books/chapters have
+Publishers and repositories seem to be pretty good about providing **OAI-PMH**
+API access to their metadata and records (and sometimes fulltext). Directories
+make it possible to look up thousands of API endpoints. **BASE** seems to be
+the best aggregation of all this metadata, and some projects build on top of
+BASE (eg, oaDOI). **CORE** finds all of it's fulltext this way. It's not
+clear if BASE is a good place to pull bulk metadata from; they seem to re-index
+from scratch occasionally. **oaDOI** and **dissem.in** are services that
+provide an API and search interface over metadata and point to Open Access
+copies of the results.
+**PubMed** (index) and **PubMed Central** (fulltext) are large and well
+maintained. There are Pubmed records and identifiers ("PMID") going far back in
+history, though only for medical texts (there is increasing contemporary
+coversage out of medicine/biology, but only very recently). Annual and daily
+database dumps are available, so a good resource to pull from.
+**CiteSeerX** has been crawling the web for PDFs for a long time. Other than
+**Google Scholar** and maybe the **Internet Archive** I think they do the most
+serious paper crawling, though many folks do smaller or one-off crawls. They
+are academic/non-profit and are willing to share metadata and their collected
+papers; their systems are documented and open-source. Metadata and citations
+are extracted from PDFs themselves. They have collaborated with the Microsoft
+Research and the Allen Institute; I suspect they provided most or all content
+for **Semantic Scholar** and **Microsoft Academic Knowledge** (the later now
+defunct). NB: there are some interesting per-domain crawl statistics
+[available](http://csxcrawlweb01.ist.psu.edu//), though half-broken.
+It's worth noting that there is probably a lot of redundancy between
+**pre-prints** and the final published papers, even though semantically most
+people would consider them versions or editions of the same paper, not totally
+distinct works. This might inflate both the record counts and the DOI counts.
+A large number of other resources are not listed because they are very
+subject-specific or relatively small. They may or may not be worth pursuing,
+depending on how redundant they are with the larger resources. Eg, CogPrints
+(cognative science, ~thousands of fulltext), MathSciNet (proprietary math
+bibliogrpahy, ERIC (educational resources and grey lit), paperity.org (similar
+to CORE), etc.
+*Note: We don't do a very good job promoting it, but as of June 2017 The
+Internet Archive is hiring! In particular we're looking for an all-around web
+designer and a project manager for an existing 5 person python-web-app team.
+Check out those and more on our
+: "The Number of Scholarly Documents on the Public Web", PLoS One, 1994,
+Khabsa and Giles. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0093949
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