About a year ago I posted some emails on various techie UIUC newsgroups about the need for DDoS-FOIA software, the right bookend to the left one of DDoS-FOIA filing. With the UIUC-FOIA office neatly boxed between these endpoints.
As you can probably tell, I’ve spent too much of my holiday break researching and writing about UIUC — call it method, call it madness, I’m used to either as a callsign. In any case, I’ve finally figured out how to easily search a single site with the google, so I’ve been searching the UIUC-FOIA office’s site, where they post (searchable) log files of every FOIA filed.1
When I did this search of FOIA result letters using “Salaita” as the search term, I found 10 hits, corresponding to 10 FOIA requests up on the site as of the end of 2014:2
- 14–549 (16 pages);
- 14–535 (143 pages);
- 14–538 (204 pages);
- 14–544 (78 pages);
- 14–565 (Request to Narrow);
- 14–584 (0 pages);
- 14–591 (55 pages);
- 14–617 (179 pages);
- 14–536 (Request to Narrow);
- 14–652 (48 pages).
- (All of these files packaged as a single .zip at UIUC-Salaita-FOIAs_ASOF_20141231 – again note that these are just the response letters from UIUC-FOIA, and not the actual documents. If you want the documents you have to FOIA UIUC to obtain them, referencing the FOIA request number.)
As I say, the website doesn’t provide the produced documents, which total up to 723 pages. But even as figure out how to procure that corpus of Salaita documents,3 I thought I’d present this as an instructive opportunity to collaborate with someone(s) out there on DDoS-FOIA software adapted for parsing/crunching this set of data.
Not just for this data, of course, but for sets of FOIA data in general, because all of these sets unquestionably share some very common characteristics.
1. My background in patent searching software.
I come to the question of DDoS-FOIA software by way of my dalliance over the last 10 years or with coding my own patent searching software, which I did out of complete frustration with the poor rationales behind current patent-search software.
So without going into gory detail, “natural language” analysis applies to both the language as, say, english grammar, and also to the overall rules of construction that a particular class of corpus falls into — the high-level “language” of the class of corpus. For example, patent documents are highly structured not simply by the language they’re written in, or even by the document structure like title + abstract + specification + claims, but also by the human being that constructs the patent, that human being largely being someone specifically trained in a relatively standard way of patent construction.
Given the above, my idea was to use metrics for parsing patent documents that were indicative of the high-level considerations the patent attorney, patent agent or experienced drafter typically uses in preparing the document. For anyone familiar with these techniques, any patent or patent application has multiple “tells” in it that speak volumes to you … if you know what you’re looking for.4
And I do know what I’m looking for. I’m a patent attorney, it’s what I do.5
2. The “natural language” of a single FOIA production set.
So to run with the above concept, when you get a FOIA result set back from any particular FOIA office, it’s going to have embedded in it all the ticks and idiosyncrasies of that office’s procedures and personnel. And also the the ticks and idiosyncrasies inherent in FOIA productions.
Let’s examine these in reverse order:
- Ticks and idiosyncrasies of FOIA documents generally. Redactions are of course the signal feature of FOIAed documents, so any contemplation of analysis necessarily begins with some method of parsing redactions. At the lowest level such parsing would be to identify if the reaction was a single word, a phrase, a sentence, a paragraph etc. You can go wild with this concept and extend it to meta-analysis of backfilling of redacted words by context of surrounding non-redacted text. You can add to that estimations of content based on the physical length of the redaction (e.g., in cm) versus the kind of font used to generate the text. Another hook into analysis would be to use the standard language of emails (from, to, subject, attachments) to do further parsing and analysis.
- Ticks and idiosyncrasies of FOIA documents resulting from procedure and personnel. Every FOIA office has its own signatures for what it likes to redact, and this breaks down into individuals within the office as well as the office over time, depending upon how sophisticated the redacting and how much workflow the office experiences. For example, redacting “personal information” is really simple when it involves merely phone numbers and social security numbers and addresses, but much harder when it’s information about, say travel, which might seem benign but oftentimes can be used to reconstruct adulterous adventures6 and so on.7 Thus document reconstruction may often be advanced by compiling a database of the ticks and foibles of each FOIA office and each FOIA officer.
3. The “natural meta-language” of an aggregated (DDoS-FOIA) production set.
FOIAed document reconstruction becomes even more interested in the context of a DDoS-FOIA approach, since we’re now talking about a corpus of sets of documents, each set obtained by separate FOIA, each separate FOIA possibly parsed by a different FOIA officer without coordination with the other FOIA officers.
So take the 723 page Salaita document corpus that I’m still trying to figure out how to obtain. That corpus resulted from 10 separate but likely overlapping FOIAs, therefore, data-reduction is mandatory to analysis.
But. Data reduction needs to occur against an awareness of possibly only partially–redundant data — Miller’s name came up because UIUC-FOIA failed to redact it in one instance, as did Miller’s office location in Northbrook or travel destination of Santa Fe.
And beyond this, even seemingly benign non-redacted text can cast a light on other redactions, a situation that often occurs when one redactor removes an entire sentence, and another only part of a sentence.
To summarize: aggregated FOIA documents obtained by DDoS-FOIA offer up analytic possibilities that likely go beyond what’s obtainable in a single production.
4. A proposal for DDoS-FOIA software.
Based on the above, it would be completely reasonable to take a standard NLP front-end in the language of your choice and build not just a redacted document processor but also a processor for building correlations and extracting information from corpuses obtained by DDoS-FOIA.
I’ve already talked about this to a number of different organizations, none of which seemed particularly interested. In fact, I wanted to join the UIUC Executive Roundtable to talk about this as well as my patent search software company, but was immediately rejected as “merely a patent attorney” by the powers that be of that apparently exclusive club.8
So. Are there any peoples out there that would be interested in this? My contacts are extremely good. And it’s a concept easily scalable to MMDDoS-FOIA9 software, where perhaps a grand unified database of cross-the-country FOIA filings could be built, analyzed, and discussed.
The marquee image started life as an interior panel of “Space Detective #1,” which I believe is of 1951 vintage. See Space Detective #1. Obviously I took a certain amount of artistic license with the original, but I’m sure Teena and space detective (aka Rod Hathway/The Avenger) approve.
And if you think I’m being too acerbic about the UIUC-FOIA office, go back through my earlier posts and re-read that quote from the Illinois Attorney General’s office about the UIUC-FOIA office’s ongoing “illegal” behavior.
- The search string to enter into the google search box is “search_term site:http://www.foia.uillinois.edu/” (without the quotes), where search_term is the term you want to search for that was present in the FOIA response letter. Note that the UIUC-FOIA office website doesn’t put up the actual FOIA results, so your search won’t identify the search term if it occurs in those results. [↩]
- Illinois mandates a 5 working day period between receipt of FOIA request and production of documents, but that period can be extended by 5 days by the FOIA office, and still longer if the filer is a frequent-filer (“vexatious filer”) or the FOIA office uses one or more of its many tricks to delay response (e.g., asking the requester to narrow the request). Consequently it’s highly possible that there were more than 10 FOIA filings in 2014 containing the keyword “Salaita.” These will crop up on the UIUC-FOIA log site, but only after UIUC-FOIA sends out a response letter. [↩]
- Given my vexatious-filer status, UIUC-FOIA will delay production of these documents for months, if not years. [↩]
- Note that this is a blanket statement that doesn’t take into account different practices in different countries and for different types of patent documents, e.g., provisionals versus US non-provisional filing versus PCT etc. [↩]
- Not to boast, but this isn’t what most patent attorneys do. I have an academic bent that makes it impossible for me to use a tool without either a) breaking it or b) making it better. I’d like to add a possibility of c) breaking it in order to make it better … sometimes I think I do this, but more often I probably just break things. [↩]
- “Hiking the Appalachian Trail.” [↩]
- As I said in an earlier post, UIUC-FOIA redacted Steve Miller’s trip destination of Santa Fe in some emails and not in others. And didn’t redact Chancellor Wise saying “Oh, I love Santa Fe.” So much for consistency. [↩]
- Part of a drawn-out process of experiencing what, in my opinion and frankly that of others, is a frequently sub-par unit of UIUC, the Research Park, or at least the incubator component thereof. [↩]
- That is, “Massively-Mutlple Distributed-Denial-of-Stonewalling Freedom-of-Information-Act.” [↩]