Semantic Search Engine for Time-Series Data

It's the year 2014 and there are several updates to the Zymergi Object-Oriented Metadata Search (i.e. a semantic search engine for time-series data).

The first update is that we've moved to HTML5.  This means that we're dropping support for for IE8 or less.  We're proven on the latest versions major web-browsers: Google Chrome, Mozilla Firefox and Apple Safari.

Here's a screenshot of what the search page looks like.  There's no equivalent of "Google Instant" but given the metadata inputted by the administrator into ZOOMS, the software is able to guess what words you are meaning to type:

The second update is that ZOOMS uses a CSS Framework called, "Bootstrap."  Bootstrap was developed by Twitter and they gave it out for free.  The deal with CSS Frameworks is that someone has already done a lot of the heavy web-page styling.  You just need to customize it a bit to fit your look.

The other thing about Bootstrap is that it is "responsive," meaning the webpage will "respond" differently depending on the size of your screen.  Responsive web design (RWD) refers to whether or not a website is optimized for mobile devices.

No, we aren't wading into the time-series-data on mobile devices.  We actually believe that Transpara has a great product in Visual KPI.   We actually don't expect customers to be using ZOOMS on a phone or tablet on a regular basis, but we acknowledge that it can't be helped; in those cases, you can get your trend data with ZOOMS.  Besides, it came for free, so why not add this value?

The last update is that the entire product has been refactored.  The changes are all under the hood, but we've applied the MVC design pattern to separate the functions for a faster, more technically supportable system.

Below, you see a search engine results page (i.e. SERP) for the search terms inputted above.  ZOOMS tells you exactly which typed words has which meaning:

• Reactor1 was identified as a unit.
• Temperature was identified as a parameter.
• Volume was identified as a parameter.

ZOOMS is figuring out what the typed words mean and combining it into a search result.  In this case, someone looking for the reactor temperature and volume may be interested in a trend with each of these two traces plotted.

It is by far the fastest way for an untrained individual to get/view time-series data in a process environment.

We'll be disclosing shortly, but in addition to existing features, there are exciting updates in the coming months… like the ability to run without connecting to other data historians (yep, there's going to be an internal one).

Want a test drive?

ZST is 67% faster.

For those of you who don't know, the ZST (Zymergi SQL Tool) is a Windows-app that gets your database information and puts it in any format you want.  Typically, customers want to convert their relational data to HTML5 so that they can view (and act on ) it with a desktop or mobile-device browser.



Well, there's good news.  ZST is now 67% faster.  Now, this increased speed may not matter in an enterprise environment where apps are feature-rich, but slow.  But for our customers with external-facing websites, more speed = more revenue.

So why would the enterprise customer want ZST?

Well, the first thing is that this is commercial off-the-shelf (COTS) software.  Secondly, you're essentially adding search and browsing capabilities to your existing relational data.  And ultimately, you're looking to institutionalize tribal knowledge.

• Boosting speed of ZST
• ZST Support Page

How to Institutionalize Tribal Knowledge

Is your knowledge going to walk out the door when key old-timers begin retiring?

Biotechnology was invented in the 1970's by Bob Swanson and Herb Boyer. Commercialization of this stuff (large-scale biologics manufacturing) started taking off in the 1980's.

We're closing in on 30-years since biotech manufacturing started. If you joined as a junior employee (in your 20's), you're now in your fifties. If you joined as a more senior employee (in your 30's), you're about to retire.

Chances are, a lot of your core competency is sloshing around in the brains of these folks. And when those guys are long gone, all that's left will be hard drives full of spreadsheets and documents.

How do you institutionalize tribal knowledge?

Zymergi has solved this problem for biotech companies with the help of Google. Prior to Google Docs and Google Mail for the enterprise, Google sold their search engine as a physical appliance. Customers purchase their machine, slide it into a server rack and configure it to crawl your web-enabled network drives.

(The process is iterative since there's quite a number of files on public network drives that ought not be there)

From here, you basically get an intranet site that looks and feels like Google, except now, instead of searching the internet, you're searching critical enterprise documents, powerpoint slides and PDFs.

The limitation with the out-of-the-box solution is that scope is limited to files on a network drive. Yet in an enterprise environment, your usable knowledge may be stored in back-end relational databases used by systems like SAP or TrackWise. How do you liberate the knowledge stuck behind the front-end application that has been engineered to run a business process (as opposed to serve data)?

ZST is Zymergi's answer. ZST is a web-application that does one thing: make web-pages out of relational database data. Coded in the .NET Framework, the ZST runs in the Windows environment, and when configured, can expose your relational data to search engines for indexing.

With QA discrepancy data and engineering change order data juxtaposed with scientific memos, anyone with authorized access can learn your business the way they learn other subjects: using Google and on the... intranet.

Want to see all discrepancies, change orders, process flow diagrams, campaign summaries, science memos about CD11a production culture pH?



Want to know about all contaminations at the seed train scale across the entire manufacturing network?

by Oliver Yu

Managing the biologics manufacturing workforce of the future will require institutionalizing tribal knowledge.  One way to tech transfer from tribal elders to young blood is with ZST and an intranet search engine.