Archive for the ‘Information Silos’ Category

Silos You Will Always Have With You (Apologies to the Apostle Matthew)

Wednesday, August 31st, 2016

Apologies to the Apostle Matthew, but “The poor you will always have with you…” (Matt. 26:11), sprang to mind when I read the interview with Mayur Gupta, Chief Digital Officer of Healthgrades, in Digital Transformation in Healthcare with Mayur Gupta, Chief Digital Officer, Healthgrades.

Or at least my rendering of that passage as:

Silos You Will Always Have With You

when I read:


I think two things and this is again this is something that I’ve learned through my career and continue to learn. First and foremost, is break down those silos. Connect the dots, drive convergence in every single aspect of your business. Whether that is how you organized, how you’re structured, the kind of talent to bring in. How you look at data, how you look at technology. It doesn’t matter what vertical it is, but just drive convergence.

We living in a world that is all about ecosystems and platforms not about silo products, silo technologies, silo experiences. And I think the best way to think about it is from a consumer standpoint she does not see the silos you know. She does not see a channel. All she expects is the best experience, the best service, the best product, at the best price. You know at a location in touchpoint at a time of her own choice. And the only way we as brands and technologists and marketers can make that happen is when we break down those silos and we drive conversions in our own world and we stopped looking at digital as the thing, because we now live, operate and breathe in an intrinsically digital world.

Silos have been a recognized issue since organized record keeping began.

The universal solution: Let’s build another, bigger silo!

Think about it. There is never going to be a time when new and different information systems and data will not be appearing.

Rather than flailing against silos, along with all the political costs of the same, why not keep your current silos and use topic maps to map across those silos?

Those interested in preserving “silos” (you know who you are), will be happy because their systems and sovereignty over them is preserved, yet other stakeholders can combine that data with new data, for other purposes.

Do you have the political capital to defeat current silos while trying to erect your own?

As I said, “silos you will always have with you….”

You can accept that and use topic maps to create your new “silo” or fight against existing silos.

Your call.

Boy Scout Explusions – Oil Drop Semantics

Monday, October 22nd, 2012

Data on decades of Boy Scout expulsions released by Nathan Yau.

Nathan points to an interactive map, searchable list and downloadable data from the Los Angeles Times of data from the Boy Scouts of America on people expelled from the Boy Scouts for suspicions of sexual abuse.

The LA Times has done a great job with this data set (and the story) but it also illustrates a limitation in current data practices.

All of these cases occurred in jurisdictions with laws against sexual abuse of children.

If a local sheriff or district attorney reads about this database, how do they tie it into their databases?

Not at simple as saying “topic map,” if that’s what you were anticipating.

Among the issues that would need addressing:

  • Confidentiality – Law enforcement and courts have their own rules about sharing data.
  • Incompatible System Semantics – The typical problem that is encountered in business enterprises, writ large. Every jurisdiction is likely to have its own rules, semantics and files.
  • Incompatible Data Semantics – Assuming systems talk to each other, the content and its semantics will vary from one jurisdiction to another.
  • Subjects Evading Identification – The subjects (sorry!) in question are trying to avoid identification.

You could get funding for a conference of police administrators to discuss how to organize additional meetings to discuss potential avenues for data sharing and get the DHS to fund a large screen digital TV (not for the meeting, just to have one). Consultants could wax and whine about possible solutions if someday you decided on one.

I have a different suggestion: Grab your records guru and meet up with an overlapping or neighboring jurisdiction’s data guru and one of their guys. For lunch.

Bring note pads and sample records. Talk about how you share information between officers (that you and your counter-part). Let the data gurus talk about how they can share data.

Practical questions of how to share data and what does your data mean now? Make no global decisions, no award medals for attending, etc.

Do that once or twice a month for six months. Write down what worked, what didn’t work (just as important). Each of you picks an additional partner. Share what you have learned.

The documenting and practice at information sharing will be the foundation for more formal information sharing systems. Systems based on documented sharing practices, not how administrators imagine sharing works.

Think of it as “oil drop semantics.”

Start small and increase only as more drops are added.

The goal isn’t a uniform semantic across law enforcement but understanding what is being said. That understanding can be mapped into a topic map or other information sharing strategy. But understanding comes first, mapping second.

Graph Databases: Information Silo Busters

Wednesday, February 29th, 2012

In a post about InfiniteGraph 2.1 I found the following:

Other big data solutions all lack one thing, Clark contends. There is no easy way to represent the connection information, the relationships across the different silos of data or different data stores, he says. “That is where Objectivity can provide the enhanced storage for actually helping extract and persist those relationships so you can then ask queries about how things are connected.”

(Brian Clark, vice president, Data Management, Objectivity)

It was the last line of the post but I would have sharpened it and made it the lead slug.

Think about what Clark is saying: Not only can we persist relationship information within a datastore but also generate and persist relationship information between datastores. With no restriction on the nature of the datastores.

Try doing that with a relational database and SQL.

What I find particularly attractive is that persisting relationships across datastores means that we can jump the hurdle of making everyone use a common data model. It can be as common (in the graph) as it needs to be and no more.

Of course I think about this as being particularly suited for topic maps as we can document why we have mapped components of diverse data models to particular points in the graph but what did you expect?

But used robustly, graph databases are going to allow you to perform integration across whatever datastores are available to you, using whatever data models they use, and mapped to whatever data model you like. As others may map your graph database to models they prefer as well.

I think the need for documenting those mappings is one that needs attention sooner rather than later.

BTW, feel free to use the phrase “Graph Databases: Information Silo Busters.” (with or without attribution – I want information silos to fall more than I want personal recognition.)