How PLM can join semantic enterprise graph?

How PLM can join semantic enterprise graph?


Connectivity is a key these days and graphs are playing key role in the development of our connectivity. It doesn’t matter what to connect – people, information, devices. Graphs are fascinating things. Actually, I came to conclusion we live in the era of fast graph development. More and more things around us are getting “connected”.

It is almost two years since I first posted about Why PLM need to learn about Google Knowledge Graph. The story of Knowledge Graph is getting more power every day. GKG is growing. It represents “things” in the knowledge base describing lots of topics – music, books, media, films, locations, businesses and many others. Part of Google Knowledge Graph is fueled by Freebase – large collaborative database of structured data. Originally Freebase was developed by Metaweb and acquired by Google in 2010. It is still not completely clear how Google Knowledge Graph built. You can read some investigations here. Nevertheless, it is hard to undervalue the power of Knowledge Graph.

Another well known and publicly developed graph is Facebook social graph. Last year I posted – Why PLM should pay attention to Facebook Graph Search. Facebook graph represents structured information captured from Facebook accounts. It allows to run quite interesting and powerful queries (also known as Facebook Graph Search).

In my opinion, we are just in the beginning of future graph discovery and expanded information connectivity. It won’t stop in social networks and public web. I can see graphs will proliferate into enterprise and will create lots of valuable opportunities related to information connectivity and efficient query processing. article Let Enterprise Graph Tell You A Story speaks about enterprise as a set of Facebook pages. It explains how we can build a graph story of enterprise communication, collaboration, people activities, related data and other things. Here is my favorite passage from the article:

Wallace relies on Hadoop and graph database technology, with network data represented as a property graph. “Property graphs are utterly, totally extensible and flexible,” she said, and “the system gets smarter as you add more data into it.” The enterprise social network data generates triple sets (that John Smith created X Document that was downloaded by Jane Doe) that get pocketed into the graph, for example, as is metadata extracted from relational databases. A general set of algorithms can find a user within the graph and calculate his or her engagement level – activities, reactions, eminence and so on. “We now have a Big Data service with a set of APIs so people can query the enterprise graph,” she set, and then run analytics on those results that can drive applications.

I found this aspect of graph development very inspiring. To collect enterprise information into graph database and run a diverse set of queries can be an interesting thing. If I think about PLM as a technological and business approach, the value of graph connecting different part of information about product and activities located in different enterprise systems can be huge. These days, PLM vendors and manufacturing companies are using a diverse strategies to manage this information – centralized databases, master data management, enterprise search and others. Graph data approach can be an interesting option, which will make enterprise looks like a web we all know today.

What is my conclusion? The growing amount of information in enterprise organizations will change existing information approaches. It doesn’t mean all existing technologies will change overnight. However, new complementary techniques will be developed to discover and use information in a new ways. Graph is clearly going to play big role. PLM strategist, developers and managemers should take a note. Just my thoughts…

Best, Oleg

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