What metadata means in modern PDM/PLM systems

February 26, 2014

meta-data

Metadata is "data about data". If you stay long with PDM industry, you probably remember how earlier EDM/PDM software defined their role by managing of "data about CAD files" (metadata). However, it was long time ago. Wikipedia article defines two types of metadata – structural and descriptive. Here is a quote from the article:

The term is ambiguous, as it is used for two fundamentally different concepts (types). Structural metadata is about the design and specification of data structures and is more properly called "data about the containers of data"; descriptive metadata, on the other hand, is about individual instances of application data, the data content.

In my view, CAD/PDM/PLM is using both types. Since design is very structured and contains lots of rich semantic relations, metadata about CAD files stored in PDM system is structured. At the same time, descriptive metadata such as file attributes, information about people, project, organization can be applied to individual instance of CAD data (files) as well.

Since early EDM/PDM days, lots of changes happened in the definition and usage of a word metadata. Some of them are very confusing. The traditional use and definition of files (for example, in context of CAD files) is changing. Sometimes, we want to to keep "file" as a well-known abstraction, but underlining meaning is completely different and point more on "data" or "design" rather than actual files. Also, introduction of web based systems are changing physical use of files. The usage of file accessed via mobile application located in Dropbox is completely different. In many scenarios you will never get access to these physical files.

DBMS2 article Confusion about Metadata speaks about some additional aspects of metadata management that getting more relevant these days. It includes data about mobile devices usage (telephone metadata) and document data. Document data is getting more structured these days and often cannot be distinguished from structured RDBMS data. Here is interesting passage that describes the transformation of database and document based data.

[data about data structure] has a counter-intuitive consequence — all common terminology notwithstanding, relational data is less structured than document data. Reasons include: Relational databases usually just hold strings — or maybe numbers — with structural information being held elsewhere. Some document databases store structural metadata right with the document data itself. Some document databases store data in the form of (name, value) pairs. In some cases additional structure is imposed by naming conventions. Actual text documents carry the structure imposed by grammar and syntax.

Modern data management systems and especially noSQL data bases such as document and key-value databases can introduce new types of metadata or data. IoT (Internet of things) brings another level of complexity to data management. I can see many others to come.

What is my conclusion? I think, the term meta-data is getting outdated at least in the scope of design and engineering. Originally used a lot in EDM/PDM systems managing metadata about CAD files is not relevant anymore. Design data originally stored in CAD files becomes more transparent and connected to external to design world. The whole data paradigm is changing. Just my thoughts…

Best, Oleg


Tech Soft 3D TechTalk: PLM and Data Management in 21st Century

October 25, 2013

databases-300x225

Boston is one of the rare places where you meet many CAD and PLM people at the same time at the same place. You don’t need to guess a lot why so. MIT CAD Lab as well as many companies in this domain made Greater Boston a unique place for talents in CAD and PLM space.

Tech Soft 3D is well known technological outfit helping many companies in CAD and PLM domain to develop successful products. Besides that Tech Soft 3D is sponsoring a gathering of technological fellows in the CAD/PLM domain to come, network and share their experience – Tech Talk. Yesterday was my first time attending Tech Talk in downtown Boston. I missed one last year because of crazy travel schedule. This year I’ve been honored to get invited and make a short speak. I shared my experience and thoughts about database and data management technological trends. As part of my presentation I shared my thoughts about so called NoSQL trend, what it contains and how it can be useful for CAD, PDM/PLM. Below you can see a full slide deck of my presentation.

PLM and Data Management in 21st Century from Oleg Shilovitsky

On the following slide, you can see a simplified decision table that can help you to designate what noSQL databases can be useful for different type of solutions.

PLM-and-database-options

What is my conclusion? Database and data management technology is going through cambrian explosion of different options and flavors. It is a result of massive amount of development coming from open source, web and other places. Database is moving from “solution” into “toolbox” status. Single database (mostly RDBMS) is no longer a straightforward decision for all your development tasks. My hunch, CAD/PLM developers need to ramp up with with tools and knowledge to tackle with future database decisions. Just my thoughts…
Best, Oleg


PDM 101: Engineering Document Management Fallacy

August 30, 2013

We love new technologies and trends. However, from time to time, I want to get back to basic topics of engineering and manufacturing software. The topic I’d like to discuss today is Engineering Document Management (EDM). This post was triggered by DM vs. EDM article by Scott Cleveland on 2PLM letter. Here is the passage Scott use to explain the main difference:

Document management can be as simple as saving a document to a protected directory. It could be any of the document management software packages like SharePoint. Engineering document management is a different beast. Engineering document management follows some basic engineering rules. The concept is that of a vault.

Later in the article engineering rules are explained as access control, version control, process states (create, change, release) and audit trail.

I found myself a bit confused by this definition. There are many document management systems that will comply with rules described above. However, I’d not recommend to use these systems for engineering document management purposes. I took a look in wikipedia and here is what I found. Navigate to the following wikipedia link about Document Management System (DMS). The article is quite comprehensive. Here is a short passage that defines DMS:

A document management system (DMS) is a computer system (or set of computer programs) used to track and store electronic documents. It is usually also capable of keeping track of the different versions modified by different users (history tracking). The term has some overlap with the concepts of content management systems. It is often viewed as a component of enterprise content management (ECM) systems and related to digital asset management, document imaging, workflow systems and records management systems. Document management systems commonly provide storage, versioning, metadata, security, as well as indexing and retrieval capabilities.

Later in the article, I found a very useful table describing functions and components of document management. One of the them (very important) is Versioning:

Versioning is a process by which documents are checked in or out of the document management system, allowing users to retrieve previous versions and to continue work from a selected point. Versioning is useful for documents that change over time and require updating, but it may be necessary to go back to or reference a previous copy.

Now, let’s move forward and see what wikipedia states about Engineering Document Management (EDM). I didn’t find a separate EDM article. The most relevant one was Technical Data Management derived from Document Management System (DMS). I captured the following important passage:

A Technical Data Management System (TDMS) is essentially a Document management system (DMS) pertaining to the management of technical and engineering drawings and documents. Often the data are contained in ‘records’ of various forms, such on paper, microfilms or on digital media. Hence technical data management is also concerned with record management involving purely technical or techno-commercial or techno-legal information or data.

Wikipedia article compares TDMS and DMS in a following way:

TDMS functions are conceptually similar to that of conventional archive functions, except that the archived material in this case are essentially engineering drawings, survey maps, technical specifications, plant and equipment data sheets, feasibility reports, project reports, operation and maintenance manuals, standards, etc.

In my view, these days, most of people are associating Engineering Document Management directly with PDM. Navigate to wikipedia page EDM page and you find a confirmation to that (Engineering Data Management, also known as Product Data Management).

So, what is so special and different about Engineering Document Management that confuses many people? In my view, it comes down to the type of data system is managing. It is about CAD models, Drawings, Design, Simulation, etc. This data is semantically rich and contains lots of connections and constraints. To manage versions of Excel files is easy. Many document management systems can do so. However, to manage versions of SolidWorks or Inventor assemblies is not so simple. You need to track dependencies between parts, drawings and other elements of interconnected data.

What is my conclusion? Semantic complexity makes engineering document management complicated. It is all about connections and data dependencies. This is a specialty of engineering document management software. To manage revisions of interconnected files is complicated. It cannot be done on a level of single file and requires different approach. Engineering Document Management (today mostly known as PDM) is a special class of data management solutions used for this purposes. Just my thoughts…

Best, Oleg


PLM: Data vs Process – Wrong Dilemma?

August 7, 2013

Recent debate on Tech4PD brought back one of my favorite topics in PLM – data vs. process. The topic isn’t new, but it is not diminishing the importance. I found first appearance of my debates with Jim going to back in 2009. Navigate to the following link and read my old blog – PDM vs. PLM: Is it about the process? Another perspective on data vs. process in PLM was presented in my blog post – PLM: controversy about process vs. data managemen. The last one was inspired by Bell Helicopter presentation made during Dassault Customer Conference back in 2011.

Take a moment of time and watch the debate. I gave my vote to Jim. I like his broad perspective on setting organization on the right path with their working procedures. Jim also "packaged" his process opinion together with "file management", which made me assume that engineers will be able to identify right versions of a specific file/design. What made me feel sad a bit with regards to Chad’s position is his wiliness to focus on how to control all data in PLM – something I have hard time to believe as needed and even possible. To me PLM cannot control all data, but should rely on technologies to make data available for decision (and not only) processes.

The debate made me think about why Data vs. Process is probably a wrong dilemma in the context of PLM. In my view, the right focus should be on "lifecycle" as a core value proposition of PLM and ability of PLM to support product development. In a nutshell, product development is about how to move product definition (in a broad sense of this word) from initial requirements and design to engineering and manufacturing. If I go future, next stages of product definition will be related to maintenance and disposal. To define what represent product on every stage together with what is required to move product from one stage to another is a core value of product lifecycle and PLM.

What is my conclusion? After many years of debates about data vs. processes, I think time came to get to the next mature level of understanding how to get PLM work for companies. The focus on product definition for every stage of product lifecycle bundled together with procedures or requirements needed in order to move between stages can be a new way to define what PLM is about. Just my thoughts…

Best, Oleg


How Amazon helps cloud PLM to connect to enterprise data?

April 16, 2013

Face it, even cloud is trending and growing fast, on enterprise premise systems are representing a major part of engineering and manufacturing systems in organizations. It includes ERP, CRM, PDM, PLM systems as well as zillions of Excels and CAD files. I’ve been thinking how to optimize cloud/on-premise data co-existance. My attention was caught by the news about Amazon Storage Gateway. Amazon, in its push to draw more enterprise customers, had to make sure the Amazon Storage Gateway will run in Microsoft Hyper-v virtualized shops. Which expands the ability of Amazon to synchronize data between cloud and on premise environment.

For those of you not familiar with ASG (Amazon Storage Gateway), navigate to the following link to learn more. The AWS Storage Gateway supports two configurations:

1/ Gateway-Cached Volumes: You can store your primary data in Amazon S3, and retain your frequently accessed data locally. Gateway-Cached volumes provide substantial cost savings on primary storage, minimize the need to scale your storage on-premises, and retain low-latency access to your frequently accessed data.

2/ Gateway-Stored Volumes: In the event you need low-latency access to your entire data set, you can configure your on-premises gateway to store your primary data locally, and asynchronously back up point-in-time snapshots of this data to Amazon S3. Gateway-Stored volumes provide durable and inexpensive off-site backups that you can recover locally or from Amazon EC2 if, for example, you need replacement capacity for disaster recovery.

The two options are representing an interesting option on how enterprise data can co-exist between cloud and on-premise environments. I can see mid-size companies are doing it to optimize their file storages. Larger companies can use it for extended value chain communication.

What is my conclusion? As cloud systems will expand in organizations, the demand for hybrid environment will grow as well. Companies won’t be able to migrate enterprise data assets outside of organizations fast, therefore cloud PLM solutions that will be able to communicate and co-exist in hybrid deployments will grow. The ability to connect existing enterprise data assets and cloud apps is a key to make future cloud expansion. Just my thoughts…

Best, Oleg



PDM and Data Sharing Changing Paradigm

January 15, 2013

I would like to speak about PDM today. You can hardly find engineers that like data management. For many years, Product Data Management (PDM) kept the score of inevitable evil in engineering and manufacturing software. Everybody wants data, but nobody want to manage it. At the same time, even if PDM is quite challenging in terms of implementation, it brings a lot of benefits. Navigate to the following link to read Jim Browns’ Best Practices for Managing Data. Data sharing is one of the most important aspects PDM is supposed to solve. Difficulties to share data with internal and external colleagues is one of the most critical aspects of data management.

However, the problem of files sharing is relevant outside of PDM too. Consumerization is one of the strongest technological trends these days. Few days ago, the following CMSwire article and infographic caught my attention – The evolution of file sharing. The article speaks about mobility and mobile access. Take a look on the picture – it is self explaining.

It is interesting to see how data security was one of the key important aspects related to enabling of data sharing even back in 1950s. The following passage was my favorite:

Concern over who is accessing what files is not unique to the use of mobile devices. In the Mad Men era of the 1960s, sensitive files were kept under lock and key in cabinets. Only people with physical keys could access those files and information, and careful lists of those with access were kept. However, the widespread use of inventions like the copier by the 1950s and the fax machine by the 1960s introduced new security threats as these documents could then be replicated.

Mobile and cloud technologies are revolutionizing data sharing paradigms. One of examples I specially like is Chrome tabs access across devices. If you are using Chrome browser, you can share the information open between different browsers in different devices.

What is my conclusion? Technological landscape is changing very fast these days. The fundamentals of PDM were invented 15-20 years ago. I don’t think these fundamental assumptions will survive under new requirements coming with mobile access revolution. Technology and shift in workforce will be driving a new wave of innovation in manufacturing. The technology will become more transparent for users and more sophisticated internally. It is a time to re-think paradigm. Files and data need to be shared, but technology should be invisible. Just my thoughts…

Best, Oleg

Infographic credit to CMSWire article.


PLM and Information Strategy Focus

October 2, 2012

Nobody is not surprised how important information nowadays. Actually, maybe it is not true. What we usually do was called "data management" – CAD,Engineering Document / Data Management, Product Data Management, Product Lifecycle Management. Data played an important role in this process of "management". However, the biggest confusion was created by the CAD/PLM industry was about losing the point of information importance.

Information in Google Age

I think, we learned lesson or two during the last ten years of Google Age. The ultimate focus of Google was about how to create an information consumption culture. It doesn’t matter where information resides, but it does matter and very important how effectively we can get an access to the information and consume it.

Information and the business impact

The business systems eco system is different. People didn’t pay much attention to the importance of information culture and information awareness. Recently, I can see an increased awareness about the role of information companies. I was reading Forester blog couple of days ago – Focus Your Information Strategy On Business Impact by Gene Leganza. Have a read and make your opinion. However, I found the follow quote very important in the context of what PLM companies are doing these days:

Getting the right information to the right people at the right time.There’s little more frustrating than knowing that somewhere, inaccessible to you, your firm has collected the data that can inform the decision you’re trying to make. Does the loyalty of the customer on the phone warrant waiving your standard policy on returns? Is there a pattern to the process errors you’re experiencing in part of your operation? Is there conflicting information in the forms you’ve collected to comply with regulations before launching an expensive initiative? A well-defined information architecture tells you where that information is, and a well-executed information strategy provides the tools to access it to the staff that needs them, when it needs them.

Companies in PLM eco-systems are focusing more on the information. It is not "a database can do everything" story anymore. There are many examples – Dassault acquired Exalead, TeamCenter released Active Workspace, Autodesk acquired Inforbix technologies. I’m sure we are going to see more examples in the future.

What is my conclusion? Long time we’ve been focusing on data – how to produce it, how to control it, how to change it. However, we missed to importance of how to consume data. To me it means the creation of "information awareness". It is an important shift. I think vendors and customers will need to pay attention to that. Just my thoughts…

Best, Oleg

Image courtesy of [Stuart Miles] / FreeDigitalPhotos.net


PLM Think Tank Top 5 – August. Thoughts about Pink Lady Apples.

August 27, 2012

I screw up my promise to stop blogging during my vacation. I’m in Israel these days with my family. You are probably asking what this picture of Pink Lady apple does on my blog. I made yesterday evening in the hotel in Tel-Aviv where I’m staying. Of course, I appreciate the hotel for complimentary welcome service. At the same time, what struck me is that this apple was absolutely identical to the apple from local Costco store in Brookline, Mass I ate just before leaving home. Amazing example of global supply channels. What potentially can make apple made in USA travels all the way down to Middle East. I found hard to find the answer on this question. Is there a chance future PLM data services will be able to answer these questions? If you have an idea of explanation, speak your mind. Now, let me turn it back to a traditional top 5 post.

What is the right data model for PLM?

Many of the technologies used by PLM companies these days are outdated and came from the past 20-25 years. There is nothing wrong in these technologies. They are proven and successfully used for many applications. However, in order to achieve the next level of efficiency and embrace future of PLM, new horizons need to be explored. Data flexibility, openness and interoperability – these elements are absolutely important in the future of PLM. Options to use future data models coming from past 10 years of web experience need to be explored. Important.

What is the future of PLM databases?

The complexity of product lifecycle problems brings the need of new concepts in data modeling and data management. One of the main questions – how to break the boundary of a single database? This is a key question, in my view. It will solve the problem of logical scalability and provide a platform for future information discovery.

PLM Supply Chain – Go Big Data or Go Home

Big data is one of the big things PLM can use to optimize supply chain, in my view. PLM vendors need to switch gears from supply data exchange towards supply chain optimization. In order to do so, PLM vendors need to bring additional capabilities to analyze supply chain, related information. It is an important topic to for coming years.

How to Shift from Noisy PLM to Calm Technologies?

In Designing Calm Technology, Weiser and John Seely Brown describe calm technology as “that which informs but doesn’t demand our focus or attention.” I want collaborative software to stop to behave as a noisy monster and move to state of “an invisible quite servant”. I don’t think, there is a simple recipe how to do so. PLM vendors can look for examples in consumer devices, web and mobile application behaviors and other consumer-oriented technologies and companies. I see it quite possible.

Will DoD Strategy Change Cloud PLM Future?

Speaking about future cloud systems, I think the keyword “optimization” is the most important one. Everybody is looking towards efficiency these days. It is equally important to small companies and large institution. In my view, larger companies will come soon to PLM providers with questions about how PLM environment can be optimized towards cloud computing. And this is just a matter of time when it happens. PLM vendors have some time for preparation. However, not too much time.

Best, Oleg


Part numbers and External Classification Schemas

February 8, 2012

fingerprint-253x300.jpgI want to talk about Part Numbers. Yes, Part Numbers, again… My previous blog -Part Numbering and the future of identification raised few interesting conversations. So, I decided to open a Pandora box of part numbering. The formal trigger for this conversation was Arena Solutions blog – Three consideration when choosing Part Numbering schema for you. Here is passage that actually made me think about the fact we are doing something wrong:

Choosing a part numbering scheme is one of the more important decisions you make as you move toward production… Once you commit to a part numbering scheme, you are married to it for a long time to come, so you need to be 100% sure it is nimble enough to evolve and scale right along with you...

It sounded like a Catholic marriage. Once you decided about part numbering, you are done for many years. The same Arena’s blog post mentioned some external tools you can use to generate part numbers – part-numbering.com and partnumber.com.

The idea that stroke me earlier today is that most of the companies are using “smart Part Numbers” in order to simplify part search, re-use and, even more fundamentally, classification. Type of part, organization, suppliers – these are only small elements of “an intelligent part number”. What if some “smart applications” are available that can add classification information to existing part numbers in order to enrich (actually to annotate) Part Number identification. These tools can be web-based and even applied to existing data in the company.

What is my conclusion? We need to re-think some very fundamental elements and concepts of product development, PDM and PLM. The ability to enrich data without building lots of sophistication in the Part Numbering is something that can make PDM / PLM systems more flexible and drive cost of changes down. I’d be interested how to support it in existing PDM/PLM systems. Not sure if it is a simple task. However, I’m curious if new PLM software coming tomorrow to market from companies like Autodesk will have a different set of capabilities to solve the problem of Part Numbering and identification. Just my thoughts…

Best, Oleg


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