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The Open Group Panel: Internet of Things – Opportunities and Obstacles

Below is the transcript of The Open Group podcast exploring the challenges and ramifications of the Internet of Things, as machines and sensors collect vast amounts of data.

Listen to the podcast.

Dana Gardner: Hello, and welcome to a special BriefingsDirect thought leadership interview series coming to you in conjunction with recent The Open Group Boston 2014 on July 21 in Boston.

Dana Gardner I’m Dana Gardner, principal analyst at Interarbor Solutions, and I’ll be your host and moderator throughout these discussions on Open Platform 3.0 and Boundaryless Information Flow.

We’re going to now specifically delve into the Internet of Things with a panel of experts. The conference has examined how Open Platform 3.0™ leverages the combined impacts of cloud, big data, mobile, and social. But to each of these now we can add a new cresting wave of complexity and scale as we consider the rapid explosion of new devices, sensors, and myriad endpoints that will be connected using internet protocols, standards and architectural frameworks.

This means more data, more cloud connectivity and management, and an additional tier of “things” that are going to be part of the mobile edge — and extending that mobile edge ever deeper into even our own bodies.

When we think about inputs to these social networks — that’s going to increase as well. Not only will people be tweeting, your device could be very well tweet, too — using social networks to communicate. Perhaps your toaster will soon be sending you a tweet about your English muffins being ready each morning.

The Internet of Things is more than the “things” – it means a higher order of software platforms. For example, if we are going to operate data centers with new dexterity thanks to software-definited networking (SDN) and storage (SDS) — indeed the entire data center being software-defined (SDDC) — then why not a software-defined automobile, or factory floor, or hospital operating room — or even a software-defined city block or neighborhood?

And so how does this all actually work? Does it easily spin out of control? Or does it remain under proper management and governance? Do we have unknown unknowns about what to expect with this new level of complexity, scale, and volume of input devices?

Will architectures arise that support the numbers involved, interoperability, and provide governance for the Internet of Things — rather than just letting each type of device do its own thing?

To help answer some of these questions, The Open Group assembled a distinguished panel to explore the practical implications and limits of the Internet of Things. So please join me in welcoming Said Tabet, Chief Technology Officer for Governance, Risk and Compliance Strategy at EMC, and a primary representative to the Industrial Internet Consortium; Penelope Gordon, Emerging Technology Strategist at 1Plug Corporation; Jean-Francois Barsoum, Senior Managing Consultant for Smarter Cities, Water and Transportation at IBM, and Dave Lounsbury, Chief Technical Officer at The Open Group.

Jean-Francois, we have heard about this notion of “cities as platforms,” and I think the public sector might offer us some opportunity to look at what is going to happen with the Internet of Things, and then extrapolate from that to understand what might happen in the private sector.

Hypothetically, the public sector has a lot to gain. It doesn’t have to go through the same confines of a commercial market development, profit motive, and that sort of thing. Tell us a little bit about what the opportunity is in the public sector for smart cities.

Barsoum_Jean-FrancoisJean-Francois Barsoum: It’s immense. The first thing I want to do is link to something that Marshall Van Alstyne (Professor at Boston University and Researcher at MIT) had talked about, because I was thinking about his way of approaching platforms and thinking about how cities represent an example of that.

You don’t have customers; you have citizens. Cities are starting to see themselves as platforms, as ways to communicate with their customers, their citizens, to get information from them and to communicate back to them. But the complexity with cities is that as a good a platform as they could be, they’re relatively rigid. They’re legislated into existence and what they’re responsible for is written into law. It’s not really a market.

Chris Harding (Forum Director of The Open Group Open Platform 3.0) earlier mentioned, for example, water and traffic management. Cities could benefit greatly by managing traffic a lot better.

Part of the issue is that you might have a state or provincial government that looks after highways. You might have the central part of the city that looks after arterial networks. You might have a borough that would look after residential streets, and these different platforms end up not talking to each other.

They gather their own data. They put in their own widgets to collect information that concerns them, but do not necessarily share with their neighbor. One of the conditions that Marshall said would favor the emergence of a platform had to do with how much overlap there would be in your constituents and your customers. In this case, there’s perfect overlap. It’s the same citizen, but they have to carry an Android and an iPhone, despite the fact it is not the best way of dealing with the situation.

The complexities are proportional to the amount of benefit you could get if you could solve them.

Gardner: So more interoperability issues?

Barsoum: Yes.

More hurdles

Gardner: More hurdles, and when you say commensurate, you’re saying that the opportunity is huge, but the hurdles are huge and we’re not quite sure how this is going to unfold.

Barsoum: That’s right.

Gardner: Let’s go to an area where the opportunity outstrips the challenge, manufacturing. Said, what is the opportunity for the software-defined factory floor for recognizing huge efficiencies and applying algorithmic benefits to how management occurs across domains of supply-chain, distribution, and logistics. It seems to me that this is a no-brainer. It’s such an opportunity that the solution must be found.

Tabet_SaidSaid Tabet: When it comes to manufacturing, the opportunities are probably much bigger. It’s where we can see a lot of progress that has already been done and still work is going on. There are two ways to look at it.

One is the internal side of it, where you have improvements of business processes. For example, similar to what Jean-Francois said, in a lot of the larger companies that have factories all around the world, you’ll see such improvements on a factory base level. You still have those silos at that level.

Now with this new technology, with this connectedness, those improvements are going to be made across factories, and there’s a learning aspect to it in terms of trying to manage that data. In fact, they do a better job. We still have to deal with interoperability, of course, and additional issues that could be jurisdictional, etc.

However, there is that learning that allows them to improve their processes across factories. Maintenance is one of them, as well as creating new products, and connecting better with their customers. We can see a lot of examples in the marketplace. I won’t mention names, but there are lots of them out there with the large manufacturers.

Gardner: We’ve had just-in-time manufacturing and lean processes for quite some time, trying to compress the supply chain and distribution networks, but these haven’t necessarily been done through public networks, the internet, or standardized approaches.

But if we’re to benefit, we’re going to need to be able to be platform companies, not just product companies. How do you go from being a proprietary set of manufacturing protocols and approaches to this wider, standardized interoperability architecture?

Tabet: That’s a very good question, because now we’re talking about that connection to the customer. With the airline and the jet engine manufacturer, for example, when the plane lands and there has been some monitoring of the activity during the whole flight, at that moment, they’ll get that data made available. There could be improvements and maybe solutions available as soon as the plane lands.

Interoperability

That requires interoperability. It requires Platform 3.0 for example. If you don’t have open platforms, then you’ll deal with the same hurdles in terms of proprietary technologies and integration in a silo-based manner.

Gardner: Penelope, you’ve been writing about the obstacles to decision-making that might become apparent as big data becomes more prolific and people try to capture all the data about all the processes and analyze it. That’s a little bit of a departure from the way we’ve made decisions in organizations, public and private, in the past.

Of course, one of the bigger tenets of Internet of Things is all this great data that will be available to us from so many different points. Is there a conundrum of some sort? Is there an unknown obstacle for how we, as organizations and individuals, can deal with that data? Is this going to be chaos, or is this going to be all the promises many organizations have led us to believe around big data in the Internet of Things?

Gordon_PenelopePenelope Gordon: It’s something that has just been accelerated. This is not a new problem in terms of the decision-making styles not matching the inputs that are being provided into the decision-making process.

Former US President Bill Clinton was known for delaying making decisions. He’s a head-type decision-maker and so he would always want more data and more data. That just gets into a never-ending loop, because as people collect data for him, there is always more data that you can collect, particularly on the quantitative side. Whereas, if it is distilled down and presented very succinctly and then balanced with the qualitative, that allows intuition to come to fore, and you can make optimal decisions in that fashion.

Conversely, if you have someone who is a heart-type or gut-type decision-maker and you present them with a lot of data, their first response is to ignore the data. It’s just too much for them to take in. Then you end up completely going with whatever you feel is correct or whatever you have that instinct that it’s the correct decision. If you’re talking about strategic decisions, where you’re making a decision that’s going to influence your direction five years down the road, that could be a very wrong decision to make, a very expensive decision, and as you said, it could be chaos.

It just brings to mind to me Dr. Suess’s The Cat in the Hat with Thing One and Thing Two. So, as we talk about the Internet of Things, we need to keep in mind that we need to have some sort of structure that we are tying this back to and understanding what are we trying to do with these things.

Gardner: Openness is important, and governance is essential. Then, we can start moving toward higher-order business platform benefits. But, so far, our panel has been a little bit cynical. We’ve heard that the opportunity and the challenges are commensurate in the public sector and that in manufacturing we’re moving into a whole new area of interoperability, when we think about reaching out to customers and having a boundary that is managed between internal processes and external communications.

And we’ve heard that an overload of data could become a very serious problem and that we might not get benefits from big data through the Internet of Things, but perhaps even stumble and have less quality of decisions.

So Dave Lounsbury of The Open Group, will the same level of standardization work? Do we need a new type of standards approach, a different type of framework, or is this a natural path and course what we have done in the past?

Different level

Lounsbury_DaveDave Lounsbury: We need to look at the problem at a different level than we institutionally think about an interoperability problem. Internet of Things is riding two very powerful waves, one of which is Moore’s Law, that these sensors, actuators, and network get smaller and smaller. Now we can put Ethernet in a light switch right, a tag, or something like that.

Also, Metcalfe’s Law that says that the value of all this connectivity goes up with the square of the number of connected points, and that applies to both the connection of the things but more importantly the connection of the data.

The trouble is, as we have said, that there’s so much data here. The question is how do you manage it and how do you keep control over it so that you actually get business value from it. That’s going to require us to have this new concept of a platform to not only to aggregate, but to just connect the data, aggregate it, correlate it as you said, and present it in ways that people can make decisions however they want.

Also, because of the raw volume, we have to start thinking about machine agency. We have to think about the system actually making the routine decisions or giving advice to the humans who are actually doing it. Those are important parts of the solution beyond just a simple “How do we connect all the stuff together?”

Gardner: We might need a higher order of intelligence, now that we have reached this border of what we can do with our conventional approaches to data, information, and process.

Thinking about where this works best first in order to then understand where it might end up later, I was intrigued again this morning by Professor Van Alstyne. He mentioned that in healthcare, we should expect major battles, that there is a turf element to this, that the organization, entity or even commercial corporation that controls and manages certain types of information and access to that information might have some very serious platform benefits.

The openness element now is something to look at, and I’ll come back to the public sector. Is there a degree of openness that we could legislate or regulate to require enough control to prevent the next generation of lock-in, which might not be to a platform to access to data information and endpoints? Where is it in the public sector that we might look to a leadership position to establish needed openness and not just interoperability.

Barsoum: I’m not even sure where to start answering that question. To take healthcare as an example, I certainly didn’t write the bible on healthcare IT systems and if someone did write that, I think they really need to publish it quickly.

We have a single-payer system in Canada, and you would think that would be relatively easy to manage. There is one entity that manages paying the doctors, and everybody gets covered the same way. Therefore, the data should be easily shared among all the players and it should be easy for you to go from your doctor, to your oncologist, to whomever, and maybe to your pharmacy, so that everybody has access to this same information.

We don’t have that and we’re nowhere near having that. If I look to other areas in the public sector, areas where we’re beginning to solve the problem are ones where we face a crisis, and so we need to address that crisis rapidly.

Possibility of improvement

In the transportation infrastructure, we’re getting to that point where the infrastructure we have just doesn’t meet the needs. There’s a constraint in terms of money, and we can’t put much more money into the structure. Then, there are new technologies that are coming in. Chris had talked about driverless cars earlier. They’re essentially throwing a wrench into the works or may be offering the possibility of improvement.

On any given piece of infrastructure, you could fit twice as many driverless cars as cars with human drivers in them. Given that set of circumstances, the governments are going to find they have no choice but to share data in order to be able to manage those. Are there cases where we could go ahead of a crisis in order to manage it? I certainly hope so.

Gardner: How about allowing some of the natural forces of marketplaces, behavior, groups, maybe even chaos theory, where if sufficient openness is maintained there will be some kind of a pattern that will emerge? We need to let this go through its paces, but if we have artificial barriers, that might be thwarted or power could go to places that we would regret later.

Barsoum: I agree. People often focus on structure. So the governance doesn’t work. We should find some way to change the governance of transportation. London has done a very good job of that. They’ve created something called Transport for London that manages everything related to transportation. It doesn’t matter if it’s taxis, bicycles, pedestrians, boats, cargo trains, or whatever, they manage it.

You could do that, but it requires a lot of political effort. The other way to go about doing it is saying, “I’m not going to mess with the structures. I’m just going to require you to open and share all your data.” So, you’re creating a new environment where the governance, the structures, don’t really matter so much anymore. Everybody shares the same data.

Gardner: Said, to the private sector example of manufacturing, you still want to have a global fabric of manufacturing capabilities. This is requiring many partners to work in concert, but with a vast new amount of data and new potential for efficiency.

How do you expect that openness will emerge in the manufacturing sector? How will interoperability play when you don’t have to wait for legislation, but you do need to have cooperation and openness nonetheless?

Tabet: It comes back to the question you asked Dave about standards. I’ll just give you some examples. For example, in the automotive industry, there have been some activities in Europe around specific standards for communication.

The Europeans came to the US and started to have discussions, and the Japanese have interest, as well as the Chinese. That shows, because there is a common interest in creating these new models from a business standpoint, that these challenges they have to be dealt with together.

Managing complexity

When we talk about the amounts of data, what we call now big data, and what we are going to see in about five years or so, you can’t even imagine. How do we manage that complexity, which is multidimensional? We talked about this sort of platform and then further, that capability and the data that will be there. From that point of view, openness is the only way to go.

There’s no way that we can stay away from it and still be able to work in silos in that new environment. There are lots of things that we take for granted today. I invite some of you to go back and read articles from 10 years ago that try to predict the future in technology in the 21st century. Look at your smart phones. Adoption is there, because the business models are there, and we can see that progress moving forward.

Collaboration is a must, because it is a multidimensional level. It’s not just manufacturing like jet engines, car manufacturers, or agriculture, where you have very specific areas. They really they have to work with their customers and the customers of their customers.

Adoption is there, because the business models are there, and we can see that progress moving forward.

Gardner: Dave, I have a question for both you and Penelope. I’ve seen some instances where there has been a cooperative endeavor for accessing data, but then making it available as a service, whether it’s an API, a data set, access to a data library, or even analytics applications set. The Ocean Observatories Initiative is one example, where it has created a sensor network across the oceans and have created data that then they make available.

Do you think we expect to see an intermediary organization level that gets between the sensors and the consumers or even controllers of the processes? Is there’s a model inherent in that that we might look to — something like that cooperative data structure that in some ways creates structure and governance, but also allows for freedom? It’s sort of an entity that we don’t have yet in many organizations or many ecosystems and that needs to evolve.

Lounsbury: We’re already seeing that in the marketplace. If you look at the commercial and social Internet of Things area, we’re starting to see intermediaries or brokers cropping up that will connect the silo of my android ecosystem to the ecosystem of package tracking or something like that. There are dozens and dozens of these cropping up.

In fact, you now see APIs even into a silo of what you might consider a proprietary system and what people are doing is to to build a layer on top of those APIs that intermediate the data.

This is happening on a point-to-point basis now, but you can easily see the path forward. That’s going to expand to large amounts of data that people will share through a third party. I can see this being a whole new emerging market much as what Google did for search. You could see that happening for the Internet of Things.

Gardner: Penelope, do you have any thoughts about how that would work? Is there a mutually assured benefit that would allow people to want to participate and cooperate with that third entity? Should they have governance and rules about good practices, best practices for that intermediary organization? Any thoughts about how data can be managed in this sort of hierarchical model?

Nothing new

Gordon: First, I’ll contradict it a little bit. To me, a lot of this is nothing new, particularly coming from a marketing strategy perspective, with business intelligence (BI). Having various types of intermediaries, who are not only collecting the data, but then doing what we call data hygiene, synthesis, and even correlation of the data has been around for a long time.

It was an interesting, when I looked at recent listing of the big-data companies, that some notable companies were excluded from that list — companies like Nielsen. Nielsen’s been collecting data for a long time. Harte-Hanks is another one that collects a tremendous amount of information and sells that to companies.

That leads into the another part of it that I think there’s going to be. We’re seeing an increasing amount of opportunity that involves taking public sources of data and then providing synthesis on it. What remains to be seen is how much of the output of that is going to be provided for “free”, as opposed to “fee”. We’re going to see a lot more companies figuring out creative ways of extracting more value out of data and then charging directly for that, rather than using that as an indirect way of generating traffic.

Gardner: We’ve seen examples of how this has been in place. Does it scale and does the governance or lack of governance that might be in the market now sustain us through the transition into Platform 3.0 and the Internet of Things.

Gordon: That aspect is the lead-on part of “you get what you pay for”. If you’re using a free source of data, you don’t have any guarantee that it is from authoritative sources of data. Often, what we’re getting now is something somebody put it in a blog post, and then that will get referenced elsewhere, but there was nothing to go back to. It’s the shaky supply chain for data.

You need to think about the data supply and that is where the governance comes in. Having standards is going to increasingly become important, unless we really address a lot of the data illiteracy that we have. A lot of people do not understand how to analyze data.

One aspect of that is a lot of people expect that we have to do full population surveys, as opposed representative sampling to get much more accurate and much more cost-effective collection of data. That’s just one example, and we do need a lot more in governance and standards.

Gardner: What would you like to see changed most in order for the benefits and rewards of the Internet of Things to develop and overcome the drawbacks, the risks, the downside? What, in your opinion, would you like to see happen to make this a positive, rapid outcome? Let’s start with you Jean-Francois.

Barsoum: There are things that I have seen cities start to do now. There are couple of examples: Philadelphia is one and Barcelona does this too. Rather than do the typical request for proposal (RFP), where they say, “This is the kind of solution we’re looking for, and here are our parameters. Can l you tell us how much it is going to cost to build,” they come to you with the problem and they say, “Here is the problem I want to fix. Here are my priorities, and you’re at liberty to decide how best to fix the problem, but tell us how much that would cost.”

If you do that and you combine it with access to the public data that is available — if public sector opens up its data — you end up with a very powerful combination that liberates a lot of creativity. You can create a lot of new business models. We need to see much more of that. That’s where I would start.

More education

Tabet: I agree with Jean-Francois on that. What I’d like to add is that I think we need to push the relation a little further. We need more education, to your point earlier, around the data and the capabilities.

We need these platforms that we can leverage a little bit further with the analytics, with machine learning, and with all of these capabilities that are out there. We have to also remember, when we talk about the Internet of Things, it is things talking to each other.

So it is not human-machine communication. Machine-to-machine automation will be further than that, and we need more innovation and more work in this area, particularly more activity from the governments. We’ve seen that, but it is a little bit frail from that point of view right now.

Gardner: Dave Lounsbury, thoughts about what need to happen in order to keep this on the tracks?

Lounsbury: We’ve touched on lot of them already. Thank you for mentioning the machine-to-machine part, because there are plenty of projections that show that it’s going to be the dominant form of Internet communication, probably within the next four years.

So we need to start thinking of that and moving beyond our traditional models of humans talking through interfaces to set of services. We need to identify the building blocks of capability that you need to manage, not only the information flow and the skilled person that is going to produce it, but also how you manage the machine-to-machine interactions.

Gordon: I’d like to see not so much focus on data management, but focus on what is the data managing and helping us to do. Focusing on the machine-to-machine and the devices is great, but it should be not on the devices or on the machines… it should be on what can they accomplish by communicating; what can you accomplish with the devices and then have a reverse engineer from that.

Gardner: Let’s go to some questions from the audience. The first one asks about a high order of intelligence which we mentioned earlier. It could be artificial intelligence, perhaps, but they ask whether that’s really the issue. Is the nature of the data substantially different, or we are just creating more of the same, so that it is a storage, plumbing, and processing problem? What, if anything, are we lacking in our current analytics capabilities that are holding us back from exploiting the Internet of Things?

Gordon: I’ve definitely seen that. That has a lot to do with not setting your decision objectives and your decision criteria ahead of time so that you end up collecting a whole bunch of data, and the important data gets lost in the mix. There is a term “data smog.”

Most important

The solution is to figure out, before you go collecting data, what data is most important to you. If you can’t collect certain kinds of data that are important to you directly, then think about how to indirectly collect that data and how to get proxies. But don’t try to go and collect all the data for that. Narrow in on what is going to be most important and most representative of what you’re trying to accomplish.

Gardner: Does anyone want to add to this idea of understanding what current analytics capabilities are lacking, if we have to adopt and absorb the Internet of Things?

Barsoum: There is one element around projection into the future. We’ve been very good at analyzing historical information to understand what’s been happening in the past. We need to become better at projecting into the future, and obviously we’ve been doing that for some time already.

But so many variables are changing. Just to take the driverless car as an example. We’ve been collecting data from loop detectors, radar detectors, and even Bluetooth antennas to understand how traffic moves in the city. But we need to think harder about what that means and how we understand the city of tomorrow is going to work. That requires more thinking about the data, a little bit like what Penelope mentioned, how we interpret that, and how we push that out into the future.

Lounsbury: I have to agree with both. It’s not about statistics. We can use historical data. It helps with lot of things, but one of the major issues we still deal with today is the question of semantics, the meaning of the data. This goes back to your point, Penelope, around the relevance and the context of that information – how you get what you need when you need it, so you can make the right decisions.

Gardner: Our last question from the audience goes back to Jean-Francois’s comments about the Canadian healthcare system. I imagine it applies to almost any healthcare system around the world. But it asks why interoperability is so difficult to achieve, when we have the power of the purse, that is the market. We also supposedly have the power of the legislation and regulation. You would think between one or the other or both that interoperability, because the stakes are so high, would happen. What’s holding it up?

Barsoum: There are a couple of reasons. One, in the particular case of healthcare, is privacy, but that is one that you could see going elsewhere. As soon as you talk about interoperability in the health sector, people start wondering where is their data going to go and how accessible is it going to be and to whom.

You need to put a certain number of controls over top of that. What is happening in parallel is that you have people who own some data, who believe they have some power from owning that data, and that they will lose that power if they share it. That can come from doctors, hospitals, anywhere.

So there’s a certain amount of change management you have to get beyond. Everybody has to focus on the welfare of the patient. They have to understand that there has to be a priority, but you also have to understand the welfare of the different stakeholders in the system and make sure that you do not forget about them, because if you forget about them they will find some way to slow you down.

Use of an ecosystem

Lounsbury: To me, that’s a perfect example of what Marshall Van Alstyne talked about this morning. It’s the change from focus on product to a focus on an ecosystem. Healthcare traditionally has been very focused on a doctor providing product to patient, or a caregiver providing a product to a patient. Now, we’re actually starting to see that the only way we’re able to do this is through use of an ecosystem.

That’s a hard transition. It’s a business-model transition. I will put in a plug here for The Open Group Healthcare vertical, which is looking at that from architecture perspective. I see that our Forum Director Jason Lee is over here. So if you want to explore that more, please see him.

Gardner: I’m afraid we will have to leave it there. We’ve been discussing the practical implications of the Internet of Things and how it is now set to add a new dimension to Open Platform 3.0 and Boundaryless Information Flow.

We’ve heard how new thinking about interoperability will be needed to extract the value and orchestrate out the chaos with such vast new scales of inputs and a whole new categories of information.

So with that, a big thank you to our guests: Said Tabet, Chief Technology Officer for Governance, Risk and Compliance Strategy at EMC; Penelope Gordon, Emerging Technology Strategist at 1Plug Corp.; Jean-Francois Barsoum, Senior Managing Consultant for Smarter Cities, Water and Transportation at IBM, and Dave Lounsbury, Chief Technology Officer at The Open Group.

This is Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator throughout these discussions on Open Platform 3.0 and Boundaryless Information Flow at The Open Group Conference, recently held in Boston. Thanks again for listening, and come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript.

Transcript of The Open Group podcast exploring the challenges and ramifications of the Internet of Things, as machines and sensors collect vast amounts of data. Copyright The Open Group and Interarbor Solutions, LLC, 2005-2014. All rights reserved.

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Filed under Boundaryless Information Flow™, Business Architecture, Cloud, Cloud/SOA, Data management, digital technologies, Enterprise Architecture, Future Technologies, Information security, Internet of Things, Interoperability, Open Platform 3.0, Service Oriented Architecture, Standards, Strategy, Supply chain risk, Uncategorized

The Power of APIs – Join The Open Group Tweet Jam on Wednesday, July 9th

By Loren K. Baynes, Director, Global Marketing Communications, The Open Group

The face of technology is evolving at breakneck speed, driven by demand from consumers and businesses alike for more robust, intuitive and integrated service offerings. APIs (application programming interfaces) have made this possible by offering greater interoperability between otherwise disparate software and hardware systems. While there are clear benefits to their use, how do today’s security and value-conscious enterprises take advantage of this new interoperability without exposing them themselves?

On Wednesday, July 9th at 9:00 am PT/12:00 pm ET/5:00 pm GMT, please join us for a tweet jam that will explore how APIs are changing the face of business today, and how to prepare for their implementation in your enterprise.

APIs are at the heart of how today’s technology communicates with one another, and have been influential in enabling new levels of development for social, mobility and beyond. The business benefits of APIs are endless, as are the opportunities to explore how they can be effectively used and developed.

There is reason to maintain a certain level of caution, however, as recent security issues involving open APIs have impacted overall confidence and sustainability.

This tweet jam will look at the business benefits of APIs, as well as potential vulnerabilities and weak points that you should be wary of when integrating them into your Enterprise Architecture.

We welcome The Open Group members and interested participants from all backgrounds to join the discussion and interact with our panel of thought-leaders from The Open Group including Jason Lee, Healthcare and Security Forums Director; Jim Hietala, Vice President of Security; David Lounsbury, CTO; and Dr. Chris Harding, Director for Interoperability and Open Platform 3.0™ Forum Director. To access the discussion, please follow the hashtag #ogchat during the allotted discussion time.

Interested in joining The Open Group Security Forum? Register your interest, here.

What Is a Tweet Jam?

A tweet jam is a 45 minute “discussion” hosted on Twitter. The purpose of the tweet jam is to share knowledge and answer questions on relevant and thought-provoking issues. Each tweet jam is led by a moderator and a dedicated group of experts to keep the discussion flowing. The public (or anyone using Twitter interested in the topic) is encouraged to join the discussion.

Participation Guidance

Here are some helpful guidelines for taking part in the tweet jam:

  • Please introduce yourself (name, title and organization)
  • Use the hashtag #ogchat following each of your tweets
  • Begin your tweets with the question number to which you are responding
  • Please refrain from individual product/service promotions – the goal of the tweet jam is to foster an open and informative dialogue
  • Keep your commentary focused, thoughtful and on-topic

If you have any questions prior to the event or would like to join as a participant, please contact George Morin (@GMorin81 or george.morin@hotwirepr.com).

We look forward to a spirited discussion and hope you will be able to join!

 

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Filed under Data management, digital technologies, Enterprise Architecture, Enterprise Transformation, Information security, Open Platform 3.0, real-time and embedded systems, Standards, Strategy, Tweet Jam, Uncategorized

Future Technologies

By Dave Lounsbury, The Open Group

The Open Group is looking toward the future – what will happen in the next five to ten years?

Those who know us think of The Open Group as being all about consensus, creating standards that are useful to the buy and supply side by creating a stable representation of industry experience – and they would be right. But in order to form this consensus, we must keep an eye on the horizon to see if there are areas that we should be talking about now. The Open Group needs to keep eyes on the future in order to keep pace with businesses looking to gain business advantage by incorporating emerging technologies. According to the McKinsey Global institute[1], “leaders need to plan for a range of scenarios, abandoning assumptions about where competition and risk could come from and not to be afraid to look beyond long-established models.”

To make sure we have this perspective, The Open Group has started a series of Future Technologies workshops. We initiated this at The Open Group Conference in Philadelphia with the goal of identifying emerging business and technical trends that change the shape of enterprise IT.  What are the potential disruptors? How should we be preparing?

As always at The Open Group, we look to our membership to guide us. We assembled a fantastic panel of experts on the topic who offered up insights into the future:

  • Dr. William Lafontaine, VP High Performance Computing, Analytics & Cognitive Markets at IBM Research: Global technology Outlook 2013.
  • Mike Walker, Strategy and Enterprise Architecture Advisor at HP: An Enterprise Architecture’s Journey to 2020.

If you were not able to join us in Philadelphia, you can view the Livestream session on-demand.

Dr. William Lafontaine shared aspects of the company’s Global Technology Outlook 2013, naming the top trends that the company is keeping top of mind, starting with a confluence of social, mobile analytics and cloud.

According to Lafontaine and his colleagues, businesses must prepare for not “mobile also” but “mobile first.” In fact, there will be companies that will exist in a mobile-only environment.

  • Growing scale/lower barrier of entry – More data created, but also more people able to create ways of taking advantage of this data, such as companies that excel at personal interface. Multimedia analytics will become a growing concern for businesses that will be receiving swells of information video and images.
  • Increasing complexity – the Confluence of Social, Mobile, Cloud and Big Data / Analytics will result in masses of data coming from newer, more “complex” places, such as scanners, mobile devices and other “Internet of Things”. Yet, these complex and varied streams of data are more consumable and will have an end-product which is more easily delivered to clients or user.  Smaller businesses are also moving closer toward enterprise complexity. For example, when you swipe your credit card, you will also be shown additional purchasing opportunities based on your past spending habits.  These can include alerts to nearby coffee shops that serve your favorite tea to local bookstores that sell mysteries or your favorite genre.
  •  Fast pace – According to Lafontaine, ideas will be coming to market faster than ever. He introduced the concept of the Minimum Buyable Product, which means take an idea (sometimes barely formed) to inventors to test its capabilities and to evaluate as quickly as possible. Processes that once took months or years can now take weeks. Lafontaine used the MOOC innovator Coursera as an example: Eighteen months ago, it had no clients and existed in zero countries. Now it’s serving over 4 million students around the world in over 29 countries. Deployment of open APIs will become a strategic tool for creation of value.
  • Contextual overload – Businesses have more data than they know what to do with: our likes and dislikes, how we like to engage with our mobile devices, our ages, our locations, along with traditional data of record. The next five years, businesses will be attempting to make sense of it.
  • Machine learning – Cognitive systems will form the “third era” of computing. We will see businesses using machines capable of complex reasoning and interaction to extend human cognition.  Examples are a “medical sieve” for medical imaging diagnosis, used by legal firms in suggesting defense / prosecution arguments and in next generation call centers.
  • IT shops need to be run as a business – Mike Walker spoke about how the business of IT is fundamentally changing and that end-consumers are driving corporate behaviors.  Expectations have changed and the bar has been raised.  The tolerance for failure is low and getting lower.  It is no longer acceptable to tell end-consumers that they will be receiving the latest product in a year.  Because customers want their products faster, EAs and businesses will have to react in creative ways.
  • Build a BRIC house: According to Forrester, $2.1 trillion will be spent on IT in 2013 with “apps and the US leading the charge.” Walker emphasized the importance of building information systems, products and services that support the BRIC areas of the world (Brazil, Russia, India and China) since they comprise nearly a third of the global GDP. Hewlett-Packard is banking big on “The New Style of IT”: Cloud, risk management and security and information management.  This is the future of business and IT, says Meg Whitman, CEO and president of HP. All of the company’s products and services presently pivot around these three concepts.
  • IT is the business: Gartner found that 67% of all EA organizations are either starting (39%), restarting (7%) or renewing (21%). There’s a shift from legacy EA, with 80% of organizations focused on how they can leverage EA to either align business and IT standards (25%), deliver strategic business and IT value (39%) or enable major business transformation (16%).

Good as these views are, they only represent two data points on a line that The Open Group wants to draw out toward the end of the decade. So we will be continuing these Future Technologies sessions to gather additional views, with the next session being held at The Open Group London Conference in October.  Please join us there! We’d also like to get your input on this blog.  Please post your thoughts on:

  • Perspectives on what business and technology trends will impact IT and EA in the next 5-10 years
  • Points of potential disruption – what will change the way we do business?
  • What actions should we be taking now to prepare for this future?

[1] McKinsey Global Institute, Disruptive technologies: Advances that will transform life, business, and the global economy. May 2013

Dave LounsburyDave Lounsbury is The Open Group‘s Chief Technology Officer, previously VP of Collaboration Services.  Dave holds three U.S. patents and is based in the U.S.

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Filed under Cloud, Enterprise Architecture, Future Technologies, Open Platform 3.0

As Platform 3.0 ripens, expect agile access and distribution of actionable intelligence across enterprises, says The Open Group panel

By Dana Gardner, Interarbor Solutions

Listen to the recorded podcast here

This latest BriefingsDirect discussion, leading into the The Open Group Conference on July 15 in Philadelphia, brings together a panel of experts to explore the business implications of the current shift to so-called Platform 3.0.

Known as the new model through which big data, cloud, and mobile and social — in combination — allow for advanced intelligence and automation in business, Platform 3.0 has so far lacked standards or even clear definitions.

The Open Group and its community are poised to change that, and we’re here now to learn more how to leverage Platform 3.0 as more than a IT shift — and as a business game-changer. It will be a big topic at next week’s conference.

The panel: Dave Lounsbury, Chief Technical Officer at The Open Group; Chris Harding, Director of Interoperability at The Open Group, and Mark Skilton, Global Director in the Strategy Office at Capgemini. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

This special BriefingsDirect thought leadership interview comes in conjunction with The Open Group Conference, which is focused on enterprise transformation in the finance, government, and healthcare sectors. Registration to the conference remains open. Follow the conference on Twitter at #ogPHL. [Disclosure: The Open Group is a sponsor of this and other BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: A lot of people are still wrapping their minds around this notion of Platform 3.0, something that is a whole greater than the sum of the parts. Why is this more than an IT conversation or a shift in how things are delivered? Why are the business implications momentous?

Lounsbury: Well, Dana, there are lot of IT changes or technical changes going on that are bringing together a lot of factors. They’re turning into this sort of super-saturated solution of ideas and possibilities and this emerging idea that this represents a new platform. I think it’s a pretty fundamental change.

Lounsbury

If you look at history, not just the history of IT, but all of human history, you see that step changes in societies and organizations are frequently driven by communication or connectedness. Think about the evolution of speech or the invention of the alphabet or movable-type printing. These technical innovations that we’re seeing are bringing together these vast sources of data about the world around us and doing it in real time.

Further, we’re starting to see a lot of rapid evolution in how you turn data into information and presenting the information in a way such that people can make decisions on it. Given all that we’re starting to realize, we’re on the cusp of another step of connectedness and awareness.

Fundamental changes

This really is going to drive some fundamental changes in the way we organize ourselves. Part of what The Open Group is doing, trying to bring Platform 3.0 together, is to try to get ahead of this and make sure that we understand not just what technical standards are needed, but how businesses will need to adapt and evolve what business processes they need to put in place in order to take maximum advantage of this to see change in the way that we look at the information.

Harding: Enterprises have to keep up with the way that things are moving in order to keep their positions in their industries. Enterprises can’t afford to be working with yesterday’s technology. It’s a case of being able to understand the information that they’re presented, and make the best decisions.

Harding

We’ve always talked about computers being about input, process, and output. Years ago, the input might have been through a teletype, the processing on a computer in the back office, and the output on print-out paper.

Now, we’re talking about the input being through a range of sensors and social media, the processing is done on the cloud, and the output goes to your mobile device, so you have it wherever you are when you need it. Enterprises that stick in the past are probably going to suffer.

Gardner: Mark Skilton, the ability to manage data at greater speed and scale, the whole three Vs — velocity, volume, and value — on its own could perhaps be a game changing shift in the market. The drive of mobile devices into lives of both consumers and workers is also a very big deal.

Of course, cloud has been an ongoing evolution of emphasis towards agility and efficiency in how workloads are supported. But is there something about the combination of how these are coming together at this particular time that, in your opinion, substantiates The Open Group’s emphasis on this as a literal platform shift?

Skilton: It is exactly that in terms of the workloads. The world we’re now into is the multi-workload environment, where you have mobile workloads, storage and compute workloads, and social networking workloads. There are many different types of data and traffic today in different cloud platforms and devices.

Skilton

It has to do with not just one solution, not one subscription model — because we’re now into this subscription-model era … the subscription economy, as one group tends to describe it. Now, we’re looking for not only just providing the security, the infrastructure, to deliver this kind of capability to a mobile device, as Chris was saying. The question is, how can you do this horizontally across other platforms? How can you integrate these things? This is something that is critical to the new order.

So Platform 3.0 addressing this point by bringing this together. Just look at the numbers. Look at the scale that we’re dealing with — 1.7 billion mobile devices sold in 2012, and 6.8 billion subscriptions estimated according to the International Telecommunications Union (ITU) equivalent to 96 percent of the world population.

Massive growth

We had massive growth in scale of mobile data traffic and internet data expansion. Mobile data is increasing 18 percent fold from 2011 to 2016 reaching 130 exabytes annually.  We passed 1 zettabyte of global online data storage back in 2010 and IP data traffic predicted to pass 1.3 zettabytes by 2016, with internet video accounting for 61 percent of total internet data according to Cisco studies.

These studies also predict data center traffic combining network and internet based storage will reach 6.6 zettabytes annually, and nearly two thirds of this will be cloud based by 2016.  This is only going to grow as social networking is reaching nearly one in four people around the world with 1.7 billion using at least one form of social networking in 2013, rising to one in three people with 2.55 billion global audience by 2017 as another extraordinary figure from an eMarketing.com study.

It is not surprising that many industry analysts are seeing growth in technologies of mobility, social computing, big data and cloud convergence at 30 to 40 percent and the shift to B2C commerce passing $1 trillion in 2012 is just the start of a wider digital transformation.

These numbers speak volumes in terms of the integration, interoperability, and connection of the new types of business and social realities that we have today.

Gardner: Why should IT be thinking about this as a fundamental shift, rather than a modest change?

Lounsbury: A lot depends on how you define your IT organization. It’s useful to separate the plumbing from the water. If we think of the water as the information that’s flowing, it’s how we make sure that the water is pure and getting to the places where you need to have the taps, where you need to have the water, etc.

But the plumbing also has to be up to the job. It needs to have the capacity. It needs to have new tools to filter out the impurities from the water. There’s no point giving someone data if it’s not been properly managed or if there’s incorrect information.

What’s going to happen in IT is not only do we have to focus on the mechanics of the plumbing, where we see things like the big database that we’ve seen in the open-source  role and things like that nature, but there’s the analytics and the data stewardship aspects of it.

We need to bring in mechanisms, so the data is valid and kept up to date. We need to indicate its freshness to the decision makers. Furthermore, IT is going to be called upon, whether as part of the enterprise IP or where end users will drive the selection of what they’re going to do with analytic tools and recommendation tools to take the data and turn it into information. One of the things you can’t do with business decision makers is overwhelm them with big rafts of data and expect them to figure it out.

You really need to present the information in a way that they can use to quickly make business decisions. That is an addition to the role of IT that may not have been there traditionally — how you think about the data and the role of what, in the beginning, was called data scientist and things of that nature.

Shift in constituency

Skilton: I’d just like to add to Dave’s excellent points about, the shape of data has changed, but also about why should IT get involved. We’re seeing that there’s a shift in the constituency of who is using this data.

We have the Chief Marketing Officer and the Chief Procurement Officer and other key line of business managers taking more direct control over the uses of information technology that enable their channels and interactions through mobile, social and data analytics. We’ve got processes that were previously managed just by IT and are now being consumed by significant stakeholders and investors in the organization.

We have to recognize in IT that we are the masters of our own destiny. The information needs to be sorted into new types of mobile devices, new types of data intelligence, and ways of delivering this kind of service.

I read recently in MIT Sloan Management Review an article that asked what is the role of the CIO. There is still the critical role of managing the security, compliance, and performance of these systems. But there’s also a socialization of IT, and this is where  the  positioning architectures which are cross platform is key to  delivering real value to the business users in the IT community.

Gardner: How do we prevent this from going off the rails?

Harding: This a very important point. And to add to the difficulties, it’s not only that a whole set of different people are getting involved with different kinds of information, but there’s also a step change in the speed with which all this is delivered. It’s no longer the case, that you can say, “Oh well, we need some kind of information system to manage this information. We’ll procure it and get a program written” that a year later that would be in place in delivering reports to it.

Now, people are looking to make sense of this information on the fly if possible. It’s really a case of having the platforms be the standard technology platform and also the systems for using it, the business processes, understood and in place.

Then, you can do all these things quickly and build on learning from what people have gone in the past, and not go out into all sorts of new experimental things that might not lead anywhere. It’s a case of building up the standard platform in the industry best practice. This is where The Open Group can really help things along by being a recipient and a reflector of best practice and standard.

Skilton: Capgemini has been doing work in this area. I break it down into four levels of scalability. It’s the platform scalability of understanding what you can do with your current legacy systems in introducing cloud computing or big data, and the infrastructure that gives you this, what we call multiplexing of resources. We’re very much seeing this idea of introducing scalable platform resource management, and you see that a lot with the heritage of virtualization.

Going into networking and the network scalability, a lot of the customers have who inherited their old telecommunications networks are looking to introduce new MPLS type scalable networks. The reason for this is that it’s all about connectivity in the field. I meet a number of clients who are saying, “We’ve got this cloud service,” or “This service is in a certain area of my country. If I move to another parts of the country or I’m traveling, I can’t get connectivity.” That’s the big issue of scaling.

Another one is application programming interfaces (APIs). What we’re seeing now is an explosion of integration and application services using API connectivity, and these are creating huge opportunities of what Chris Anderson of Wired used to call the “long tail effect.” It is now a reality in terms of building that kind of social connectivity and data exchange that Dave was talking about.

Finally, there are the marketplaces. Companies needs to think about what online marketplaces they need for digital branding, social branding, social networks, and awareness of your customers, suppliers, and employees. Customers can see that these four levels are where they need to start thinking about for IT strategy, and Platform 3.0 is right on this target of trying to work out what are the strategies of each of these new levels of scalability.

Gardner: We’re coming up on The Open Group Conference in Philadelphia very shortly. What should we expect from that? What is The Open Group doing vis-à-vis Platform 3.0, and how can organizations benefit from seeing a more methodological or standardized approach to some way of rationalizing all of this complexity? [Registration to the conference remains open. Follow the conference on Twitter at #ogPHL.]

Lounsbury: We’re still in the formational stages of  “third platform” or Platform 3.0 for The Open Group as an industry. To some extent, we’re starting pretty much at the ground floor with that in the Platform 3.0 forum. We’re leveraging a lot of the components that have been done previously by the work of the members of The Open Group in cloud, services-oriented architecture (SOA), and some of the work on the Internet of things.

First step

Our first step is to bring those things together to make sure that we’ve got a foundation to depart from. The next thing is that, through our Platform 3.0 Forum and the Steering Committee, we can ask people to talk about what their scenarios are for adoption of Platform 3.0?

That can range from things like the technological aspects of it and what standards are needed, but also to take a clue from our previous cloud working group. What are the best business practices in order to understand and then adopt some of these Platform 3.0 concepts to get your business using them?

What we’re really working toward in Philadelphia is to set up an exchange of ideas among the people who can, from the buy side, bring in their use cases from the supply side, bring in their ideas about what the technology possibilities are, and bring those together and start to shape a set of tracks where we can create business and technical artifacts that will help businesses adopt the Platform 3.0 concept.

Harding: We certainly also need to understand the business environment within which Platform 3.0 will be used. We’ve heard already about new players, new roles of various kinds that are appearing, and the fact that the technology is there and the business is adapting to this to use technology in new ways.

For example, we’ve heard about the data scientist. The data scientist is a new kind of role, a new kind of person, that is playing a particular part in all this within enterprises. We’re also hearing about marketplaces for services, new ways in which services are being made available and combined.

We really need to understand the actors in this new kind of business scenario. What are the pain points that people are having? What are the problems that need to be resolved in order to understand what kind of shape the new platform will have? That is one of the key things that the Platform 3.0 Forum members will be getting their teeth into.

Gardner: Looking to the future, when we think about the ability of the data to be so powerful when processed properly, when recommendations can be delivered to the right place at the right time, but we also recognize that there are limits to a manual or even human level approach to that, scientist by scientist, analysis by analysis.

When we think about the implications of automation, it seems like there were already some early examples of where bringing cloud, data, social, mobile, interactions, granularity of interactions together, that we’ve begun to see that how a recommendation engine could be brought to bear. I’m thinking about the Siri capability at Apple and even some of the examples of the Watson Technology at IBM.

So to our panel, are there unknown unknowns about where this will lead in terms of having extraordinary intelligence, a super computer or data center of super computers, brought to bear almost any problem instantly and then the result delivered directly to a center, a smart phone, any number of end points?

It seems that the potential here is mind boggling. Mark Skilton, any thoughts?

Skilton: What we’re talking about is the next generation of the Internet.  The advent of IPv6 and the explosion in multimedia services, will start to drive the next generation of the Internet.

I think that in the future, we’ll be talking about a multiplicity of information that is not just about services at your location or your personal lifestyle or your working preferences. We’ll see a convergence of information and services across multiple devices and new types of “co-presence services” that interact with your needs and social networks to provide predictive augmented information value.

When you start to get much more information about the context of where you are, the insight into what’s happening, and the predictive nature of these, it becomes something that becomes much more embedding into everyday life and in real time in context of what you are doing.

I expect to see much more intelligent applications coming forward on mobile devices in the next 5 to 10 years driven by this interconnected explosion of real time processing data, traffic, devices and social networking we describe in the scope of platform 3.0. This will add augmented intelligence and is something that’s really exciting and a complete game changer. I would call it the next killer app.

First-mover benefits

Gardner: There’s this notion of intelligence brought to bear rapidly in context, at a manageable cost. This seems to me a big change for businesses. We could, of course, go into the social implications as well, but just for businesses, that alone to me would be an incentive to get thinking and acting on this. So any thoughts about where businesses that do this well would be able to have significant advantage and first mover benefits?

Harding: Businesses always are taking stock. They understand their environments. They understand how the world that they live in is changing and they understand what part they play in it. It will be down to individual businesses to look at this new technical possibility and say, “So now this is where we could make a change to our business.” It’s the vision moment where you see a combination of technical possibility and business advantage that will work for your organization.

It’s going to be different for every business, and I’m very happy to say this, it’s something that computers aren’t going to be able to do for a very long time yet. It’s going to really be down to business people to do this as they have been doing for centuries and millennia, to understand how they can take advantage of these things.

So it’s a very exciting time, and we’ll see businesses understanding and developing their individual business visions as the starting point for a cycle of business transformation, which is what we’ll be very much talking about in Philadelphia. So yes, there will be businesses that gain advantage, but I wouldn’t point to any particular business, or any particular sector and say, “It’s going to be them” or “It’s going to be them.”

Gardner: Dave Lounsbury, a last word to you. In terms of some of the future implications and vision, where could this could lead in the not too distant future?

Lounsbury: I’d disagree a bit with my colleagues on this, and this could probably be a podcast on its own, Dana. You mentioned Siri, and I believe IBM just announced the commercial version of its Watson recommendation and analysis engine for use in some customer-facing applications.

I definitely see these as the thin end of the wedge on filling that gap between the growth of data and the analysis of data. I can imagine in not in the next couple of years, but in the next couple of technology cycles, that we’ll see the concept of recommendations and analysis as a service, to bring it full circle to cloud. And keep in mind that all of case law is data and all of the medical textbooks ever written are data. Pick your industry, and there is huge amount of knowledge base that humans must currently keep on top of.

This approach and these advances in the recommendation engines driven by the availability of big data are going to produce profound changes in the way knowledge workers produce their job. That’s something that businesses, including their IT functions, absolutely need to stay in front of to remain competitive in the next decade or so.

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Filed under ArchiMate®, Business Architecture, Cloud, Cloud/SOA, Conference, Data management, Enterprise Architecture, Platform 3.0, Professional Development, TOGAF®

Connect at The Open Group Conference in Sydney (#ogSYD) via Social Media

By The Open Group Conference Team

By attending The Open Group’s conferences, attendees are able to learn from industry experts, understand the latest technologies and standards and discuss and debate current industry trends. One way to maximize the benefits is to make technology work for you. If you are attending The Open Group Conference in Sydney next week, we’ve put together a few tips on how to leverage social media to make networking at the conference easier, quicker and more effective.

Using Twitter at #ogSYD

Twitter is a real-time news-sharing tool that anyone can use. The official hashtag for the conference is #ogSYD. This enables anybody, whether they are physically attending the event or not, to follow what’s happening at The Open Group Conference in Sydney in real-time and interact with each other.

Before the conference, be sure to update your Twitter account to monitor #ogSYD and, of course, to tweet about the conference.

Using Facebook at The Open Group Conference in Sydney

You can also track what is happening at the conference on The Open Group Facebook Page. We will be posting photos from conference events throughout the week. If you’re willing to share, your photos with us, we’re happy to post them to our page with a photo credit. Please email your photos, captions, full name and organization to photo (at) opengroup.org!

LinkedIn during The Open Group Conference in Sydney

Motivated by one of the sessions? Interested in what your peers have to say? Start a discussion on The Open Group LinkedIn Group page. We’ll also be sharing interesting topics and questions related to The Open Group Conference as it is happening. If you’re not a member already, requesting membership is easy. Simply go to the group page and click the “Join Group” button. We’ll accept your request as soon as we can!

Blogging during The Open Group Conference in Sydney

Stay tuned for conference recaps here on The Open Group blog. In case you missed a session or you weren’t able to make it to Sydney, we’ll be posting the highlights and recaps on the blog. If you are attending the conference and would like to submit a recap of your own, please contact ukopengroup (at) hotwirepr.com.

If you have any questions about social media usage at the conference, feel free to tweet the conference team @theopengroup.

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Filed under Conference

Thinking About Big Data

By Dave Lounsbury, The Open Group

“We can not solve our problems with the same level of thinking that created them.”

- Albert Einstein

The growing consumerization of technology and convergence of technologies such as the “Internet of Things”, social networks and mobile devices are causing big changes for enterprises and the marketplace. They are also generating massive amounts of data related to behavior, environment, location, buying patterns and more.

Having massive amounts of data readily available is invaluable. More data means greater insight, which leads to more informed decision-making. So far, we are keeping ahead of this data by smarter analytics and improving the way we handle this data. The question is, how long can we keep up? The rate of data production is increasing; as an example, an IDC report[1] predicts that the production of data will increase 50X in the coming decade. To magnify this problem, there’s an accompanying explosion of data about the data – cataloging information, metadata, and the results of analytics are all data in themselves. At the same time, data scientists and engineers who can deal with such data are already a scarce commodity, and the number of such people is expected to grow only by 1.5X in the same period.

It isn’t hard to draw the curve. Turning data into actionable insight is going to be a challenge – data flow is accelerating at a faster rate than the available humans can absorb, and our databases and data analytic systems can only help so much.

Markets never leave gaps like this unfilled, and because of this we should expect to see a fundamental shift in the IT tools we use to deal with the growing tide of data. In order to solve the challenges of managing data with the volume, variety and velocities we expect, we will need to teach machines to do more of the analysis for us and help to make the best use of scarce human talents.

The Study of Machine Learning

Machine Learning, sometimes called “cognitive computing”[2] or “intelligent computing”, looks at the study of building computers with the capability to learn and perform tasks based on experience. Experience in this context includes looking at vast data sets, using multiple “senses” or types of media, recognizing patterns from past history or precedent, and extrapolating this information to reason about the problem at hand. An example of machine learning that is currently underway in the healthcare sector is medical decision aids that learn to predict therapies or to help with patient management, based on correlating a vast body of medical and drug experience data with the information about the patients under treatment

A well-known example of this is Watson, a machine learning system IBM unveiled a few years ago. While Watson is best known for winning Jeopardy, that was just the beginning. IBM has since built six Watsons to assist with their primary objective: to help health care professionals find answers to complex medical questions and help with patient management[3]. The sophistication of Watson is the reaction of all this data action that is going on. Watson of course isn’t the only example in this field, with others ranging from Apple’s Siri intelligent voice-operated assistant to DARPA’s SyNAPSE program[4].

Evolution of the Technological Landscape

As the consumerization of technology continues to grow and converge, our way of constructing business models and systems need to evolve as well. We need to let data drive the business process, and incorporate intelligent machines like Watson into our infrastructure to help us turn data into actionable results.

There is an opportunity for information technology and companies to help drive this forward. However, in order for us to properly teach computers how to learn, we first need to understand the environments in which they will be asked to learn in – Cloud, Big Data, etc. Ultimately, though, any full consideration of these problems will require a look at how machine learning can help us make decisions – machine learning systems may be the real platform in these areas.

The Open Group is already laying the foundation to help organizations take advantage of these convergent technologies with its new forum, Platform 3.0. The forum brings together a community of industry thought leaders to analyze the use of Cloud, Social, Mobile computing and Big Data, and describe the business benefits that enterprises can gain from them. We’ll also be looking at trends like these at our Philadelphia conference this summer.  Please join us in the discussion.


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Filed under Cloud, Cloud/SOA, Data management, Enterprise Architecture

Business Architecture Tweet Jam – March 19

By Patty Donovan, The Open Group

On Tuesday, March 19 at 2:00 p.m. PT/9:00 p.m. BST/Wednesday, March 20 at 8:00 a.m. EDT (Sydney, Australia), The Open Group will host a tweet jam examining the topic of Business Architecture.

Today, Business Architecture is shaping and fostering enterprise transformation initiatives and continuous improvement throughout companies of all sizes. In The Open Group’s 2013 Predictions, Steve Philp, marketing Director for Open CA and Open CITS at The Open Group predicted that Business Architecture would continue to grow in prominence and visibility among executives. According to Steve’s prediction, “there are a number of key technology areas for 2013 where business architects will be called upon to engage with the business such as Cloud Computing, Big Data and social networking.” Steve also predicted that “the need to have competent Business Architects is a high priority in both the developed and emerging markets and the demand for Business Architects currently exceeds the supply.” Steve’s sentiments mirror an industry-wide perspective: It’s certain that Business Architecture will impact enterprises, but to what extent?

This tweet jam, sponsored by The Open Group, will take a step back and allow participants to discuss what the nascent topic of Business Architecture actually means. How is Business Architecture defined? What is the role of the business architect and how does Business Architecture relate to Enterprise Architecture?

Please join us for our upcoming Business Architecture tweet jam where leading experts will discuss this evolving topic.

And for those of you who are unfamiliar with tweet jams, here is some background information:

What Is a Tweet Jam?

A tweet jam is a one hour “discussion” hosted on Twitter. The purpose of the tweet jam is to share knowledge and answer questions on Business Architecture. Each tweet jam is led by a moderator and a dedicated group of experts to keep the discussion flowing. The public (or anyone using Twitter interested in the topic) is encouraged to join the discussion.

Participation Guidance

Whether you’re a newbie or veteran Twitter user, here are a few tips to keep in mind:

  • Have your first #ogChat tweet be a self-introduction: name, affiliation, occupation.
  • Start all other tweets with the question number you’re responding to and the #ogChat hashtag.
    • Sample: “Q1 Business Architecture has different meanings to different people within my organization #ogChat”
    • Please refrain from product or service promotions. The goal of a tweet jam is to encourage an exchange of knowledge and stimulate discussion.
    • While this is a professional get-together, we don’t have to be stiff! Informality will not be an issue!
    • A tweet jam is akin to a public forum, panel discussion or Town Hall meeting – let’s be focused and thoughtful.

If you have any questions prior to the event or would like to join as a participant, please direct them to Rod McLeod (rmcleod at bateman-group dot com). We anticipate a lively chat and hope you will be able to join!

patricia donovanPatricia Donovan is Vice President, Membership & Events, at The Open Group and a member of its executive management team. In this role she is involved in determining the company’s strategic direction and policy as well as the overall management of that business area. Patricia joined The Open Group in 1988 and has played a key role in the organization’s evolution, development and growth since then. She also oversees the company’s marketing, conferences and member meetings. She is based in the U.S.

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