Why we focus on spatial data science

Blog post
edited by
Matt Tricomi

The I in Information Technology is so broad – why is our first integrated data science problem focus on spatial data? It doesnt fit when looking on face of our Services Catalog . We get asked this a lot and this is our reason, and like Geospatial, its multi-dimensional spanning different ways of thinking, audiences, maturity, progressions, science, modeling, and time:

 

In green, x-axis, is the time progression of public web content. The summary point is data took the longest period – about 10-15 years. And data can only get better as it matures into being popular 25 years old on the web. We are in the information period now, but moving swiftly into the knowledge period. Just see how much more scientific data visualizations, and dependence we are on the internet. Just think how much you were on the web in 1998 compared to 15 years later – IT IS IN YOUR POCKET now. 

This isn’t just our theory.

RadarNetworks put together the visual of progressing through the web eras. Web 1.0 was websites or Content and early Commerce sites. Web 2.0 raised the web community with blogs and the web began to link collaboratively built information with wikis. Web 3.0 is ushering in the semantic direction and building integrated knowledge.

Even scarier, Public Web Content progression lags several business domains, but not necessarily in this leading order: Intelligence, Financial, Energy, Retail, and Large Corporate Analytics. Meaning, this curve reflects the Public maturity, and those other domains have different and faster curves. 

The recent discussions on intelligence analysis linking social/internet data with profile, Facebook/Google Privacy and use for personalized advertising, level of detail SalesForce knows about you and why companies pay so much for a license/seat, how energy exploration is optimizing where to drill in some harder to find areas, or the absolute complexity and risk of the financial derivatives as the world market goes – these technologies usually lag in how we integrate public content for googling someone, or using the internet to learn more and faster. Reason: Those do not make money. Same reason why the DoD invented the internet – it was driven by security of the U.S. which makes money which makes power. 

So, that digression aside (as we have been told “well, my industry is different”), the public progression does follow a parabolic curve that matches Moore’s Law driving factor in IT capability – every 2 years, computing power doubles in power, at same cost (paraphrasing). The fact that we can do more faster at quality levels means we can continue to increase our complexity of analysis in red. And there appears to be a stall not moving towards wisdom, but as we move toward knowledge. Its true our knowledge will continue to increase VERY fast, but what we do with that as a society is the “fear” as we move towards this singularity so fast. 

Fast is an understatement, very fast even for logarithmic progression as its hard to emote and digest the magnitude of just how fast it is moving. We moved from

  • The early 90s simply placing history up there and experimentation and having general content with loose hyperlinking and web logs
  • to the late 90s conducting eCommerce and doing math/financial interaction modeling and simulations and building product catalogs with metadata that allowed us to relate and say if a user found that quality or metdata in something, it might liek something else over here
  • to the early 2000s to engineering solutions including social and true community solutions that began to build on top of relational and the network effect and use semantics and continually share content on timelines and where a photo was taken as GPS devices began to appear in our pockets
  • To the 2010s or today where we are looking for new ways to collaborate, find new discoveries in cloud, and use the billions and billions on sensors and data streams to create more powerful more knowledgable applications

Another way to digest this progression is via the table below.

Web VersionTimeDIKWWeb MaturityKnowledge Domain Leading WebData Use Model on WebData Maturity on Web
.9early 90sDataContentHistoryExperimentalLogs
1.01995+Info HistoryExperimentalContent
1.11997  MathExperimentalRelational
1.21999 +CommerceMathHypotheticalMetadata
1.32002  EngineeringHypotheticalSpatial
2.02005+Knowledge+CommunityEngineeringComputationalTemporal
2.12010s  EngineeringComputationalSemantic
3.02015 and predictable webKnowledge+CollaborationScienceData as 4th paradigm notTempoSpatial (goes public)
4.02020 -2030Wisdom in sectorsAdvancing Collaboration with 3rd world coreAdvancing Science into Shared Services – Philsophical is out yearRobot/Ant data qualitySentiment and Predictive (goes public/useful) – Sensitive is out year

Now, think of the last teenager that could maintain eye contact in a conversation with an adult while holding phone in their hand and not be distracted by the pavlovian response of a text, tweet, instagram, etc. Now imagine, ten years from now, when its not tidbits of data, but as a call comes up, auto-searching on terms they arent aware of come up in augmented reality. Advice on how to react on the sentiment they just received – not just the information. The emotional knowledge quotient will be google now – “What do I do when?” versus critical thinking and live and learn.

So, taking it back to the “now”, though this blog is lacking the specific citations (blogs do allow us to cheat, but our research sources will make sure to detail and source our analysis), if you agree that spatial mapping for professional occurred in early 2000s and agree now that it has hit the public and understand that spatially tagging data has pass the tipping points with advent of smartphones, map apps, local scouts, augmented reality directions, and multi-dimensionl modeling integrating GIS and CAD with web, then you can see the data science maturity stage we are in that has the largest impact right now is – Geospatial.

Geospatial data is different. Prior to geospatial, data is non-dimension-based. It has many attributable and categorical facets, but prior to spatial data, that data does not have to be stored as a mathematical or picture form with specific relation to earth position. Spatial data – GIS, CAD, Lat/Longs, have to be stored in numerical fashion in order to calculate upon it. Further more, it hasnt be be related to a grounding point. Essentially, geospatial is storing vector maps or pixel maps. When you begin to put that together for 10s of millions of streams, you get a a very large complicated spatially referenced hydrography dataset. It gets even more complicated when you overlay 15-minute time-based data such as water attributes (flow, height, temperature, quality, changes, etc.) with that. Even more complicated when you combine that data with other dimensions such as earth elevations and need to relate across domains of science, speaking different languages to be able to calculate how fast water may flow a certain contaniment down a slope after a river bank or levy collapses.

Before we can get to those more complex scenarios, geospatial data is the next progression in data complexity .

That said, definitely check out our Geospatial Integrated Services and Capabilities

Our Change Services Concepts

Blog post
added by
Wiki Admin

Our Concepts and Approach starts with the executive sponsor. 

We want to connect the line of sight from drivers to goals through products and services, process, roles, systems of information and technology and down through the bottom line. We can start with a short rapid implementation planning workshop to validate, discover, level-set, educate, and start your transformation effort on the right foot. Or we can use ITIL continuous improvement approach as part of supporting your operations.

Our methodology and training focuses on transformation leadership that can help improve customer effectiveness and efficiency. We do this by proactively managing risk and delivering results through strong, facilitated execution or increase relevancy and economics of existing or new product lines and services.  In working with customers, Xentity provides integrated oversight of the parts that need to be connected, understood, and communicated prior to significant investment.  This approach enables Xentity to understand value opportunities and risk, determine mitigation strategies, and support customer awareness on how to realize recommendations.  Once decisions and investments have been made, Xentity utilizes strong communication and project management skills to facilitate change. The methodology work we developed has been recognized and adopted as Federal Government best practices by the U.S. OMB.

This approach helps design, execute, and showcase major change through proven methods. We approach information and technology change from within the mission out to the enterprise. This is different. And it has been an adopted concept and method by the Federal Government and has become popular in the commercial space. Take on the right amount of change, a focus area at a time. This is what we know. It is what we do and have been doing since 2001. 

Either as a team creating deliverables, embedded consultants, or staff augmentation, our transformation designers, architects, analysts managers, management consultants, and creatives specialize in change.

 Our transformation approach and experts will help you buy-back the risk.

  •  Upfront, we can help you design and architect your transformation concept of operations, develop the full architecture and requirements before you go to the street using our collaborative business transformation approach.
  • We can tactically engage to support and manage your project – either existing project and team back on track or new project and team going on right foot.
  • We then can design and execute your outreach efforts and even produce short movies to help you brag about your change.
  • And for program support, and continuous improvement, we can provide your high-tech, geospatial, and science operations, analysis, and management with true subject-matter familiarity and staffing solutions. 

 We want to connect the line of sight from drivers to goals through products and services, process, roles, systems of information and technology and down through the bottom line. We can start with a short rapid implementation planning workshop to validate, discover, level-set, educate, and start your transformation effort on the right foot. Or we can use ITIL continuous improvement approach as part of supporting your operations. Read more about our Services on how we can design change with you or augment your current architecture, management, and communication staffing needs.

Address gaps early on. Buy back the risk.  

  • Get the right definition and design for embracing the right innovation and disruption concepts.
  • Coordinate and integrate your change to mediate and anticipate risks and challenges. 
  • Recover from current project design and management issues. 
  • Showcase and engage your community with your new or changed solution the way it deserves. 
  • Bring on someone that can help you with this transformation lifecycle

Our Services:

  • Buy-Back Risk of your transformation failing
  • Improve transformation requirements and concepts
  • Set path for most successful project implementation
  • Focus on Information Lifecycle challenges
  • Address Solutions for Disruptions in tech, business, and cultural shifts
  • Increase the likelihood of achieving your metrics and goals
  • Help accelerate time-to-market, 
  • Increase quality and relevance of your change effort.
  • Can include training and workshop to transition approaches to keep focus on continuous improvement
  • Tell the world your transformation story!

If this story below is you, these are services you need

Information Technology used to be hidden in your organization. Likely for Financials and other enterprise resource management or MIS. Ran as a cost-center under the CFO or COO.  Now its core to your business. Workforce costs are being replaced on the delivery or customer service ends by internet provided capabilities. Sales force automation, marketing campaigning, devices, storefronts, support desks, mission critical services – you name it.

Moreso, Now, data is an asset and your business is done online or through B2B information exchange. Its in the boardroom to the factory floor to the customer interface. You need to manage the information supply chain, use for management decisions, analytics, and in many cases your business is completely reliant on information and technology as your service. 

So you invest capital funds or operation funds deferrals in projects, development, infrastructure, contracts, etc.. in hopes of gaining that competitive edge or cost savings. This introduces new ways of doing business. And Change. Which of course, no one likes change except the change visionary.

The canary in the cave signals start to come in. The project the costs keep creeping up. Requirements weren`t there. Traditional cost-center procurement and development models were used to bid or build. You created a business case, but most of the time its ignored. A plan is used as the law, instead of the guide, and was wrong as business agility and the technology offerings changed before you even started. And an architecture or operating concept is either non-existent, incomplete, or build on old patterns.

As a result, the outcomes are not there, and delays, over-runs, re-designs are bringing forward nightmare scenarios. It gets risky. Before you know it, project costs are beyond up, a new technology is out, outcomes are missed and you and your stakeholders and stockholders are very skeptical. Worse yet, public relations and internal chatter is causing a culture of loss confidence which may leak public forcing an premature launch.

Something has to give.

You are at risk of joining the statistic that only 25% of IT projects succeed, 25% fail, and rest are partial wins/losses (Source: KPMG). 

This is where we come in – either before the nightmare occurs, or in the midst. We can operate as a project team, embedded consultants, or SWAT team.