National Vector Database

  Resources Know No Boundaries

and even humans can’t

see borders drawn in the sand

…well, except maybe at crossing state lines on a highway or bridge

The History of the Map Industry begins with

Colonization and Exploration

In the realm of an exploratory society, Geographers and Cartographers were known far and wide for their efforts in land surveying and exploring the globe. Mapped Areas in the 1500s were not inaccurate, and not until the adoption of triangulated surveys did warring regions and borders begin to settle and take shape. Largely funded by military and resource exploration efforts, some of the earliest places with triangulated surveys worthy of their coordinate printings are in Europe (of course, but also in India, and mineral rich areas of the Americas (Northern Michigan, Pennsylvania and General Wheeler’s West of the 100th Meridian).

Triangulated Surveys

(Years of Survey, Lead Surveyor, Lead Cartographer, Map Scale)

  • Carte de France was surveyed
    • 1714-1784
    • Cassini family
    • 1: 86,400
  • British Ordinance Survey
    • 1783–1853
    • Lieutenant-Colonel David Watson,
    • 1:1250, 1:2500
  • Survey of India
    • 1767 – 1843
    • George Everest, Aaron Arrowsmith
    • 1:63,360
  • US Geological Survey – Historical
    • 1879-1920
    • John Wesley Powell
    • 1:63,360
  • Wheeler Survey
    • 1869-1871
    • General George Montague Wheeler
    • 1: 42,240 (8 miles to the inch)

Triangulated Cartography was the necessary counterpart to this endeavor. Artistic rendering was secondary to the scientific lead of triangulation, not because the Cartography was inferior but because the task of Surveying was so great. In these centuries of exploration and colonization, mapping was the hand of the King. Perhaps the most famous quote delineating this relationship was from King Louis XIV’s reaction to learning that the triangulated measurement of France was smaller than the pre-mapping era estimate. David Turnbull articulated in his publication Cartography and Science in Early Modern Europe: Mapping the Construction of Knowledge Spaces

Faced with political and technical problems of assemblage, Cartographer/Surveyors Cassini, Jean Picard and the Academie proposed the creation of a network of surveyed triangles that would encompass the country and thereby would enable the drawing of a unified map of France on one grid. The proposed network of triangles would also link Paris to every part of the kingdom by invisible but powerful, ‘terraforming’, bonds. France would never be the same again; when the new map, later to be known as the Carte de France, showed France to be smaller than previously believed, Louis XIV complained, “I paid my academicians well and they have diminished my kingdom.” Nor was ‘knowing’ France ever the same again.

As the definitive measurements and boundaries grew in the documentation that contributed greatly to their stability, very quickly followed the swing in occupations related to exploring. Collection of data to processing of data to map making and producing. Following the pattern of occupations – the positions and projects that people do to generate and earn money – charts the evolution of the industry.

This is the first step toward creating an Essential Base Layer of data about the Earth. Exploration and waypoint mapping so as to create an accurate cartographic representation.

Industrialization

The turn of the 19th Century found most Geographers and Cartographers in the first era of shifting from science as lead to art as the skillset in demand. Maps are commonplace, and the market is saturated with them as themes and regions of interest. Many many beautiful maps are made throughout three centuries, and many intrepid stories are told of surveyors and others in the field collecting measurements and observations. Maps are useful, and they fetch a fair price to make it would be interesting to see the ratio of persons in a given category of occupation throughout time. Through the mid-to-late 1900s Cartography remained as a known profession, and Geography was strong in many Secondary Education Institutions. For a time it is the artistic skill for cartographic rendering that keeps Geograpers employed.

As the century turned, so too did the count of available positions in the map making industry. The benefits of spatially integrated systems and the abundance of applications hit the scene in the 1960s, the science of earth measurement once again emerges as the leading skillset of the field. The modern applications of cartography, mapping and surveying are best represented through the medium of GIS. Geospatial Survey Engineers, Geospatial Engineers, GIS Technicians (vector database maintenance), Data Analysts, Data Visualization Experts, Interactive Map Makers, GIS technicians and static map producers for print and publication. The bounty of these occupation types, and the increasing demand for development of skills and techniques to make useful all of the data that continually builds up in various ways. Cartography is rapidly going the way of the artist accompanying the scientist.

Continuing the perspective of quantifying the industry by the number and type of occupations people find salaries in a given era, it is clear that navigation fueled the digitization of map data. The legacy of importance in ground truthing and accuracy of measurement is maintained through the science of GIS. This connection is the base building block of all data representations and visualizations that use them as a foundation. This is the need for symbiosis of art and science – the data is only as useful as the visualization (cartographic representation) that renders it as “knowledge” from a previous state of “information.”

There are areas of the globe still lacking in adequate cartographic representation. Logs of satellite imagery, aerial photography, LiDAR representation, and even survey grade GPS locations – are all simply raw input data until they are transformed into value added attribute rich map infrastructure of places. Data. This mass collection and rapid regeneration of the earth in Google Maps, Bing Pictometry, Gogle Earth 3D, and the growing collection of interactive maps made using tools like Leaflet, Mapbox and CartoDB – all contribute to the common conception that any map is current, accurate, and giving honest representation.

This same common conception also considers the ‘status’ of mapping and surveying of the earth to be “pretty much all covered.” People have seen world maps since childhood, and then Google Earth appears to have every inch in 3D. The idea that all things have been mapped in great detail seems to be a cultural understanding in the modern era. It is true that military driven earth models for navigation are available and updated regularly with satellites and aerial imagery. There is a big distance between the data that the military has and the data that gets into the hands of citizens.

The concepts of currency (time) and scale (area) are the two fundamental reasons why there is not actually equally detailed data about every corner of the planet.

Regardless, it is the common perception that navigation and exploration have met their maximum use and potential for ingenuity in their given form. Many in the Cartographic tradition feel that the new era of citizen mapping has bastardized the industry and artisanship of this legacy trade. None the less, the return of the relationship of the individual with the map in daily life is what dictates the need for combining the skills of the artisan Cartographer and the tools of the Data Scientist.

Mapping in the Tertiary and Quaternary sectors of the Tertiary Society

For the first time since the exploration of new continents are people relying on maps as an extension of daily life. This is true for both navigation and global conceptualization. Since 2000 here has been a commanding uprising in the presentation of digital maps to portray and conceptualize data. This is of course the era of Big Data, and the amount of data that has a geolocational component is often selected because it is inherent to visualization. People see maps in daily news, in their GPS, on retail location sites, when planning trips, and many other applications. Amazingly, the final way that maps are being expected in daily life is through the science that they represent. This is amazing because there are very few “leekages” of academic research and ideas in to every day culture and society. Certainly this challenge is an entirely other article, because this disconnect is a result of many factors, but the point is that many exciting things are being discovered by scientists every minute, but only a few of them are successfully translated into a medium that is received by mainstream culture.

The expectation of maps to provide support services like scientific understanding, navigation and retail support has provided a new era and opportunity for the cartographers thought to be losing clout from lack of direct application. Economy will always simultaneously dictate and indicate the subtleties and details of daily life. Unfortunately, it is also the expectation of map availability that has encumbered the capacity for it to gain funding.

Which iterates the main challenge of the need for openly and freely available data, and what is not as readily understood, is that data is a continually evolving entity. It must be continually maintained or it will go stale, and for it to truly meet the needs of those answering the tough questions of the day about how to use resources and dictate policy that will ensure sustainable societal growth and a measurable quality of life for all individuals is embedded in the iterative process of growing and creating new data. The dimensions through which spatial analysis has improved the functioning of certain essential processes of collecting and continually refining. Until it is learned that there are a certain basic level of statistics that need to be collected in relation to a specific set of indicators: The Essential Base Layers.

Measuring Sustainability and Societal Success

At its most basic, the populations of the world employing and advancing technologies beyond what can best be characterized as manufacturing of tangible goods in the physical realm, give rise to supporting the model of  a linear representation of economic and technical progression of a specific demographic sector of society – colloquially known as the Western World. The truth of the world progression toward “development” and “modernization” is shown through Hans Rosling’s famous talk Let My Dataset Change Your Mindset, is that a linear progression model such as Primary through Quaternary is not applicable to all nations.

“Isn’t it strange to see that the United States first grew the economy, and then gradually got rich? Whereas China could get healthy much earlier, because they applied the knowledge of education, nutrition, and then also benefits of penicillin and vaccines and family planning.And Asia could have social development before they got the economic development. So to me, as a public health professor, it’s not strange that all these countries grow so fast now.”

The point of illustrating this difference in paradigms is two fold. Not only does it iterate that having reliable data is the only mechanism for truly measuring societal success. It also showcases that economic and industrial progression are not entirely the metrics of sustainable and successful societies. It is just as imperative to have data about health, food production, water treatment, land resource acquisition and distribution, etc., etc. Quality of Life is the indicator for societal success, not GDP, and only through continual reliable and standardized data over time will any Quality of Life indicators retain their value. As Hans articulates about his primary source for data, the Demographic Health Survey.

“And it is my task, on behalf of the rest of the world, to convey a thanks to the U.S. taxpayers, for Demographic Health Survey. It is due to USA’s continuous sponsoring during 25 years of the very good methodology for measuring child mortality that we have a grasp of what’s happening in the world. (Applause) And it is U.S. government at its best, without advocacy, providing facts, that it’s useful for the society. And providing data free of charge on the internet, for the world to use. Thank you very much. Quite the opposite of the World Bank, who compiled data with government money, tax money, and then they sell it to add a little profit, in a very inefficient, Gutenberg way.”

The science of gathering and using data has a place in the modern world of providing services and sustaining quality of life. Thus the return to the case for funding. The degree to which a finite extent of data is essential to maintain about the globe, so too is the degree to which that data can be budgeted for maintenance and curation.

 

National Vector Database – The Essential Base Layers

This is a concept of both spatial and descriptive data types. These essential layers are determined by their capacity as an independent indicator as well as their level of capacity for integration with other datasets.

How many times have an exciting discussion about research culminated at the point in the conversation where you say “that would be cool, if only we had that data.”

For most researchers, this occurs more times than they can count. On the flip side, it seems government agencies, corporations and retail businesses have data pouring over their ears. So much data being collected to track the daily transactions of people’s lives and activities. Surely there is an equilibrium between these two.

The first way to begin sorting what data is essential, and what data therefore becomes secondary – in terms of effort and dollars to maintain and curate – is what data is available and what data should be available. The full process includes considerations of authoritative sources on data.

 

Data That Should Be Available

Data that promotes the sustainability of its people to an established minimum standard for quality of life and well being. A place that attends to the details of life experience for its residents maintains its population and is a draw for economic investment.

Quality of Life Indicators

  • Health (mental and physical)
  • Natural Resources
  • Goods and Services
  • Community Development and Community Structure
  • Group Relations and Political Participation
  • Personal Development
  • Recreation and Leisure
  • Learning
  • Clean Physical Environment (nuisance, visual perception and scenic quality, climate, pollution)
  • Economic Stability and Diversification
  • Personal Economic Security and Standard of Living
  • Housing
  • Administration of Justice, Crime, Safety

Economic Development Indicators

  • Policy
  • Tourism
  • Labor force and job markets
  • Industry
  • Agriculture
  • Transportation
  • Trade and commodities
  • Quality of Life and Well-Being

3 Steps to Creating Data Required to Support Accurate Indicators

  1. Read reports and mission statements related to economic development and quality of life
  • Individual metrics for measuring progress indicates the data required for accurate measurement
  1. Look at other states that run app competitions to get a feel for what apps have been created and what data was used
  2. Look at popular apps that make use of government data

Factors for Data Quality

  1. Data Availability (how accessible is the data, is it already in tabular format and in what format)
  2. Data Relevance to Economic Development (how clear is the link to OEDIT goals)
  3. Data Relevance to Societal Trends
  • The data, when combined with economic data, creates an exponential increase in value of both
  1. Primary, Secondary, Tertiary and Quaternary Economic Patterns
  • Primary and Secondary: overall economic impact is not visible or easily understood by the lay person, but often has great depth or breadth (sales and distribution of hay and seed)
  • Tertiary: overall economic impact is of high public profile, is often quantified by disposable income, and are more noteworthy based on their subject matter (vineyard tasting rooms)
  • Quaternary: overall economic impact is visible but usually only in narrow applications (information technology, consultation, education, research and development, finance)
Data That Is Available

How quickly this returns to the age-old Jefferson vs. Hamilton debate of big vs small government.

What should a state government open source platform be populated with? What data is best managed at the federal level, at the state level and at the local level. Determine what federal data should be subset and housed, and if there are Federal Stewards that will make State subsets readily available so data remains fresh.

Data by Department – Data Stewards as separate from Data Consumers

  • Economy and Community
  • City Management and Ethics
  • Transportation
  • Public Safety
  • Health and Social Services
  • Geographic Locations and Boundaries
  • Energy and Environment
  • Housing and Buildings
  • City Infrastructure
  • Culture and Recreation

 Three Steps to Finding Available Data

  1. Scour the websites of government agencies to derive a list of data leads
  • Data indicators include permits, licenses other filings, inventories, address lists
  • Look for studies done at state level and avoid case studies
  • Look for tables and charts in reports on studies, collated data that is indicative of collected data
  • Look for hyper-links, appendixes and measurable outcomes in reports
  • Grants often generate data and reports on how money is spent
  • Read meeting notes and newsletters to see how organizations value their data
  • Read FAQs to see if dataset locations are in responses
  1. Look at the work other states are doing
  • What data is standard to collect?
  • What is innovative data that others are collecting?
  • What are the most popularly used datasets in different places?
  1. Look at what major cities are doing
  • What data is better stored at the municipal level?
  • What data should be aggregated at the state level?
The Essential Base Layers ARE SEAMLESS

The argument is the same for the seamless basemap. Continuous multi-dimensional representation of earth surface and cover. What is essential to the classification that accurately depicts what is most essential to the human understanding of the earth. For the ultimate seamless 3D model, as is being purported and actualized for New Zeeland by Roger Smith and his company Geographix. Similar to Google Earth, but in greater detail and resloution.

“The development of Skyline technology has been largely geared to meet the needs of the defence and intelligence communities. It also has application across a range of civil industry sectors, including engineering and infrastructural development and design, urban and regional planning, environmental management, emergency services, mining, education, and tourism.”

The goal for standardization and  vectorization is bodacious but not unthinkable. Especially when considering that Geospatial data can best be perceived as the data clothesline for the nation. ESRI has developed The Living Atlas – as a place for data to be collected and aggregated.

It is the seamless perception of the world that will offer the most efficient and effective method for understanding it and optimizing society within it. Watersheds are the flagship example of boundaries that are far from congruent, and the multitude of political jurisdictions that watershed boundaries cross creates havoc for good management and stewardship – much less effective use of resources.

Seamless Layers Sponsored by Authoritative Sources

The Essential Base Layer categorization is a schema very similar to Land Cover and Land Use Classification. Land Cover includes data about Land Ownership and Management, Water Resources, Forest Management and Conservation, Agriculture, Rangeland, Rugged Terrain, Shoreline, Riparian, Wetland. Land Use includes Transportation, Building Permits, Utilities, Parks, Greenways, and Openspace. Economics, Demographics and Health Data are the signatures of the remaining essential base layers.

One of the cardinal rules of data management, cleaning and processing is that interpolation must always be done in aggregating and never in dis-integrating. The first challenge is that data for all of thee layers is managed at differnt levels of governance – from municipality, to state and then federal. Some of the data is gathered by non-profit organizations.

In order to build a dataset that will crosswalk Nations, new fields will have to be established to identify the essential attribute information related to each data type. There are commonalities between regions, and it is the simple task to identify what fields can be conflated and what fields must be in greater detail at a local level. It is essentially the most basic but unwittingly complex task of sorting through all differences between attribute fields, all of which hang on the geometry data that draws the invisible lines that dictate human activity and policy.

Full Data Curation Comes through Use

There are two major ways that national databases retain their accuracy and value. The first is by having local stewards of the data “check in” and “version” updates while retaining date stamps of updated layers and segments. The second is by having as many users as possible work with the data in as many ways as possible to find all the opportunities to improve and refine the data integrity and quality.

This is the logic behind Open Street Maps, and the intelligence behind The British Ordinance Survey’s new OS Open Data.

“When countries across the globe will show their support for open data policies, Ordnance Survey (OS) announce plans to launch a world-leading digital map as open data and the creation of an engagement hub in London…. Making this data more accessible means more small and medium companies will be able to use Ordnance Survey’s world-leading maps, combining geographical data from multiple sources and visualising them at a high level of detail.”

Here again, the biggest challenge of having a national standard is convening all of the attribute data. This is of course also the most engaging part of creating a unified standard for data for essential layers.

Proper data curation is the future of the industry because technology is advancing to support this medium. Storage is inexpensive, and file transmission and size are on the decline every day.  This means the quality input to GIS databases enables cartographers the confidence their data is reliable, and focus on the art of properly transmitting the true concepts in the data through good visualization.

To bring full circle the evolution of maps and perception. The biggest intersection of the maps and perception venn diagram is in the realm of mapping national trends.

ny times map joke

So to understand this level of frustration, use a few basic principles to assess the quality and validity of the message being presented. First is to look at the data source, and then is to look at the data scale. This exercise works for any example, but consider a map like this one in the NY Times article claiming that it can show The Places in America Where College Football Means the Most.

ny times map joke2

First ask what type of data might be able to reflect the opinion or excitement level of humans in relation to College Football. Note the pop-up, ok Facebook posts/per county. Interesting data to represent, so there is a point for that. However, does Facebook activity really accurately represent an entire population? Is this data source accurate to represent or test the hypothesis? Is it adequate considering the availability of other data sources for returning a valuable interpretation of the hypothesis?

Next consider the scale. This map is taking data and aggregating it to the county level for the nation. Consider the sampling size in relation to the population. The assumption of this hypothesis is that every person who likes College Football is -1- active on Facebook -2- expresses their true interest in sports through Facebook. What about citizens that love College Football, but have a particular disdain for talking about Football on Facebook. Are these percentages based on people mentioning College Football – regardless of what they are saying about it? What about people posing on Facebook that they hate College Football?

New York Times is not alone in using this exploitation of maps and data through improper representation and analysis – they are just the flagship.

This phenomena is pointed to so frequently because it iterates a literal and metaphoric point about what data is needed and how it should be represented. Ultimately making the case for the National Vector Database and the Essential Base Layers.

It is true that few works of note ever find their way to completion in just one generation. The most influential and pivotal research and philanthropic contributions to society have largely been the work of projects and conceptions that improve over time to become more efficient and lean. It is not the grossing accumulation of growth that indicates successes, but instead the advancement toward a system that functions to refine itself.

Thus, having Essential Base Layers maintained to a standard of quality provide the foundation for both artistic and scientific arms of using data to understand and communicate about the world.

 

Margaret Spyker

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