•  May 9, 2022

    Vintage Sewing Machines and Enterprise Geospatial Data

    This article was originally published by Applied Geographics Inc. (AppGeo), a company acquired by The Sanborn Map Company Inc in September 2022.

    Bill Johnson, Carpe Geo Evangelist, AppGeo

    My wife loves to sew. I love to repair and restore mechanical things. We both love antiques. That combination of factors has resulted in a new hobby we are enjoying together, collecting and restoring vintage sewing machines. These things are amazing – the ingenious engineering, the high manufacturing quality, the transformation they ushered into society that ended the drudgery of hand sewing of all garments, their contemporary utility, and their beauty, all combine to make them really special.

    Sewing machines do not replicate hand sewing. Rather, they create a superior method of joining fabric; the lockstitch. When you hand sew, you use a needle to carry a single thread back and forth through the fabric, creating a stitch that in cross-section resembles a sine wave. A sewing machine uses two threads, one above the fabric and a second below. The upper thread is carried through the fabric by a needle and is then brought around the lower thread (by forming a loop that is passed completely around the bobbin where the lower thread is held) to create an interlocking stitch that looks the same on both sides of the fabric and is very strong. In cross-section, the locking portion of the stitch, where the two threads cross over each other, occurs in the center of the fabric.

    For this all to work and form the proper lockstitch, both the upper and lower threads have to be held in balanced tension. People that sew already know that the most important adjustment on their sewing machine is thread tension. I’ve learned all of this over the past several months and have marveled at how the early engineers solved and perfected the lockstitch process, especially the clever ways they regulated thread tension through the stitch formation cycle.

    You may be wondering where I am going with this discussion of sewing machines…

    It occurs to me that the miracle of the machine lockstitch, which balances the tensions of two separate threads on opposing sides of the fabric, is a wonderful metaphor for what I see happening more and more with enterprise data. My definition of state-level enterprise data is geospatial data produced by a coalition of partners and managed through a state-led governance process to satisfy a wide range of use cases. This has traditionally been the central focus of state GIS offices: assembling government-owned data as a public good and made freely available in the public domain. But today, we are seeing a growing volume of new data created in the private sector and made available for use by government agencies under licensing agreements.

    A current example is the Federal Communications Commission (FCC) licensing a nationwide geospatial address point dataset to meet their needs for a new, more granular national broadband map. I’ve written previously about the importance of this new map and how it will be used to allocate $42.45 billion in broadband funds. Statewide imagery programs are another area where licensed data is gaining prominence as a cost-effective alternative to custom contracting for government-owned data. The trend in the public sector is to balance the opposing realities of cost (licensed data can be significantly less expensive) with the need for transparency and open data (licensed data comes with usage and distribution restrictions) which generates other benefits by making data available without restrictions. Therein lies the tension.

    Just as hand sewing with a single thread has no tension balancing issues, a “single thread” data strategy based entirely on government data lacks tensions, as well, but start blending licensed data into the traditional realm of public geospatial data, or stitching with 2 threads, to follow the lockstitch metaphor, and suddenly the tension balance becomes very important. The sewing machine pioneers figured it out through trial and error as the sewing machine evolved from the mid-1800’s through the 1930’s. Similarly, we need to learn how to balance the tension on both sides to deal with the growing reality that public and private data are now blended in many of our geospatial applications. Balancing the tensions is fundamental to success. To do that, we need to understand the tensions. This is a key challenge today. Think of it as lockstitch engineering for the digital age.

    How do we balance the tensions? The example of broadband mapping

    As an example, let’s look at what is happening right now with broadband mapping. The COVID-19 pandemic has awakened us all to the need to finally provide broadband service to all Americans. Congress has approved unprecedented levels of new funding to achieve this goal. An immediate need is accurate and detailed mapping to show exactly where to direct these new funds. As I mentioned above, the FCC is licensing a nationwide dataset showing every location (address point) where broadband service should be available. The new FCC map will be created by combining those broadband location points (what the FCC calls the Broadband Serviceable Location Fabric, or simply the Fabric) with service area polygons that the broadband provider companies will be submitting to the FCC this summer. This will be a blend of government-collected open data and licensed commercial data. The new FCC map is not expected until the end of 2022 or early in 2023 (the timing is my speculation, as no announcement has yet been made).

    States need detailed broadband mapping now to begin their planning for the new federal funds, and also to be ready to challenge the accuracy of the new FCC map (there will be a formal challenge process). Some states have geospatial address point data ready to use for broadband mapping and are doing so, like Tennessee. Some states have address data that needs some improvement and are making that investment on an expedited basis, like Massachusetts. And some states are using commercial (licensed) data that is immediately available to meet their broadband mapping needs, like Montana. Many more are still considering their path forward.

    What is the right choice? There is no easy answer. Using licensed data may be the most practical option for some states. Doing so can mean that broadband mapping to the individual address level can begin immediately, though they must weigh the tradeoffs in licensing terms that limit how widely the data may be used and shared. States may also have concerns about data accuracy and quality coming from a non-authoritative source. These factors represent tension. Alternatively, states may choose to invest in improving their state address data, which can support a wide range of uses beyond broadband mapping and can be freely shared, but the urgency to commence broadband mapping right away is at odds with that choice. More tension. Perhaps states see that an ongoing investment in address data that may already be well underway for Next-Generation 911 can be leveraged to support broadband, but the coordination mechanisms necessary to resolve a host of governance, technical, funding, and policy issues are not in place to make this happen. Still more tension.

    Blending commercial and public data requires a thoughtful GIS strategy

    These are very interesting times and we are seeing that the complexity of situations like this can lead to short-term thinking and decision-making that may not yield the best long-term solution or the most favorable return on investment. What is needed to balance the tensions and make wise decisions is a strategic vision that provides the “North star” for the decision-making process, detailed knowledge of the trade-offs including an understanding of licensing terms, clear requirements against which to evaluate the technical offerings, and the infrastructure of coordination (such as a state Geospatial Advisory Council) to ensure that stakeholders can weigh in and inform the decision.

    This is just one of many examples I could cite where the tensions between public and private data must be carefully considered and balanced. If you are not already thinking about how to achieve this balance, you surely will be, and probably sooner than you expect. Blending and balancing these tensions will be a significant part of our geospatial future. Just as vintage sewing machines were solidly built, as an investment intended to last, blended enterprise data solutions that properly balance the tensions between public and private data can also endure and deliver real value over the long term. With the opposing tensions in balance, it’s as though a strong and durable lockstitch has sewn it all together.

    My wife would be pleased. Me, too.

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