Debunking the Notion that GIS is dead

Recently, Matt Forrest shared a video positing the death of Geographic Information Systems (GIS). This sparked a range of opinions within the community. My thoughts on the matter were too extensive to simply convey in a comment. With Matt's permission, I've opted to craft a response in the form of a counter blog. For those who haven't yet engaged with Matt's argument, I strongly encourage you to do so. Understanding his perspective is crucial for framing the ongoing discourse. While I won't fully reiterate his points here, I'll provide a brief summary of the reasons Matt believes GIS is dead:

First, the proliferation of big data necessitates a stronger online presence, shifting the landscape for GIS. Secondly, advancements in tools are facilitating the automation of common GIS tasks, altering traditional workflows. Thirdly, the field of GIS continues to evolve, creating space for new roles and skill sets. Fourthly,GIS is undergoing a migration towards cloud-based platforms, reshaping how it operates and interacts with data. And lastly, he views GIS solely as a technology and? its vulnerability to shifts in technological paradigms.

These points encapsulate Matt's perspective on the current state and trajectory of GIS. In my forthcoming response, I aim to engage with these arguments constructively, offering insights and reflections that contribute to the ongoing dialogue surrounding the future of GIS.

I'd like to begin by expressing my concurrence with Matt regarding the factual content presented in his video. However, I find his interpretation open to debate, and this will be the focus of my discussion.

Let's begin with the basics. GIS is commonly understood as a suite of tools for storing, visualizing, analyzing, and interpreting geographic data. While this definition may seem straightforward, it overlooks the scientific underpinnings inherent in the process. Advancements in GIS tools inherently imply progress in the science behind GIS, often referred to as GI-Science.

Within the realm of GIS, we recognize the existence of subsystems nested within the overarching system. These subsystems encompass data storage and retrieval, data manipulation and analysis, and data output and display. These subsystems rely on various components, including hardware, software, data, skilled personnel, and methodologies.

Matt's assertion seems to suggest that GIS is primarily a technology, possibly referring to hardware and software, while relegating the other components to a category he terms as "geography." However, this perspective raises questions about the functioning of GIS as a system. Without the inclusion of all components, the system would cease to operate effectively. Each component plays a critical role in supporting the various subsystems, and the removal of any component would disrupt the chain, leading to system failure.

Despite considering Matt's characterization of GIS as? just a technology, it's important to delve into the essence of what technology truly represents. To illustrate this, allow me to recount an experience from my interactions with individuals in Uganda. During our visit to communities in Uganda, we encountered a new technological innovation implemented within the public water system. This innovation involved the utilization of an ATM-like keycard system, enabling individuals to load money onto the card and utilize it to activate water pumps, with credits deducted based on the volume of water dispensed. Initially, there was considerable enthusiasm among the community members, who appreciated the transparency afforded by this new system.

However, when we visited the area a year later, despite the widespread installation of these keycard-operated standpipes, accessibility to water remained a significant challenge. Following the initial setup and funding provided by the system's creators or consultants, local community members encountered difficulties in loading funds onto their cards. This was primarily due to the lack of support for such cards by local banks, rendering the standpipes unusable for many individuals. Consequently, despite the visible presence of the water system, it remained out of reach for those who needed it most.

This prompts us to reconsider the essence of technology itself. What truly is technology if it fails to meet the needs of the people it intends to serve? Simply advancing a technology does not inherently necessitate replacing existing systems. Instead, each technology addresses specific needs, acknowledging that not all solutions are universally applicable or required at all.

The narrative recounted highlights the repercussions of the division that Matt proposes within GIS. By segregating the software and hardware components from the human element, methodologies, and data, we risk encountering situations like the one witnessed in Uganda.?

In the case of the sensor technology implemented for the water system, a crucial oversight occurred regarding the holistic understanding of technology adoption. Had the decision-maker(s) possessed a deeper comprehension of the scientific principles and framework underlying the technology, they would have recognized the necessity for infrastructure adjustments. However, implementing such adjustments is not a simple task; what one sector may perceive as an improvement, another may view as a challenge.

This underscores the importance of considering various factors, including the individuals involved, the pertinent questions being addressed, the quality and relevance of the data utilized, and the appropriateness of the tools employed. It is the alignment of these elements— the right people, questions, data, and tools—that renders GIS not only feasible but also practical in addressing real-world challenges effectively.

Another perspective I'd like to offer is that, as GIS professionals, we could be seen as "thieves" in a sense. We've taken and adapted concepts from various disciplines such as mathematics, statistics, computer science, economics, and business, among others. Consider this: where there's statistics, spatial statistics emerges; with the advent of data science, spatial data science follows suit; as artificial intelligence develops, GeoAI emerges; and where there's business intelligence, spatial business intelligence arises. We've consistently integrated spatial components into emerging fields, perpetuating what I term the "geospatial cycle."

Essential components like GPS, geocoding, digitizing, and georeferencing will remain indispensable to some people regardless of technology advancement. GIS continues to evolve because we continue to borrow and integrate from other fields. It can't die because each new child will go through the traditional process maybe a little faster but there will always be a need for traditional? methods like georeferencing, digitizing, geocoding, 2D maps etc.

However, one challenge is that the more we push for advancement, the more we risk losing sight of the fundamental connection between space, time, and events. This phenomenon, which I term the "containerization of GIS," is becoming increasingly prevalent. Our pursuit of advancements often results in streamlined processes where users simply click a button and expect results without fully comprehending the underlying spatial principles.

I've observed instances where statisticians, business professionals, and others struggle to ask or answer spatial questions when confronted with spatial data. Conversely, some GIS users rely heavily on default settings without grasping their implications to different scenarios. I have encountered individuals facing significant challenges due to fundamental misunderstandings, such as the distinction between geographic and projected coordinate systems.

Addressing this "containerization" issue requires a sustainable approach. It necessitates ensuring that users not only utilize GIS tools effectively but also understand the principles underpinning spatial analysis. This way, we can prevent oversights and errors that may arise from a lack of spatial literacy. Therefore , we shouldnt overly celebrate the so-called advancement yet, for the implication of the sacrifice we will definitely pay in the near future.

Matt's assertion that GIS is transitioning to the cloud due to the emergence of big data holds some truth and is indeed a noticeable trend. However, what often goes unspoken is the recent emergence of tools and technologies? like duckDB and other column databases which seem to be reversing this trend. Since the introduction of duckDB, there's been a notable shift in the definition of what constitutes big data. Many have come to realize that they may not necessarily require cloud computing, as their data can be efficiently processed locally on their personal computers. For individuals like myself, dealing with datasets of up to 10 million rows, subscribing to the lowest tiers of services offered by platforms like Amazon Web Services or Google Cloud Services may no longer be necessary with the adoption of column databases like duckDB. Furthermore, recent advancements in data formats such as Geoparquet, GeoArrow, and deck.gl are further contributing to this shift. These technologies, which integrate duckDB with JavaScript, enable browsers to load interactive maps and dashboards at unprecedented speeds, surpassing traditional benchmarks. As these technologies continue to evolve, the necessity of relying on the cloud for data processing may become a luxury for individuals and small to medium-sized companies.

In the future, it's plausible that true big data processing will become the realm of large organizations with global services such as Amazon, Google, United Nations, etc unless public web services are required. Otherwise, many operations may opt for internal dashboard and reporting operations via intranet, leading to substantial cost savings,hence reversing the cloud migration trend.

In conclusion, while the assertion that GIS is dead may spark debate, the reality is far more nuanced. The dynamics within the GIS space are intricate, and while surprises may arise, the industry's evolution is undeniable. I agree with Matt that the pace of change within the GIS industry is rapid, and it's incumbent upon us all to stay abreast of emerging trends. However, declaring GIS as dead overlooks its enduring adaptability and capacity for innovation.

It's crucial to align our skill development with our goals and the needs of our respective environments. For instance, investing heavily in cloud data management skill sets may not be strategic if you anticipate working in contexts where funding for cloud services is limited or unavailable. Similarly, prioritizing dashboard building over essential skills like data collection and quality assurance may not be prudent in environments focused on building GIS data.

Ultimately, GIS's resilience lies in its adaptability and its practitioners' commitment to continuous learning and technological advancement. As long as there are spatial questions to be answered and challenges to be addressed, GIS will remain relevant, evolving, and indispensable.There will always be spatial questions that require a traditional approach to GIS. Therefore, GIS is not dead and cannot die, given its inherent adaptability, knowledge base, and capacity for technological innovation.?

For those discouraging comments on the matter, I entreat you to read Candice Leubbering article: Am I Geospatial Enough?