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'I think I discovered a military base in the middle of the ocean' -- Null Island, the most real of fictional places

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This paper explores Null Island, a fictional place located at 0$^\circ$ latitude and 0$^\circ$ longitude in the WGS84 geographic coordinate system. Null Island is erroneously associated with large amounts of geographic data in a wide variety of location-based services, place databases, social media and web-based maps. While it was originally considered a joke within the geospatial community, this article will demonstrate implications of its existence, both technological and social in nature, promoting Null Island as a fundamental issue of geographic information that requires more widespread awareness. The article summarizes error sources that lead to data being associated with Null Island. We identify four evolutionary phases which help explain how this fictional place evolved and established itself as an entity reaching beyond the geospatial profession to the point of being discovered by the visual arts and the general population. After providing an accurate account of data that can be found at (0, 0), geospatial, technological and social implications of Null Island are discussed. Guidelines to avoid misplacing data to Null Island are provided. Since data will likely continue to appear at this location, our contribution is aimed at both GIScientists and the general population to promote awareness of this error source.
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“I think I discovered a military base in the middle of the ocean” -
Null Island, the most real of fictional places
Levente Juh´asza,* and Peter Mooneyb
aGIS Center, Florida International University, Miami, FL, USA
bDepartment of Computer Science, Maynooth University, Ireland
ARTICLE HISTORY
Compiled April 19, 2022
ABSTRACT
This paper explores Null Island, a fictional place located at 0°latitude and 0°lon-
gitude in the WGS84 geographic coordinate system. Null Island is erroneously as-
sociated with large amounts of geographic data in a wide variety of location-based
services, place databases, social media and web-based maps. While it was originally
considered a joke within the geospatial community, this article will demonstrate
implications of its existence, both technological and social in nature, promoting
Null Island as a fundamental issue of geographic information that requires more
widespread awareness. The article summarizes error sources that lead to data be-
ing associated with Null Island. We identify four evolutionary phases which help
explain how this fictional place evolved and established itself as an entity reaching
beyond the geospatial profession to the point of being discovered by the visual arts
and the general population. After providing an accurate account of data that can
be found at (0, 0), geospatial, technological and social implications of Null Island
are discussed. Guidelines to avoid misplacing data to Null Island are provided. Since
data will likely continue to appear at this location, our contribution is aimed at both
GIScientists and the general population to promote awareness of this error source.
KEYWORDS
web mapping, geoweb, fictional place, geocoding, error, human-computer
interaction
1. Introduction and motivation
There is a special place on Earth at an equally interesting location. Although it has
no spatial extent, it has a thriving community and digital economy: every day many
people record their fitness activities, there are countless properties offered to sale and it
is even the origin of malicious cyber attacks1. Many restaurants are located there, and
delivery drivers are always available to make stops at vacation rentals, there is social
media activity with millions of photos uploaded, and the place even has an airline.
This place is truly a product of our digital age. It is called Null Island, and it is located
at the center of the Earth. Although its reputation is growing as more and more people
become aware of its existence, this paper will make a valuable contribution to raising
awareness of the most interesting fact about it: that it does not exist in a way most
places do. This paper will make an important contribution to the discourse of place in
*Author to whom correspondence should be addressed (ljuhasz@fiu.edu)
arXiv:2204.08383v1 [cs.HC] 18 Apr 2022
GIScience. Even though Null Island is ‘fictional’, its implications concerning geographic
information are very real, and as such, Null Island and its associated issues should be
discussed, in a serious and sustained manner, within the GIScience community and
beyond.
The name Null Island is used to refer to the location on Earth where the equator in-
tersects the prime meridian at 0°latitude and 0°longitude (0, 0) in the Gulf of Guinea
off the coast of West Africa (Figure 1a). Although a weather observation buoy part of
the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) pro-
gram is permanently anchored to the seabed at that location (Figure 1b), Null Island
cannot be considered a physical entity (i.e. an island). As Parker (2020) puts it: ‘out-
side databases, Null Island does not exist’. It exists only as a placeholder for bad data
in databases and digital maps. It is also regularly the topic of social media discussions
(e.g. as highlighted in the title of this paper), popular media articles and blogs as well
as appearing as an artistic concept. This renders it as a real place without traditional
spatial properties. Originally considered as an insider joke within the geospatial com-
munity we argue that the concept of Null Island evolved into a wider phenomenon with
significant social and technological implications that reach beyond GIScience. People
have always found geographic extreme points and superlatives interesting (Wieckowski
2021, Varnajot 2019a), and fictious places can become real. For example, Agloe, NY
was originally a ’paper town’ or copyright trap in the 1930s. Following its inclusion
in paper maps, the Agloe General Store opened, which was followed by a gas station
and two houses, which eventually lead county administrators to consider its existence
(Green 2009, Latif et al. 2019). However, Null Island is different in the sense that it is
the product of human-computer interaction and it was discovered rather than made
up. This paper will also demonstrate that far from existing as an imaginary extreme
point Null Island has transformed into a fictional point that has become very real,
even though it does not exist. Subsequently, we contribute to raise awareness among
the GIScience community with this structured, considered and academic treatment of
Null Island as a subject. A discussion of Null Island, as is presented in this paper, is
missing from the literature. We also provide guidelines on how to avoid the pitfalls and
negative aspects of Null Island when accessing, visualizing, managing and conversing
about geogpraphic data and information.
The remainder of the paper is structured as follows. The final parts of this introduc-
tion establish the importance of discussing Null Island in Section 1.1 and describe the
methods and materials used in the study in Section 1.2. Section 2 defines Null Island
by summarizing error sources that assign geographic data to (0,0) in Section 2.1, and
by describing the history of Null Island in Section 2.2. Section 3 gives an accurate rep-
resentation of data that we can find on Null Island today at the time of writing, which
is followed by Section 4 that details the implications of having erroneous data on (0,
0). The findings and implications are discussed in Section 5, where guidelines to avoid
mistakes that incorrectly put data on Null Island are also presented (Section 5.1). Fi-
nally, Section 6 concludes the work by providing a summary and directions for future
research.
1.1. The importance of discussing Null Island
One of the important contributions of this article is to frame a discussion of Null
Island as a fundamental and conceptual issue of geographic information. Technological
advancements in the last few decades have made it very easy to create web-based maps
2
Figure 1.: Null Island’s location at the intersection of the equator and prime meridian
(a), and a PIRATA buoy named Soul permanently anchored to the seabed at that
location (b)
without any or much geospatial training. This can be considered as the democratization
of mapping since creating maps is not the privilege of geospatial professionals anymore
(Crampton and Krygier 2005). On the other hand, lack of geospatial training can easily
lead to bad mapping practices resulting in faulty or even intentionally misleading maps
(Mooney and Juh´asz 2020) as well as errors that could otherwise be avoided by careful
mapping practice. For example, people not familiar with spatial data types, projections
and other concepts are likely to ‘rediscover’ Null Island from time to time when data
is incorrect and appears in the middle of the ocean. This is apparent in the amount
of questions and discussions similar to ’why is my data mapped off the coast of West
Africa?’ in programming and GIS related Q&A (question-answer) websites, forums
and issue trackers. It is therefore important to discuss Null Island as a fundamental
and conceptual issue of geographic information. We contribute detailed discussion of
Null Island and its associated issues which are currently missing from the GIScience
literature. We believe this omission in some ways contributes to its ‘mystical nature’.
Most academic studies that mention Null Island use it in place of (0, 0) location
(Mound et al. 2019, Dijt and Mettes 2020, Hill et al. 2020, Stein et al. 2020, Gr´egoire
et al. 2021, Hakima and Bazzocchi 2021, Kousis et al. 2022), and only a handful
studies go beyond this simplistic view to mention Null Island in relation to its original
purpose: to trap geocoding errors (Janowicz et al. 2016, Kopsachilis and Vaitis 2021).
Null Island’s history and purpose was also described in an architectural design article
by Dillon (2021). Compared to these, our paper will deliver a more comprehensive
treatment of what Null Island really is by describing and explaining its significance
that reaches well beyond the geospatial profession.
This article therefore contributes an innovative, informative and timely contribution
to both the academic spatial community and the general public by providing a detailed
account of Null Island and its associated issues. It will serve as a guide that not only
describes the technical considerations of Null Island from software development and
geospatial perspectives, but it will introduce the growing interest in Null Island as a
social and artistic concept as well. Based on investigation, the article will also provide
3
guidelines to avoid common pitfalls that wrongly associate geographic data with Null
Island.
1.2. Materials and methods
One of the key investigative measures employed in order to find materials about Null Is-
land relied heavily on web searches2, as well as searches in various online databases and
services. We strategically searched through the content of websites, blogs, databases,
mailing lists, forums, news archives (e.g. NewsBank), Q&A sites (e.g. GIS StackEx-
change available at https://gis.stackexchange.com) as well as social media (e.g.
Twitter, Instagram) and other location-based services (e.g. Waze) to find mentions
and examples of Null Island and how the term is being used on the Internet. Where
available, we also utilized application programming interfaces (API) to further explore
content that otherwise might not be available on the public facing web, or would be
difficult to find. For example, the geosearch method on Wikipedia’s API is able to
locate all articles on or near a specific coordinate (MediaWiki 2022). For text-based
searches, by default we searched for the specific expression ‘Null Island’. This intro-
duces a natural bias against alternative names and potentially misses relevant content.
To mitigate this bias, we also included other terms referring to the same location in
our searches (e.g. ‘zero latitude, zero longitude’, 0°N, 0°E, etc.). For location based
queries, we searched for data on or geographically near (0, 0).
The searches mentioned above can only provide a snapshot of what is available
on the internet today. However in reconstructing the story of Null Island, historical
accounts must also be considered to build an accurate picture on the evolution and use
of the term. For that reason, we placed a strong emphasis on investigating historical
websites. More specifically, throughout our investigation we made extensive use of the
Wayback Machine (WM, http://web.archive.org), which is part of the Internet
Archive Project, capable of retrieving past content of websites (Arora et al. 2016), even
if they are not available today. For example, in 2022, the domain nullisland.com is
listed for sale and the original content is not available to browse anymore. However,
the WM stores historical versions of the website that made our investigations possible.
It is important to mention that the WM is only able to retrieve websites that were
indexed at least one point in the past, and is only able to retrieve a static snapshot
at the time of indexing. The WM is also used to provide permanent links for online
resources cited in the article.
2. Defining Null Island
On the surface, Null Island is a technological phenomenon that is product of human-
computer interaction, and a result of computerized mapping systems erroneously han-
dling spatial information. We begin by providing a detailed description of how such
errors can arise. The second half of this section reconstructs the history of Null Is-
land by providing a timeline of important events. These events together demonstrate
that the concept of Null Island evolved into a social phenomenon in addition to the
technological nature of it.
4
2.1. How do we travel to Null Island? - Error sources
Geocoding is the process of turning descriptive geographic data (e.g. an address or
place name) into an absolute geographic reference and practically speaking geographic
coordinates (Goldberg et al. 2007). It is an essential function not only in GIS and sci-
entific research but in everyday life. Given the proliferation of services for navigation,
spatial search and so on millions of geocoding requests are made daily, such as enter-
ing ‘123 Main Street’ in a navigation application, or asking a personal voice assistant
about the weather: ‘What is the weather in Miami, FL like’? These requests require
correspondence between the descriptive information and geographic coordinates. For
example, a navigation system needs to know the coordinates of ’123 Main Street’ in or-
der to find the best route to that location. Similarly, the text ’Miami, FL’ needs to be
converted into geographic coordinates first before a spatial query can be constructed
to identify location specific weather forecasts for that location. In many situations
geocoding happens in the background without users explicitly being aware of it. For
example, when listing a house for sale on real estate websites, the address is converted
into geographic coordinates so that the website can provide a map interface for poten-
tial buyers to browse. The geocoding process works quite well due to the emergence
of high quality place and address databases and gazetteers. But what happens when
geocoding fails? The address or place in question might not exist at all, or the city’s
name might be misspelled in the input stream. Historically, instead of returning an
error, many geocoding services used default locations to revert to in case of geocoding
failures. By choice, this was often the coordinates of (0, 0). Setting a default location
instead of discarding data without valid or missing georeference can also happen in the
codebase of applications outside geocoding services. For example, missing latitude and
longitude values can be represented as empty character strings (i.e. (’’, ’’) array)
in input streams. Empty strings might get interpreted as (0, 0) latitude - longitude
coordinate pair. Then, (0, 0) in the WGS84 geographic coordinate system (the default
in which web based maps get input coordinates) gets placed at the intersection of the
equator and prime meridian, off the coast of West Africa.
To understand how such software-based errors be introduced into geospatial appli-
cations, one needs to understand how data values are handled in database management
systems (DBMS) and handled within data structures in programming languages. The
so-called ‘null value problem’ relates to the treatment of missing information in re-
lational DBMS and is well known in database research. Even Codd, the inventor of
the relational database model, wrote extensively on the semantics of handling missing
values (see e.g. Codd 1979, 1986). A potential problem with ‘null values’ is that their
presence introduces three-valued logic, where not only true and false boolean values
are possible. There exists a third unknown or undetermined value. This is problematic
since it introduces a new degree of uncertainty in attribute values. Furthermore, the
treatment and evaluation of ‘null values’ depend on the DBMS (Thalheim and Schewe
2011) and there are also inconsistencies within the Structured Query Language (SQL)
standard (van der Meyden 1998). Since whether a NULL value is interpreted as zero,
FALSE or NULL depends on many factors, the ‘null value problem’ is considered a
programmer or software developer’s nightmare (P˘as˘areanu and Visser 2009). Outside
databases, JavaScript, the language of most web mapping platforms, works with a
variety of data types (i.e. numeric,boolean,string, etc.), and also allows the pro-
grammer to convert one to another through methods called type conversion and type
coercion (implicit conversion). For example, both parseFloat() and Number() built-
in functions are designed to convert data to the Number data type. Both functions
5
Table 1.: Examples of explicitly converting data (type conversion) to floating point
numbers in JavaScript with the parseFloat() and Number() built-in functions
Input value Converted value
parseFloat(Input) Number(Input)
1’0’ 0.0 0.0
2’’ NaN 0.0
3’0asd’ 0.0 NaN
return the number 0.0 when converting the character ’0’ to a number (Table 1, line
1). In other cases, however, different behavior can be observed, for example when
passing an empty character string (‘’) to these functions (Table 1 line 2). The empty
character string is converted into a NaN (Not a Number, a special data type) by the
parseFloat() function, and into the 0.0 number by the Number() function. This case
is quite common if the input data was originally stored in a comma separated text file
(CSV) and had missing geospatial coordinates. Another example can be converting
a character string that starts with the ‘0’ character (Table 1, line 3), which is con-
verted into 0.0 and NaN by parseFloat() and Number() respectively. This example
can happen due to misspelling values when recording the original data. The behavior
of these two functions can be confusing, especially if the programmer is not familiar
with JavaScript, or is new to programming in general. In addition, more confusion
can be introduced by the process of type coercion, which is a special type of type
conversion that happens implicitly during operations performed on two different data
types - sometimes without the programmer realizing this behavior is happening.
Geocoding and programming issues are not the only way for data points to get
placed on Null Island. Table 2. summarizes ways in which data can end up positioned
on Null Island. Apart from intentional use of Null Island either as a joke or as a
container for data, most issues presented in the table are problematic from a geospatial
perspective because of the geographic offset between (0, 0) and the real-world location
the data point intends to represent. The most common implications of bad data will
be discussed in Section 4 in more detail.
2.2. A brief history of Null Island
In order to describe the history of Null Island we have constructed a visual time-
line of important events associated with Null Island as shown in Figure 2. The figure
plots different types of events (i.e. related to technology and databases, and social
aspects including social media, general population) with different colors. The time-
line suggests that the term ‘Null Island’ was indeed originally within the geospatial
community as an insider joke since all events that we were able to identify within
four years after the first mention are related to individuals identifying themselves as
geospatial professionals. Upon closer examination of these events, it appears that ‘Null
Island’ as a concept managed to break away from the geospatial community and es-
tablish itself within the context of larger groups, as indicated by multiple events in
the database/technology and general population categories. We identified four evolu-
tionary phases in the timeline of Null Island based on our estimation of the interest
the term received from various communities. These timelines are fuzzy but we believe
they provide good anecdotal guidance to the phases of evolution of Null Island. The
four phases are as follows:
6
Table 2.: Error sources that place data on Null Island
Issue source Description Example
Default location Instead of not returning data in case of failures, returning
(0, 0) as the default location. This behavior can be a result
of geocoding, or the programmed behavior of applications
Multiple addresses georefer-
enced to Null Island in Fig-
ure 6e.
Programming issues Unintentional programming errors, such as data type con-
versions or error handling that lead to (0, 0). This can
be a result of an inexperienced programmer, lack of test-
ing, issues with the input data (e.g. missing values), or the
combination of these.
Newline characters preceding
the final </coordinates> tag
in KML files rendered the
last point of coordinate ar-
rays in Null Island(Google
Code 2011)
Hardware/software issues Geolocation methods (e.g. GPS/GNSS receivers, wireless
geolocation, cell triangulation) failing to obtain fix coordi-
nates and report (0, 0) instead
A digital image with the GPS
Position EXIF tag: 0°0’
0.00" N, 0°0’ 0.00" E
Projection issues Latitude - longitude coordinate pairs (in degrees) inter-
preted as projected coordinates (e.g. in EPSG:3857)
25.7N, 80.2W (Miami,
FL) would be rendered
25.7m North and 80.2m
West from Null Island in the
WGS84/Pseudo-Mercator
(EPSG:3857) projection
Intentional use Data is deliberately associated with the coordinate (0, 0),
due to, for example users’ desire for increase privacy (e.g.
location spoofing); explicitly referencing Null Island as a
place or joke
An Instagram post about ‘Air
Null’ a fictional, humorous
airline (Figure A4)
Container for data Using Null Island’s concept as a deliberate container for
data with no or uncertain geographies
See Section 3.2
(1) Phase 1: Known within the geospatial community: “Like no place on Earth” -
An insider joke (2008 - Early 2010s)
(2) Phase 2: Increased popularity and acceptance within the larger technology com-
munity (Early 2010s to mid-2010s)
(3) Phase 3: Null Island is now successfully reaching out into the general population
(Mid-2010s to late 2010s)
(4) Phase 4: Moving beyond technology only - the concept of Null Island is trans-
formed into an artistic concept (Late 2010s to present)
References to some of the events omitted from the following subsections and Figure 2
are provided as an appendix in Table A1.
2.2.1. Phase 1: “Like no place on Earth” - An insider joke
Most sources agree that the term ‘Null Island’ was coined in 2008 by Steve Pellegrin,
a data analyst who at that time worked at Tableau, a data visualization software
company. His intention with the term was to ’describe data goofs’. In the same year,
a website dedicated to the fictional Republic of Null Island was created (Figure 3a).
Historical DNS (domain name system) records show that the 2008 version of the
domain name was owned by Steve Pellegrin (Figure A2), which confirms that Null
Island was originally coined by him. The website created a backstory detailing the
island’s history, geography and economy (Pellegrin 2011). According to Pellegrin, the
island is inhabited by 4,000 people, it has the highest number of Segway scooters
per-capita in the world, and most of the working age population works in the software
development industry. The website clearly establishes Null Island as a joke, which
is further reinforced in a ’blog-like’ section of the site where ‘fun-facts’ are reported,
7
Figure 2.: Timeline of important events related to Null Island
Figure 3.: First examples of digital content dedicated to Null Island; a website dedi-
cated to the fictional ‘Republic of Null Island’ (a), and a map showing olympic medal
counts of the 1896 summer olympics erroneously rendering data on Null Island (b)
such as erroneous maps showing data mapped to Null Island (Figure 3b). The site also
featured a webshop, selling Null Island branded merchandise, such as coffee mugs, t-
shirts and hats. The first mention of Null Island on Twitter appears to be from 2009,
as a response to a user asking about being wrongly geolocated ’off the coast of Africa’.
The response tweet by Christopher Currie (senior software developer at Tableau) reads
as ’We call that spot Null Island’, which implies that by that time the term was
established at Tableau to refer to (0, 0). The first Twitter account dedicated to Null
Island (@nullisland) was created in May 2011 in the same platform, with multiple
other ones following (e.g. @nullislandgang,@nullislandbouy, and @MaptimeNull).
At this stage, with the exception of the nullisland.com website, Null Island ap-
peared as a dimensionless object at the center of the world. An important step in
establishing Null Island as a more widely accepted fictional place was providing it
with more elaborate spatial properties in the form of an outline. The first version was
created in 2010 by GeoIQ and Stamen Design, when they included it in their newly
designed basemap style called Acetate (Migurski 2010). The outline was based on the
major island from the video game Myst, which at its peak popularity in the 1990s was
the best selling video game in history. Perhaps one of the most significant events in the
real history of Null Island happened in early 2011, when it was added to version 1.3 of
8
the Natural Earth (NE) database (Natural Earth 2011) as a troubleshooting country.
The intended purpose of adding a 1m2polygon centered at (0, 0) was to flag geocoding
failures, which at the time were routed to (0, 0) by most mapping services. The feature
has a scale rank (a measure roughly corresponding to web map zoom levels) of 100,
indicating that it should never be rendered in maps, but should only be used during
analysis to keep errant points off maps (Natural Earth 2011). The significance of Null
Island’s inclusion in NE is that the dataset is in the public domain making it part of
one of the most popular sources for geographic data. This large scale dataset has been
downloaded close to seven million times as of 2022 February. We argue that this has
provided Null Island with unprecedented exposure and opportunities to be discovered
and explored with many applications that require geographic data incorporating NE.
2.2.2. Phase 2: Acceptance within the larger technology community
Events in this phase allowed Null Island to reach an audience beyond the geospatial
community and be known within the larger technology landscape mainly consisting
of developers, data scientists and open data advocates. Adding the representation of
Null Island to databases not only continued after NE but also broadened in scope.
In addition to appearing in other geospatial datasets, like Geocommons in 2014, Null
Island was included in general collections, such as Wikipedia in 2013 and Wikidata in
2014. Even though the nature of Null Island is playful, it started to gain significance
as a more serious concept. For example, Who’s on First, a gazetteer project that
aims to represent all places in the world assigned the distinguished permanent ID
of 1 to Null Island (https://spelunker.whosonfirst.org/id/1/), and occasionally,
the very first node in the OpenStreetMap (OSM) database also gets moved to (0,
0)3. Similarly to Twitter, other social media outlets as well as social news aggregator
websites that were popular among programmers also mentioned Null Island for the
first time between 2012 and 2016 (Figure 2 and Table A1). In 2012, Google released
a so-called Easter egg version (Wikipedia contributors 2022) of Google Maps closely
resembling 8-bit video games which allowed users to explore the world in 8-bit (Nomura
2012). This special version of Google Maps included an imaginary island at (0, 0),
borrowed from the computer game Dragon Quest (Figure 4a). The original 2010 outline
of Null Island by GeoIQ and Stamen has also been reworked by GNIP (a technology
company later acquired by Twitter) in 2013 as a SVG file that allowed wider adaptation
of the outline using standard graphic software4and subsequently included on more
merchandise, such as T-shirts and stickers. Furthermore, the addition of the outline
to GeoCommons (now based on Myst Island’s shape) was built into numerous web
basemaps. For example, Facebook’s map products still render the outline of Null Island
in 2022, as seen for example on Mapillary (now owned by Meta, the parent company
of Facebook) in Figure 4b.
2.2.3. Phase 3: Successfully reaching the general population
We observe that the idea of Null Island was able to reach beyond the geospatial
community and spark the interest of larger technologically oriented audiences from its
role in many conversations across the Internet. In order to judge the significance of Null
Island during this phase, a natural next question is whether it had reached a general
familiarity within the general population that did not necessarily have background and
interest in GIScience or computer science-related disciplines. To assess this, we utilized
Google Trends and extracted the search interest in the term ’Null Island’ over time,
9
Figure 4.: Null Island and its more elaborate spatial properties by the technology
community: Google Maps Easter Egg featuring Null Island in 2012 (a), and Null
Island’s outline based on Myst Island as appears on Facebook’s map products in 2022
(b)
which shows the extent of web searches that were conducted on Google5. Google does
not show the absolute number of web searches, but rather provides an index of interest
from 0 to 100, calculated within a given period, where 100 is the peak popularity of
the search term. An interest of 50 means that the search was half as popular for that
specific time. The value of 0 means not enough data was available to calculate the
index (Ballatore et al. 2020). Google also lists other searches made by users who were
interested in Null Island. The top 5 related queries were ‘null island google maps’, ‘null
island buoy’, ‘null island flag’, ‘0 0 coordinates’ and ‘null island t shirt’ in order of
decreasing popularity. This list of related queries suggests that search interest shown
in Figure 5 represents interest in Null Island, and not the result of random noise from
web searches.
The previous two phases show how Null Island gained popularity within the geospa-
tial and wider technology communities, however, Figure 5 suggests that this did not
infiltrate the general population until 2016. There is evidence of slight, sporadic in-
terest before 2016 for example a mention in The Sunday Herald in Glasgow, Scotland
in 2014 (Jameison 2014). However the majority of search interest values remain 0
or very low. The peak popularity was reached in 2016. By this time, the original
2013 Wikipedia article was translated into major languages such as German, Spanish,
French, Italian and Russian. By 2022, this list has grown to 17 languages including
Chinese, Japanese, Arabic and Portuguese among others. The peak popularity in 2016
can be traced back to popular media outlets reporting stories on Null Island. We found
evidence of at least three independent major contributions that were picked up and
shared by many other media and social media sources numerous times. First, the Li-
brary of Congress released a blog post in April 2016 titled ’The Geographical Oddity
of Null Island’ (St. Onge 2016). This was followed by an informational video released
by MinuteEarth on Youtube titled ’Null Island: The Busiest Place That Doesn’t Exist’
(MinuteEarth 2016). This video has accumulated over 2.2 million views as of time of
writing in 2022. To further add to the list of popular outlets reporting on Null Island,
The Wall Street Journal wrote “If you Can’t Follow Directions, You’ll End Up on
Null Island” which appeared both in print and online (Lee Hotz 2016). These media
mentions popularized the idea of Null Island to a general audience, which is apparent
in a more sustained web search interest seen in Figure 5 after 2016.
10
Figure 5.: Search interest of the term ‘Null Island’ on Google Trends shows peak
popularity in 2016 and sustained interest since then
2.2.4. Phase 4: Discovery by the arts - now more than just technology
Long before the geospatial revolution, the first color cartoon ever made for television,
Colonel Bleep was created in 1957 (Beck 2018). The show featured a prominent location
as Colonel Bleep’s headquarters called Zero Zero Island, which was located where the
equator meets the prime meridian (Figure A5a). Although this fictitious land mass is
not identical to Null Island, this shows that interest in the ‘center of the Earth’ by
the visual arts is not new and that (0, 0) was considered a special location Timothy
(1998a).
Recently, other forms of arts have also discovered Null Island as an artistic concept.
Artists have started using it as a metaphor and a myth where all lost objects (i.e.
without locations or coordinates) are collected. The interest seems to stem from the
paradox that Null Island is a tangible, known location that exists in place databases
and in common knowledge, yet, it is non-existent technically (Rose 1997). Therefore,
the idea of blending imaginary and real geographies seems to get more popular since
2019 when the first art exhibition dedicated to Null Island called ’NULL ISLAND:
Exploring the Busiest Place on Earth that Doesn’t Exist’ was held by ADS4 at the
School of Architecture at the Royal College of Art, London. In another exhibition,
Mapping the Cartographic in 2020, Deborah Mora creates a video installation called ‘0°
N, 0°E’ designed to retrace the origins of Null Island and collect digital materials from
biologist, geologists, such as satellite images, 3D models, photos, etc. that represent
nature to create her video6. Mora notes that ’Null Island becomes a timeless, liminal
place where all these objects try to survive virtually, beyond material deterioration’.
Another artistic representation of Null Island by Let´ıcia Ramos is shown in Figure A5b.
Null Island also lends its name to a book (Moreno 2019) and a collection of poems
called Null Landing (Hines 2022). These artistic representations of Null Island open
up a larger discussion about fiction, geography and literary nonsense that is beyond
the scope of this paper.
3. What is Null Island today?
The previous sections have described the technical details of how data can become
associated with Null Island. We have also carefully demonstrated the growing interest
and awareness about Null Island over the last number of years. This section illustrates
why Null Island is often seen as the busiest or most popular place on Earth.
11
3.1. A placeholder for “bad” data
Nicknames have been assigned to Null Island due to the amount of different data that
accidentally ends up on Null Island. This data spans across databases and datasets
and affects some of the world’s most popular location based services with hundreds
of millions of users. This indicates that “bad data” on Null Island is not an isolated
case. Naturally, a lot of technological advancements have taken place since Null Island
was first coined in 2008 which influences the types of examples we encounter. For
example, newer, improved versions of mapping and geocoding software are more likely
to have improved error handling and more reliable results therefore, in our opinion,
the likelihood of wrongly locating data on Null Island has probably decreased since
2008.
Most location-based services (LBS) mainly rely on smartphone geolocation. Smart-
phone geolocation does not only use satellite geopositioning. Other methods using
wireless and cell phone triangulation are also used to determine the geographic loca-
tion of a device (Merry and Bettinger 2019). Even though these methods are designed
to be redundant, poor or no position can still affect user generated data. This leads to
contents such as photographs and other geotagged content being associated with (0, 0).
Such problems span a wide variety of applications, such as geotagged photo services,
fitness activity trackers, and more traditional social media outlets. Figure 6a shows
over 300,000 geotagged photos on Flickr geolocated on Null Island. Unlike Flickr,
that accepts positional data as is without checking, other services may post-process
photographs, such as Mapillary (Juh´asz and Hochmair 2016) where 3D scene recon-
struction from overlapping images is used for quality checking. Despite this the issue of
locating photographs on Null Island remains as illustrated in Figure 4b. Fitness tracker
software are another type of application relying on geolocation from smartphones and
other devices, such as GPS-enabled smart watches. Strava, a leading global company
in this area, publishes a global heatmap that aggregates user activities to show areas
that are favored by the its fitness or user community (Kulyk and Sossa 2018). Fig-
ure 6b features a screenshot from this global heat map centered at Null Island, that
shows that many fitness activities are being uploaded with coordinates on or near (0,
0). Social media data that are commonly used in GIScience are also affected, such as
Twitter (Figure 6c) and Snap Map, Snapchat’s map interface (Juh´asz and Hochmair
2018). Figure 6d shows that Snapchat not only displays posts on Null Island, but
the location is also searchable by a built-in geocoding service that lets users zoom to
a location of their choosing. AirBnB, the most popular peer-to-peer property rental
service, currently lists over 300 vacation rentals in the Gulf of Guinea (Figure 6e).
Yelp allows users to review restaurants and other establishments while also providing
a POI (point of interest) database. Previously, it was found that business oriented
services similar to Yelp provided reliable POI positions on the local scale (Hochmair
et al. 2018), but as Figure 6f shows these serives are not immune to geocoding errors
and one can find several restaurants appearing on and near Null Island.
It is not only spatial data that contributes to this popularity of Null Island. In-
teractive web maps play an important role in make this location visible. Microsoft’s
Hotmap (used to visualize map viewing patterns) was the first such web-based map
that popularized the study of how people interact with online maps. Plotting the lo-
cation of map requests, that is, map tiles that were loaded by web mapping software
and viewed by users (Figure 7a). This actually helped reveal a software bug that acci-
dentally sent users to (0, 0) (Fisher 2007). Badly configured maps still exist today. We
confirmed this by visualizing the tile access logs of OSM7. Figure 7b shows the map
12
Figure 6.: Recent examples of data wrongly associated with Null Island are present
across different geospatial apps and services: (a) Flickr geotagged photos, (b) Strava
fitness activities, (c) geolocated Tweets, (d) Snaps on Snapchat as well as the loca-
tion of Null Island is searchable, (e) AirBnB vacation rentals and (f) Yelp venues
(restaurants and other POIs)
13
Figure 7.: Visualizing popular areas that web map clients load (i.e. users see) reveal
increased usage near Null Island as seen in Microsoft’s Hotmap (a); and OSM tile
access visualized on level 12 (upper) and level 14 (bottom) (b)
tile usage statistics of the default tileset displayed on openstreetmap.org, which is
also loaded by many other applications. Maps in Figure 7b highlight areas with darker
colors that are viewed more often. The upper size of the figure visualizes map tiles
on zoom level 12 (ideal display for city/town overview maps), while the lower portion
of figure uses zoom level 14 (more detailed view where individual suburbs and roads
are also visible and distinguishable). Null Island is prominently displayed across all
zoom levels (others not shown in Figure 7b) which suggests that this is not an isolated
issue. A wide array of web maps using the default OSM tiles suffer from some sort of
misconfiguration that force them to load areas on or near Null Island where otherwise
there would have been no data to actually see.
3.2. A container of data with missing or uncertain geographies
Following its inclusion in the NE dataset, Null Island was widely considered as a ‘place-
holder for bad data’. However, the container or placeholder concept can be generalized
to purposefully include data with no or uncertain geographies. An example of this is the
widely popular COVID-19 dashboard developed by Johns Hopkins University (Dong
et al. 2020) that plotted confirmed cases on a world map during the Coronavirus
disease 2019 (COVID-19) pandemic. An early version of this dashboard intentionally
mapped cases with unassigned locations on Null Island (Figure 8a). However, this
behavior was changed later when the creators realized that mapping uncertain ge-
ographies without representing this uncertainty is questionable cartographic practice
(Mooney and Juh´asz 2020). This was confirmed in an interview with the creators of
the dashboard: ‘I thought it was a great place to put everything that doesn’t have a
specific location yet. But that upset a lot of people, so that’s gone’ (Keiser 2020).
In the case of intentionally using Null Island as a container for data with no or
uncertain geographies, Null Island can be considered as a liminal place (Turner 2018,
Conti and Cassel 2020) or uncertain non-place (Aug´e 1995). These describe a state of
uncertainty and in-betweenness. Phyisical places are liminal when they are transitory
in nature and their purpose is to connect other places. They are not destinations as
people are not supposed to stay there for long. Examples include bus stations, streets
14
Figure 8.: Null Island as a liminal place containing data with uncertain geographies in
a COVID-19 dashboard developed by Johns Hopkins University (a) and in the catalog
of SFO Museum (b)
or airports (Huang et al. 2018). However, these spaces are not necessarily physical.
Null Island’s liminality comes from its essence in connecting the imaginary or uncertain
with the real world. Cope (2018) uses this concept as a device to signal (or contain)
places with uncertain geographies in the catalog of the San Francisco International
Airport (SFO) museum. Figure 8b shows this functionality implemented in the SFO
Museum’s digital collection. The figure highlights two now defunct airlines associated
with SFO (e.g. once operating a route to or from the airport), with unknown countries
of origin. Therefore, the airlines are cataloged to “visit” Null Island until the origin
country can be identified and coded in the database. The catalog contains several
other airports, airlines and companies “visiting” Null Island (https://millsfield.
sfomuseum.org/countries/1)8.
3.3. Null Island equivalents in other coordinate systems
As we have discussed so far, Null Island is a place located at the origin of the WGS84
geographic coordinate system, in the Gulf of Guinea off the coast of West Africa. The
geographic significance of this location is different from that of other geographically
famous locations such as superlatives (Varnajot 2019b) and extreme points (L¨oytynoja
2008a) (southernmost, tallest points, etc.) In this way the location of Null Island is
arbitrary and is dependent upon the WGS84 datum and geographic coordinate system
that arbitrarily chose its prime meridian. Contrary to popular belief, the meridian
crossing the Royal Observatory in Greenwich is located 102 m west from the zero
meridian used by modern satellite navigation receivers, that use geocentric reference
frames, and their realizations of the WGS84 and the International Terrestrial Reference
Frame (ITRF) (Malys et al. 2015). Subsequently Null Island’s location is also laterally
offset from the Greenwich meridian historically referred to as “the prime meridian of
the World”. Theoretically, there can be as many Null Islands as coordinate systems. To
illustrate this, Field et al. (2014) created a web map showing alternative Null Islands
by plotting the origins of all geographic and projected coordinate systems supported by
ESRI (Figure A3). However, none of these other locations gained significance nor are
used in contexts similar to that of the “original” Null Island. This is directly related to
two factors. Firstly because WGS84 is the de facto standard input coordinate system in
JavaScript-based web mapping software and secondly that the WGS84 geodetic datum
15
and geographic coordinates are used by consumer-grade global navigation satellite
system (GNSS) receivers such as GNSS chips found in modern smartphones9.
Even though most web mapping platforms rely on the Web Mercator projection for
rendering purposes and on the WGS84 geographic coordinates for data input, there are
other alternatives. For example, D3.js (data-driven documents)1, a popular JavaScript
data visualization library for the web generates SVG graphics from data as opposed
to rendering map tiles. The origin of the viewport coordinate system of SVG images is
located at the top-left corner (Dahlstr¨om et al. 2011). If D3.js is used incorrectly (e.g.
by an inexperienced developer not familiar with cartographic projections), converting
between spatial and pixel coordinates can result in NaN values which are placed at
the coordinate system origin at the top-left corner by the SVG renderer. This is the
same issue causing web maps to render bad data at Null Island (see Section 2.1). This
issue is present in practical programming related Q&A (see e.g. StackOverflow (2018))
which suggests that the top-left corner as a location is fundamentally similar to Null
Island as it is caused by technical issues in mapping or visualization systems. However,
unlike 0°latitude and 0°longitude, the (0, 0) in the SVG coordinate system (even if
the image represents a map) does not correspond to one specific location on Earth.
The real world location of the SVG’s (0, 0) depends on the current map image.
4. Implications of Null Island
At this point we have considered the definition, history, evolution and a consideration
of what Null Island represents today. In the following sections we consider what are
the implications of Null Island in terms of geospatial technologies, social perception of
place, and some guidance on how to avoid erroneous situations involving Null Island.
4.1. Geospatial technology
Although Null Island is a point object, its existence raises several questions and issues
across disciplines. These implications together elevate Null Island to becoming a global
issue that must be considered in spatial applications and studies. Perhaps the most
common implication that concerns the layman is inaccurate visualization when Null
Island’s location is present in geographic datasets. According to Monmonier (2018),
most ‘blunders that mislead’ are a result of cartographic inattention and inadequate
editing. Although these blunders are not intended to purposefully mislead not all map
users are informed or are aware of cartographic fallibility. We found several examples
from real-world applications that are incorrect, such as an in-seat map on a flight
indicating the take-off location to be Null Island instead of New Orleans, posted by a
user on Twitter with over 1.5 million followers (Figure 9a10). Sharing misleading maps
with large audiences is problematic in the era of fake news, since people tend to trust
maps as facts, and therefore a misleading map showing Null Island’s location might
be misinterpreted by someone, go viral, and even be promoted by the media (Mooney
and Juh´asz 2020). The issue is especially pronounced in the context of web maps that
are are not necessarily made by trained professionals. Another example of this is the
‘rediscovery of Null Island’ by a user on Reddit, who posted an ‘investigation’ with
the title ‘I think I discovered a secret Chinese military base in the middle of the ocean’
in a community of 1.5 million members (Reddit 2021). In the ‘investigation’, the user
1https://d3js.org/
16
Figure 9.: Misleading maps indicating that (a) a flight left from Null Island instead of
New Orleans, and (b) some cyber attacks originate from Null Island
referred to several data web maps that showed a ‘mysterious location’ in an island in
the middle of the ocean, such as a map showing cyber attacks real time (Figure 9b11),
and the existence of an island was also ‘confirmed by’ Strava’s activity heat map
(Figure 6b).
The implications of our discussion above reach far beyond geovisualization. Other
applications, such as geospatial analysis, geocomputation, spatial data storage as well
as geospatial programming all experience consequences. In the simplest form, a spatial
join of attribute data with an incorrectly placed data point on Null Island can result in
poor visualizations, such as the 1896 Summer Olympics medal map by country demon-
strated in Figure 3b. With geography’s transformation into a data-driven discipline
an increasing number of studies are conducted on large-scale and complex datasets at
multiple geographic scales (Miller and Goodchild 2015). For example, studying global
volunteered geographic information (VGI) or other user-generated datasets can be
used to infer the home location of users (citizens) (Heikinheimo et al. 2022), to predict
human mobility (Shen et al. 2022) or to analyze global citizen sentiment during the
COVID-19 pandemic (Okango and Mwambi 2022), to name but a few. Unlike local
or regional studies, global datasets have the possibility to include data on Null Island
(see Section 3.2 for examples). Missing or incomplete data in social media feeds can be
overcome by both advanced and manual verification approaches (Ilieva and McPhear-
son 2018). It is also routine practice to simply exclude data for other reasons such as
bot activity or to mitigate the bias caused by users with tendencies to contribute very
little or too much (Lovelace et al. 2016). There are no universally adopted guidelines
as to how to deal with these cases. However simply excluding data on Null Island
and assuming that these events did not occur can be problematic. One problem with
removing such events is that it assumes complete randomness to these “missing” data
points. This is at odds with Table 2 which suggests systematic processes are at play
leading to locations associated with Null Island. Subsequently, dropping these loca-
tions altogether might not be justified statistically. We argued that poorly configured
web maps can alter the way users interact with web maps by introducing artificial pat-
17
terns (Figure 7). Therefore, studies analyzing map viewing behavior (see e.g. Mooney
et al. (2021)) should be aware of this and not mistake increased data volume (e.g. at
Null Island) with increased activity.
In Wikipedia, currently there are only two articles explicitly assigned the coordinates
of (0, 0), namely Null Island and the Gulf of Guinea12. However, as we demonstrated
already, (0, 0) is a distinguished place with a significant role, and therefore other
articles might also be indexed at the same location by thematic map search engines
if they are assumed to be relevant. For example, Frankenplace, a prototype thematic
map search engine shows multiple Wikipedia articles on Null Island, such as Earth,
Geothermal gradient, Biosphere, and more (Adams et al. 2015). This is not an issue
itself, however, as Janowicz et al. (2016) point out, error propagation in geospatial
linked data can be problematic. As Janowicz et al. (2016) demonstrate: ‘Earth therefore
can be located at (0,0) together with the statement that its population is 6,814,400,000.
[...] Hence, it is the most populated geographic feature in the Gulf of Guinea and thus
causes the gulf to have the world’s highest population density.’
4.2. The social perception of place
The translation of Null Island’s Wikipedia article into 17 different languages suggests
both a growing interest and awareness of this location and that Null Island is trans-
forming into a larger phenomenon reaching beyond technology-oriented communities.
In January 2022, a discussion and debate began on the OpenStreetMap main mailing
list following the deletion of Null Island’s OSM object with the title ‘Was the deletion
of Null Island reasonable?’ (Albrecht 2022). In this debate, OSM contributors argued
fervently for or against the removal of Null Island from OSM. One side of the debate
argued that OSM thrives when OSM map data is verifiable on the ground13 and con-
sequently a group of contributors (including members of the authoritative OSM Data
Working Group) think that fictional places should not be added to the OSM database.
A counter argument shared by many contributors is that many suburbs and localities
also do not exist in a physical form. These divisions of geographic space exist as a
shared knowledge of locals inhabiting an area. In this regard, Null Island is no more
fictional than localities that exist only in the collective consciousness of people, and
refers to some specific area or location. This debate within OSM resurfaces from time-
to-time and one can guess that there is no apparent resolution on the horizon. The
discussion also resembles what is known as the locality debate in the United Kingdom
in the 1980s and 1990s to explain the restructuring of economies and their spatial
structures. As far back as 1991, it was argued that localities are not simple spatial
areas that are defined by an outline, but they should be defined in terms of the sets
of social relations or processes in question (Massey 1991). One might argue that Null
Island fits into this definition of locality, since its concept as well as its ‘real’ location
are collectively known by many people, and it is important enough to be regularly
part of social discussions in various channels.
Although we focus on the technological aspects of Null Island, explaining the grow-
ing popularity of it can also be approached from a social perspective. People have
always been drawn to geographic oddities and superlatives. Although many of these
places have physical properties, for example being the tallest or southernmost points,
other locations are purely sentimental in nature such as quadpoints or tripoints. In
fact, many geodetic lines and national boundaries became popular tourist attractions
because they tend to fascinate people (L¨oytynoja 2008b). There is also a body of
18
literature developing algorithms to calculate the locations of poles of inaccessibility
(Barnes 2020, Rees et al. 2021). As Joliveau (2009) argues ’once located on a map,
the fictional place becomes attractive for tourists and a potential source of profit’. In
Lee (2012) the author asks how value becomes attached to places that are not real
but fantastical constructions belonging to the realm of “secondary worlds (possible
non-actual worlds), such as Narnia and Pandora”. The author gives the example of
Platform 93
4from Harry Potter which is exemplary of an affective, liminal space.
While Platform 93
4does not exist this does not devalue its meaningfulness and value
to tourists who for many the platform at King’s Cross station London has become a
reality. The desire to visit an interesting location is not new. An early documented
example dates back to Captain James Cook’s expedition to Antarctica in the 1700s.
Joseph Bank, a botanist who planned to participate, was left out of the expedition due
to a dispute. His biggest disappointment was that he did not get the chance to stand
on the South Pole and turn a full circle on his heel through 360oof longitude (Timothy
1998b). This attraction is similar to what we see happening in Null Island’s case that
actually had been visited multiple times even though there is nothing but vast ocean
with a weather observation buoy (Figure 1b) at that location. Among the documented
visits are United States Coast Guard vessel Sherman in 2001, project ‘Towards Zero’
in 2007 (Project 2022) and most recently, Russian missile cruiser Marshal Ustinov in
2019 (Ministry of Defence 2019).
5. Discussion
In 2008, the term Null Island was used for the first time by Steve Pellegrin to describe
‘data goofs’: geographic data that accidentally gets assigned to the coordinates of (0,
0) and is then rendered at the origin of the WGS84 geographic coordinate system in
the Gulf of Guinea. Since then, Null Island refers to this specific location at the inter-
section of the equator and the prime meridian. The term has gone through different
evolutionary phases, from being used jokingly by the geospatial community to slowly
entering mainstream media. Eventually, Null Island has emerged and established itself
in GIScience and can now legitimately be considered a fundamental and conceptual
issue of geographic information.
5.1. Guidelines to avoid Null Island
Here we present practical guidelines to help GIScientists, geospatial professionals and
programmers avoid creating, and subsequently having to deal with, issues related to
Null Island. Most of the issues we discussed earlier (see Table 2) are associated with er-
rors during programming or geospatial data handling. In the geovisualization context,
most of these problems can be avoided by being more attentive and using appropriate
techniques during the cartographic process (Monmonier 2018). Since mapmaking to-
day is a process involving data handling and programming these issues can originate
from geospatial professionals and geoscientists not being experienced in programming
and software development. Software developers and programmers not being experi-
enced in understanding geographic principles can also be a contributory factor. To
minimize these errors, it is beneficial for geospatial professionals to acquire training in
programming and data management and for programmers who work on geospatial ap-
plications to familiarize themselves with basic geographic and cartographic concepts.
19
Perhaps the easiest and most efficient method to spot erroneous data points infiltrat-
ing a dataset is visually inspecting datasets on a map. Null Island’s location falls in
the Gulf of Guinea in the Atlantic Ocean, roughly 600km off the coast of West Africa.
This positioning separates the location easily from most other data points commonly
generated over landmasses. Below we list our recommended steps that can be taken
to avoid creating issues with Null Island:
Visual inspection of data (maps) for locational correctness
Use of standard software libraries for data input/output data; avoid implement-
ing custom software solutions that can introduce errors
Implement proper exception handling to avoid the null value problem in RDBMS
and applications (Berztiss and Thalheim 2007)
Software testing of custom software components for failure and incorrect behav-
ior (Ammann and Offutt 2016)
Use of debugging tools, e.g. to visualize errors (Keim 2005)
Geospatial training for programmers and developers
Technical training (e.g. data management and programming) for geospatial pro-
fessionals
5.2. A shifting socio-technological concept
The presence of four evolutionary phases identified in this paper suggests that the
concept of Null Island is not static. In the early days, it was purely a technological
issue associated with geocoding failures and computerized mapping systems failing to
correctly process coordinates. However, its significance is shifting from being a seri-
ous technological issue towards one which is more social and even philosophical in
nature. Null Island as a social phenomenon can be witnessed for example by branded
merchandise for sale (e.g. t-shirts) and social events, memes about Null Island circu-
lating mainly on the internet. The philosophical aspect is present in mapping debates,
namely, whether an imaginary place should be part of map databases (e.g. Open-
StreetMap). One side of the argument is that maps are a representation of the Earth
and imaginary or fictional places should not be part of it. On the other hand, Null
Island as a fictional place is no less real than a locality that exists only in the collec-
tive consciousness of certain groups of people, but without politically set boundaries.
In this sense, Null Island exists as a real place (even though not as a physical island)
since it refers to a specific location on Earth that is known to many people. Null Island
is not the first non-existent place going through this transformation, as it resembles
closely the story of Agloe, NY, that was originally intended as a copyright trap on
paper maps, but became a real locality featuring a general store and gas station (Fig-
ure A1). Null Island’s shift from technological to social concept can be attributed to
multiple factors both technological and social in nature. On the technological side,
most online geocoding services (e.g. Google) fixed these initial issues and improved
exception handling that originally reverted locations to Null Island when a match was
not found. Another reason for Null Island’s decreasing technological significance is
that NoSQL solutions are gaining momentum in place of traditional RDBMS and are
becoming more common. NoSQL databases are efficient in working with ‘messy’ data
such as some of the user-generated sources presented in this paper by not enforcing a
fixed database schema (Kononenko et al. 2014). A result of this flexibility is there is
no need to store NULL values when pieces of data are missing (e.g. location) which
in turn decreases the chances of obtaining (null, null) as a coordinate location from
20
such databases. Even with the changing technology landscape, encountering data on
Null Island is still common today as was illustrated in Section 3. Even widely popular
services operated by multi-billion dollar companies (e.g. Twitter, Snapchat, AirBnB)
display data on Null Island. Coupled with the popularization of Null Island by main-
stream media outlets has seen it discovered by the general population and the arts.
Humans are traditionally attracted to geographic oddities, superlatives and other ex-
treme points, including imaginary and non-physical features, such as administrative
borders, geographic lines and points of inaccessibility. In light of this attraction, it is
only natural that Null Island is considered a social phenomenon on top of the clear
technology-related nature of it.
5.3. Moving forward with the GIScience community
We believe that Null Island will stay with us in the long run since programming mis-
takes are easy to make by distracted programmers and cartographers. This is even more
pronounced when the programmer is unaware of geographic principles such as map
projections or when a geospatial professional is inexperienced in programming. These
instances will likely happen over and over again as can be illustrated with the steady
supply of Null Island related posts in programming Q&A sites (e.g. GIS StackOver-
flow) and social news aggregators, such as the re-discovery of Null Island by a reddit
user (see the title and Section 4.1). Null Island may seem like a lighthearted topic that
is part of jokes and funny conversations. However misplaced data can have serious
implications and therefore it is a topic of interest to GIScientists. Implications can
include, among others, spreading misleading information through maps, introducing
another source of bias into already noisy user-generated datasets, or error propagation
in linked geodata. To mitigate these instances, it is advisable to pay extra attention in
situations that would introduce Null Island to a dataset. Moving forward we see two
opportunities that are sometimes missed but could be easily implemented. First, more
technical training in terms of data management as well as programming should be
introduced into geospatial technology education so that the new generation of geospa-
tial professionals are fully equipped with skills that are needed in today’s technology
dependent environment. On the other hand concerning developers and programmers,
it is unreasonable to expect that geospatial training will be part of the mainstream
computer science curricula. Perhaps it is the task of the GIScience community to de-
velop accessible crash courses or offer training about geospatial principles, such as
projections and coordinate systems to computer science professionals.
6. Conclusions and future work
This paper has discussed Null Island, a fictional place located at (0, 0) in the WGS84
geographic coordinate system at the intersection of the equator and prime merid-
ian. It is traditionally used as a placeholder for ‘bad’ and misplaced geographic data
in databases. We have explained the importance of discussing Null Island as a con-
ceptual and fundamental issue of geographic information. The are several important
contributions from this paper. To our knowledge, after extensive searches, this is the
first serious scientific article dedicated to Null Island and the widespread implications
of its existence. Our paper has delivered a number of important contributions. The
paper provides the first comprehensive treatment of Null Island as a geospatial con-
cept which will be of interest to those in the GIScience. This structured and serious
21
treatment of Null Island will encourage other researchers to consider the broader impli-
cations of this real fictional place. We have also presented error sources and practices
that link or define geographic data with Null Island. By outlining four evolutionary
phases, our paper provides an accurate and evidence-based account on how Null Is-
land is used today. From a practical viewpoint the implications of wrongly attributing
data to Null Island was described and the interplay with geospatial location descrip-
tions, spatial relation terms and referencing geographic objects. Guidelines to avoid
erroneously placing data on Null Island are also provided.
Null island will continue to be a shifting socio-technological concept into the future
and this paper delivers the first comprehensive treatment of Null Island for the GI-
Science community. We believe that issues associated with Null Island will continue to
be present for mainly two reasons: 1) programming and cartographic mistakes when
handling geographic data are common among programmers not familiar with geospa-
tial concepts, and among geospatial professional not familiar with programming, and
2) humans will continue to be intrigued by geographic oddities and interesting places.
These two reasons will likely keep Null Island related discussions circulating for some
time. This paper is aimed at both GIScientist, programmers and the general popula-
tion to raise awareness of the implications that are inherently present in the existence
of Null Island. The paper can also serve the role of historical record for Null Island
for multidisciplinary research work considering exploring this topic further. For future
work, we plan to explore the concept of Null Island as a place and gain more un-
derstanding into why humans, mappers and geographers are so drawn to geographic
oddities like Null Island. Indeed, artistic representations of Null Island open up a larger
discussion about fiction, geography and simulated realities which are currently beyond
the scope of this paper.
Data and codes availability statement
Data and code sharing is not applicable to this article as no new data were created or
analyzed in this study.
Disclosure statement
The authors declare no conflict of interest.
Funding
This research received no external funding.
Notes
1https://security.stackexchange.com/questions/141780/why-are- attacks-pointed- to-null-island- in-tools-like- norsecorp
2We utilized Google (https://www.google.com) and DuckDuckGo search engines (https://duckduckgo.
com)
3See https://openstreetmap.org/node/1/history, versions #15 and #17.
4The repository that contains the SVG image is available at https://github.com/gnip/null-island
22
5The service is accessible at https://trends.google.com. We used the following query parameters to
extract worldwide search interest: date=all&q="Null Island". The query can be reproduced at https:
//trends.google.com/trends/explore?date=all&q="NullIsland"
6The archived version is available at http://web.archive.org/web/20210123224002/https://nextmuseum.
io/en/submissions/0-n- 0-e/
7Tile access logs can be downloaded from https://planet.osm.org/tile_logs/ and visualized using osm-
tile-access-log-viewer available at https://github.com/tyrasd/osm-tile- access-log- viewer
8Note that based on the URL, the country ID of Null Island is 1, which indicates that the catalog utilizes
Who’s on First (see Section 2.2.2)
9Note that different GNSS use different geodetic datums. GPS satellites are tracked in WGS84, but
GLONASS uses PZ 90. However, for the end user, especially in consumer grade receivers such as smartphones,
coordinates are reported in WGS84. See e.g. Henning (2014)
10 See original post at: https://twitter.com/natesilver538/status/1078748940974084096
11 Kaspersky Cyberthreat real-time map: https://cybermap.kaspersky.com/
12 This can be confirmed by the following MediaWiki API call that searches geotagged articles within a 1
km radius from Null Island: https://en.wikipedia.org/w/api.php?action=query&list=geosearch&gscoord=
0%7C-0&gsradius=1000&gslimit=100
13 See https://wiki.openstreetmap.org/wiki/Ground_truth
References
Adams, B., McKenzie, G., and Gahegan, M., 2015. Frankenplace: Interactive Thematic Map-
ping for Ad Hoc Exploratory Search. In:Proceedings of the 24th International Confer-
ence on World Wide Web, WWW ’15, May, Republic and Canton of Geneva, CHE. In-
ternational World Wide Web Conferences Steering Committee, 12–22. Available from:
https://doi.org/10.1145/2736277.2741137.
Albrecht, E.L., 2022. Was the deletion of Null Island reasonable? January. OSM-
talk mailing list, Available from: https://lists.openstreetmap.org/pipermail/talk/
2022-January/087164.html.
Ammann, P. and Offutt, J., 2016. Introduction to Software Testing. Cambridge University
Press. Google-Books-ID: 58LeDQAAQBAJ.
Arora, S.K., et al., 2016. Using the wayback machine to mine websites in the social sciences: A
methodological resource. Journal of the Association for Information Science and Technol-
ogy, 67 (8), 1904–1915. eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/asi.23503,
Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23503.
Aug´e, M., 1995. Non-places: Introduction to an Anthropology of Supermodernity. Verso. Google-
Books-ID: LMr8 pXJgdwC.
Ballatore, A., Scheider, S., and Spierings, B., 2020. Tracing Tourism Geographies with Google
Trends: A Dutch Case Study. In: P. Kyriakidis, D. Hadjimitsis, D. Skarlatos and A. Man-
sourian, eds. Geospatial Technologies for Local and Regional Development, Lecture Notes in
Geoinformation and Cartography, Cham. Springer International Publishing, 145–163.
Barnes, R., 2020. Optimal orientations of discrete global grids and the Poles of Inaccessi-
bility. International Journal of Digital Earth, 13 (7), 803–816. Publisher: Taylor & Fran-
cis eprint: https://doi.org/10.1080/17538947.2019.1576786, Available from: https://doi.
org/10.1080/17538947.2019.1576786.
Beck, J., 2018. The Colonel Bleep Show. September. Available from: http:
//web.archive.org/web/20181016221033/https://cartoonresearch.com/index.
php/the-colonel-bleep-show/.
Berztiss, A. and Thalheim, B., 2007. Exceptions in Information Systems. In:Proceedings of
the 9 th Russian Conference on Digital Libraries, Pereslavl. Available from: http://rcdl.
ru/doc/2007/paper_13_v1.pdf.
Codd, E.F., 1979. Extending the database relational model to capture more meaning. ACM
Transactions on Database Systems, 4 (4), 397–434. Available from: https://doi.org/10.
1145/320107.320109.
Codd, E.F., 1986. Missing information (applicable and inapplicable) in relational databases.
23
ACM SIGMOD Record, 15 (4), 53. Available from: https://doi.org/10.1145/16301.
16303.
Conti, E. and Cassel, S.H., 2020. Liminality in nature-based tourism experiences as mediated
through social media. Tourism Geographies, 22 (2), 413–432.
Cope, A., 2018. Who’s on First at SFO Museum. August. Available from: https:
//web.archive.org/web/20180828210352/https://millsfield.sfomuseum.org/blog/
2018/08/28/whosonfirst/.
Crampton, J.W. and Krygier, J., 2005. An Introduction to Critical Cartography. ACME: An
International Journal for Critical Geographies, 4 (1), 11–33. Number: 1, Available from:
https://acme-journal.org/index.php/acme/article/view/723.
Dahlstr¨om, E., et al., 2011. Scalable Vector Graphics (SVG) 1.1 (Second Edition). World
Wide Web Consortium (W3C), W3C Recommendation SVG11. Available from: https:
//www.w3.org/TR/2011/REC-SVG11-20110816/.
Dijt, P. and Mettes, P., 2020. Trajectory Prediction Network for Future Anticipation of Ships.
In:Proceedings of the 2020 International Conference on Multimedia Retrieval. New York,
NY, USA: Association for Computing Machinery, 73–81. Available from: https://doi.org/
10.1145/3372278.3390676.
Dillon, R., 2021. Zero Zero Ze(r)ro(r): How the Cartographic Thirst to Project the Real
Reveals Spaces for the Creation of New Worlds. Architectural Design, 91 (3), 88–95.
eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/ad.2697, Available from: https:
//onlinelibrary.wiley.com/doi/abs/10.1002/ad.2697.
Dong, E., Du, H., and Gardner, L., 2020. An interactive web-based dashboard to
track COVID-19 in real time. The Lancet Infectious Diseases, 20 (5), 533–534.
Publisher: Elsevier, Available from: https://www.thelancet.com/journals/laninf/
article/PIIS1473-3099(20)30120-1/fulltext.
Field, K., Williams, C., and Burrows, D., 2014. Nill Points. October. Avail-
able from: https://www.arcgis.com/apps/MapJournal/index.html?appid=
5981946e172a406485c7bb847cef3168&webmap=642091165f434bd8bbf7007976975e82.
Fisher, D., 2007. Hotmap: Looking at Geographic Attention. IEEE Transactions on Visual-
ization and Computer Graphics, 13 (6), 1184–1191. Conference Name: IEEE Transactions
on Visualization and Computer Graphics.
Goldberg, D.W., Wilson, J.P., and Knoblock, Craig A, 2007. From text to geographic coordi-
nates: The current state of geocoding. URISA Journal, 19, 33–46.
Google Code, 2011. Google Earth Issue #1291 - Newline causes LineString to include 0,0 (Gulf
of Guinea). October. Available from: http://web.archive.org/web/20161230144841/
https://code.google.com/archive/p/earth-issues/issues/1291.
Green, J., 2009. Paper Towns. Penguin. Google-Books-ID: uEGLDQAAQBAJ.
Gr´egoire, T., et al., 2021. Model independent search for transient multimessenger events with
AMON using outlier detection methods. In :Proceedings of 37th International Cosmic Ray
Conference — PoS(ICRC2021), July. SISSA Medialab, vol. 395, 934. Available from: https:
//pos.sissa.it/395/934.
Hakima, H. and Bazzocchi, M.C., 2021. Low-Thrust Tra jectory Design for Controlled Deor-
biting and Reentry of Space Debris. In:2021 IEEE Aerospace Conference (50100), March.
1–10. ISSN: 1095-323X.
Heikinheimo, V., et al., 2022. Detecting country of residence from social media data: a com-
parison of methods. International Journal of Geographical Information Science, 0 (0), 1–22.
Publisher: Taylor & Francis eprint: https://doi.org/10.1080/13658816.2022.2044484, Avail-
able from: https://doi.org/10.1080/13658816.2022.2044484.
Henning, W., 2014. User Guidelines for Single Base Real Time GNSS Positioning.
National Oceanic and Athmospheric Administration (NOAA), National Geode-
tic Survey. Version 3.1, Available from: https://geodesy.noaa.gov/PUBS_LIB/
UserGuidelinesForSingleBaseRealTimeGNSSPositioningv.3.1APR2014-1.pdf.
Hill, P.G., et al., 2020. How skilful are Nowcasting Satellite Applications Fa-
cility products for tropical Africa? Meteorological Applications, 27 (6), e1966.
24
eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/met.1966, Available from: https:
//onlinelibrary.wiley.com/doi/abs/10.1002/met.1966.
Hines, I., 2022. Null Landing. Slope Editions. Google-Books-ID: ZCOczgEACAAJ.
Hochmair, H.H., Juh´asz, L., and Cvetojevic, S., 2018. Data Quality of Points of Interest
in Selected Mapping and Social Media Platforms. In : P. Kiefer, H. Huang, N. Van de
Weghe and M. Raubal, eds. Progress in Location Based Services 2018. vol. Lecture Notes
in Geoinformation and Cartography. Springer: Berlin, 293–313.
Huang, W.J., Xiao, H., and Wang, S., 2018. Airports as liminal space. Annals of Tourism
Research, 70, 1–13. Available from: https://www.sciencedirect.com/science/article/
pii/S0160738318300094.
Ilieva, R.T. and McPhearson, T., 2018. Social-media data for urban sustainability. Nature
Sustainability, 1 (10), 553–565. Number: 10 Publisher: Nature Publishing Group, Available
from: https://www.nature.com/articles/s41893-018-0153-6.
Jameison, T., 2014. Into the alternative reality of John Le Carre’s novelist son. The sunday
Herald. Available from: https://infoweb.newsbank.com/apps/news/document- view?p=
WORLDNEWS&docref=news/156C5C74D00BBE08.
Janowicz, K., et al., 2016. Moon Landing or Safari? A Study of Systematic Errors and Their
Causes in Geographic Linked Data. In: J.A. Miller, D. O’Sullivan and N. Wiegand, eds. Ge-
ographic Information Science. GIScience 2016., Lecture Notes in Computer Science, Cham.
Springer International Publishing, 275–290.
Joliveau, T., 2009. Connecting real and imaginary places through geospatial technologies:
Examples from set-jetting and art-oriented tourism. The Cartographic Journal, 46 (1), 36–
45.
Juh´asz, L. and Hochmair, H.H., 2016. User Contribution Patterns and Completeness Eval-
uation of Mapillary, a Crowdsourced Street Level Photo Service. Transactions in GIS,
20 (6), 925–947. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1111/
tgis.12190.
Juh´asz, L. and Hochmair, H.H., 2018. Analyzing the spatial and temporal dynamics of
Snapchat. June.
Keim, D.A., 2005. Information Visualization: Scope, Techniques and Opportunities for Geo-
visualization. In: J. Dykes, A.M. MacEachren and M.J. Kraak, eds. Exploring Geovisual-
ization. International Cartographic Association. Oxford: Elsevier, 21–52. Available from:
https://www.sciencedirect.com/science/article/pii/B9780080445311504206.
Keiser, J., 2020. ‘Every day is a new surprise.’ Inside the effort to
produce the world’s most popular coronavirus tracker. Science Mag-
azine. Available from: https://www.science.org/content/article/
every-day-new-surprise- inside-effort-produce-world-s-most-popular-coronavirus- tracker.
Kononenko, O., et al., 2014. Mining modern repositories with elasticsearch. In:Proceedings
of the 11th Working Conference on Mining Software Repositories, MSR 2014, May, New
York, NY, USA. Association for Computing Machinery, 328–331. Available from: https:
//doi.org/10.1145/2597073.2597091.
Kopsachilis, V. and Vaitis, M., 2021. GeoLOD: A Spatial Linked Data Catalog and Recom-
mender. Big Data and Cognitive Computing, 5 (2), 17. Number: 2 Publisher: Multidisci-
plinary Digital Publishing Institute, Available from: https://www.mdpi.com/2504-2289/
5/2/17.
Kousis, I., Fabiani, C., and Pisello, A.L., 2022. Could a bio-resin and transparent pave-
ment improve the urban environment? An in field thermo-optical investigation and life-
cycle assessment. Sustainable Cities and Society, 79, 103597. Available from: https://www.
sciencedirect.com/science/article/pii/S2210670721008623.
Kulyk, V. and Sossa, R., 2018. Determining the tourist attractive regions by GIS analysis using
heatmaps. Geodesy and Cartography, 44 (1), 22–27. Number: 1, Available from: https:
//journals.vgtu.lt/index.php/GAC/article/view/882.
Latif, S., et al., 2019. Caveat Emptor: The Risks of Using Big Data for Human Development.
IEEE Technology and Society Magazine, 38 (3), 82–90. Conference Name: IEEE Technology
25
and Society Magazine.
Lee, C., 2012. ”have magic, will travel”: Tourism and harry potter’s united (magical) kingdom.
Tourist Studies, 12 (1), 52–69.
Lee Hotz, R., 2016. If You Can’t Follow Directions, You’ll End Up
on Null Island. The Wall Street Journal. Available from: http://
web.archive.org/web/20160713161209/https://www.wsj.com/articles/
if-you-cant-follow- directions-youll-end-up-on-null-island-1468422251.
Lovelace, R., et al., 2016. From Big Noise to Big Data: Toward the Verification of Large
Data sets for Understanding Regional Retail Flows. Geographical Analysis, 48 (1), 59–
81. eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/gean.12081, Available from:
https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12081.
oytynoja, T., 2008a. The development of specific locations into tourist attractions: cases from
northern europe. Fennia - International Journal of Geography, 186 (1), 15–29. Available
from: https://fennia.journal.fi/article/view/3709.
oytynoja, T., 2008b. The development of specific locations into tourist attractions: cases from
Northern Europe. Fennia - International Journal of Geography, 186 (1), 15–29. Number: 1,
Available from: https://fennia.journal.fi/article/view/3709.
Malys, S., et al., 2015. Why the Greenwich meridian moved. Journal of Geodesy, 89 (12),
1263–1272. Available from: https://doi.org/10.1007/s00190-015-0844-y.
Massey, D., 1991. The Political Place of Locality Studies. Environment and Planning A:
Economy and Space, 23 (2), 267–281. Publisher: SAGE Publications Ltd, Available from:
https://doi.org/10.1068/a230267.
MediaWiki, 2022. Geosearch. March. Available from: http://web.archive.org/web/
20220107083550/https://en.wikipedia.org/w/api.php?action=help&modules=
query+geosearch.
Merry, K. and Bettinger, P., 2019. Smartphone GPS accuracy study in an urban environment.
PLOS ONE, 14 (7), e0219890. Publisher: Public Library of Science, Available from: https:
//journals.plos.org/plosone/article?id=10.1371/journal.pone.0219890.
Migurski, M., 2010. Acetate Styles. November. Available from: https://github.com/geoiq/
acetate-styles/commit/136d23facbf80953ccb3eb4419a87b2b6ee0bb1a.
Miller, H.J. and Goodchild, M.F., 2015. Data-driven geography. GeoJournal, 80 (4), 449–461.
Available from: https://doi.org/10.1007/s10708-014-9602-6.
Ministry of Defence, R.F., 2019. Missile cruiser closes on Null Island in the Atlantic
ocean. June. Available from: http://web.archive.org/web/20191107152059/https://
eng.mil.ru/en/news_page/country/more.htm?id=12260767@egNews.
MinuteEarth, 2016. Null Island: The Busiest Place That Doesn’t Exist. July. Available from:
https://www.youtube.com/watch?v=bjvIpI-1w84.
Monmonier, M., 2018. How to Lie with Maps. Third edition ed. Chicago, London: University
of Chicago Press.
Mooney, P., et al., 2021. OpenStreetMap data use cases during the early months of the COVID-
19 pandemic. In: A. Rajabifard, D. P´aez and G. Foliente, eds. COVID-19 Pandemic, Geospa-
tial Information, and Community Resilience – Global Applications and Lessons. 1st ed. CRC
Press, 171–185. Doi: 10.1201/9781003181590-15.
Mooney, P. and Juh´asz, L., 2020. Mapping COVID-19: How web-based maps contribute to the
infodemic. Dialogues in Human Geography, 10 (2), 265–270. Publisher: SAGE Publications,
Available from: https://doi.org/10.1177/2043820620934926.
Moreno, J., 2019. Null Island. 1st ed. Avinyonet del Pened`es (Barcelona): Candaya SL.
Mound, J., et al., 2019. Regional stratification at the top of Earth’s core due to core–mantle
boundary heat flux variations. Nature Geoscience, 12 (7), 575–580. Number: 7 Pub-
lisher: Nature Publishing Group, Available from: https://www.nature.com/articles/
s41561-019-0381-z.
Natural Earth, 2011. Natural Earth Version 1.3 Release Notes. January. Available
from: http://web.archive.org/web/20110311120626/http://www.naturalearthdata.
com/blog/natural-earth-version-1- 3-release-notes/.
26
Nomura, T., 2012. Begin your quest with Google Maps 8-bit for NES. March. Avail-
able from: http://web.archive.org/web/20160727191317/https://maps.googleblog.
com/2012/03/begin-your-quest-with- google-maps-8-bit.html.
Okango, E. and Mwambi, H., 2022. Dictionary Based Global Twitter Sentiment Analysis of
Coronavirus (COVID-19) Effects and Response. Annals of Data Science, 9 (1), 175–186.
Available from: https://doi.org/10.1007/s40745-021-00358-5.
Parker, M., 2020. Humble Pi: When Math Goes Wrong in the Real World. Penguin. ISBN:
978-0-593-08468-7.
as˘areanu, C.S. and Visser, W., 2009. A survey of new trends in symbolic execution for software
testing and analysis. International journal on software tools for technology transfer, 11 (4),
339–353.
Pellegrin, S., 2011. The Republic of Null Island (nullisland.com). January. Available from:
https://web.archive.org/web/20110128203258/http://nullisland.com/.
Project, D.C., 2022. 0°N 0°E. Available from: http://web.archive.org/web/
20211129031332/https://www.confluence.org/confluence.php?lat=0&lon=0.
Reddit, 2021. I think I discovered a secret Chinese military base in the middle of the
ocean. April. Available from: http://web.archive.org/web/20210416233505/https:
//www.reddit.com/r/conspiracy/comments/mrrsms/i_think_i_discovered_a_
secret_chinese_military/.
Rees, G., et al., 2021. Finding Antarctica’s Pole of Inaccessibility. Polar Record, 57. Pub-
lisher: Cambridge University Press, Available from: https://www.cambridge.org/core/
journals/polar-record/article/finding-antarcticas-pole- of-inaccessibility/
0B60DD5B8B675CA16812A2250B3E3547.
Rose, G., 1997. Spatialities of ‘community’, power and change: The imagined geographies of
community arts projects. Cultural Studies, 11 (1), 1–16.
Shen, X., et al., 2022. Novel model for predicting individuals’ movements in dynamic re-
gions of interest. GIScience & Remote Sensing, 59 (1), 250–271. Publisher: Taylor &
Francis eprint: https://doi.org/10.1080/15481603.2022.2026637, Available from: https:
//doi.org/10.1080/15481603.2022.2026637.
St. Onge, T., 2016. The Geographical Oddity of Null Island. Geography and Map Division of
the Library of Congress. Available from: http://web.archive.org/web/20160506005836/
https://blogs.loc.gov/maps/2016/04/the-geographical-oddity-of- null-island/.
StackOverflow, 2018. StackOverflow question: ”d3 map point only drawed
in topleft corner”. January. Available from: http://web.archive.org/
web/20220221202552/https://stackoverflow.com/questions/48150306/
d3-map-point-only- drawed-in-topleft-corner.
Stein, M., et al., 2020. Hybrid Architecture Performance and Evaluation for Quantitative and
Comparative Analysis. In:34th Annual Small Satellite Conference, August. Available from:
https://digitalcommons.usu.edu/smallsat/2020/all2020/190.
Thalheim, B. and Schewe, K.D., 2011. NULL ‘Value’ Algebras and Logics. Information Mod-
elling and Knowledge Bases XXII, 225, 354–367. Publisher: IOS Press, Available from:
https://ebooks.iospress.nl/doi/10.3233/978-1-60750-690- 4-354.
Timothy, D.J., 1998a. Collecting places: geodetic lines in tourist space. Journal of Travel and
Tourism Marketing, 7 (4), 123–129.
Timothy, D.J., 1998b. Collecting Places: Geodetic Lines in Tourist Space. Jour-
nal of Travel & Tourism Marketing, 7 (4), 123–129. Publisher: Routledge eprint:
https://doi.org/10.1300/J073v07n04 07, Available from: https://doi.org/10.1300/
J073v07n04_07.
Turner, V., 2018. Dramas, Fields, and Metaphors: Symbolic Action in Human Society. Cornell
University Press. Publication Title: Dramas, Fields, and Metaphors, Available from: https:
//www.degruyter.com/document/doi/10.7591/9781501732843/html.
van der Meyden, R., 1998. Logical Approaches to Incomplete Information: A Survey. In:
J. Chomicki and G. Saake, eds. Logics for Databases and Information Systems. The Springer
International Series in Engineering and Computer Science. Boston, MA: Springer US, 307–
27
356. Available from: https://doi.org/10.1007/978-1-4615-5643-5_10.
Varnajot, A., 2019a. “walk the line”: An ethnographic study of the ritual of crossing the arctic
circle—case rovaniemi. Tourist Studies, 19 (4), 434–452. Available from: https://doi.org/
10.1177/1468797619836546.
Varnajot, A., 2019b. “walk the line”: An ethnographic study of the ritual of crossing the arctic
circle—case rovaniemi. Tourist Studies, 19 (4), 434–452.
Wieckowski, M., 2021. How border tripoints offer opportunities for transboundary tourism de-
velopment. Tourism Geographies, 0 (0), 1–24. Available from: https://doi.org/10.1080/
14616688.2021.1878268.
Wikipedia contributors, 2022. Easter Egg — Wikipedia, the free encyclopedia. March. Avail-
able from: http://web.archive.org/web/*/https://en.wikipedia.org/wiki/Easter_
egg_(media).
Appendix A. Additional tables and figures
28
Table A1.: References to additional events associated with Null Island
Date Event Source
4/17/2009 First mention on Twitter http://web.archive.org/web/20180910184441/https://twitter.com/
chriscurrie/status/1546199025
11/20/2010 Outline traced based on Myst Island http://web.archive.org/web/20170325024549/https://github.com/geoiq/
acetate-styles/commit/136d23facbf80953ccb3eb4419a87b2b6ee0bb1a
May 2011 First dedicated Twitter account http://web.archive.org/web/20140326105433/https://twitter.com/
NullIsland
10/25/2012 First comment on Hacker News http://web.archive.org/web/20121029121942/https://news.ycombinator.
com/item?id=4697543
10/1/2013 English Wikipedia entry created https://en.wikipedia.org/w/index.php?title=Null_Island&oldid=
575288934
5/17/2014 Wikidata entry created https://www.wikidata.org/w/index.php?title=Q16896007&oldid=130397167
2014 Added to Foursquare http://web.archive.org/web/20220411153347/https://foursquare.com/v/
null-island/508c6298e4b019412ca444cf
3/28/2014 First mention on Reddit http://web.archive.org/web/20220411153501/https://www.reddit.com/r/
ProgrammerHumor/comments/21kije/i_just_flew_in_from_null_island_and_
boy_are_my/
8/13/2014 Added to Geocommons https://raw.githubusercontent.com/geoiq/gc_data/master/datasets/
104581.geojson
7/15/2016 First story on Slashdot http://web.archive.org/web/20211206062041/https:
//developers.slashdot.org/story/16/07/15/064248/
null-island- the-land- of-lousy-directional- data
Figure A1.: A similar place transformation to that of Null Island: from being a fictious
copyright trap in paper maps, Agloe, NY became a real place
29
Figure A2.: Historical WHOIS records of the domain nullisland.com (Source: https:
//whois-history.whoisxmlapi.com/)
Figure A3.: Nill Points story map shows the origins of all coordinate systems supported
by ESRI software (Field et al. 2014)
30
Figure A4.: Intentional use of Null Island as a joke (Source: https://www.instagram.
com/p/CW235ZqBqzy)
Figure A5.: Visual arts inspired by Null Island: (a) Zero Zero Island in Colonel Bleep,
the first color cartoon ever made for television in 1957, and (b) Screen grab from an
interactive movie featuring Null Island as created by artist Let´ıcia Ramos in 2020
31
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