Despite its vague definition, “Big Data” is all the rage in IT-related industries. Underscoring both the trendiness and elusiveness of the term, Forbes recently published an article entitled “12 Big Data Definitions: What’s Yours?” in which they say,

The widely-quoted 2011 big data study by McKinsey highlighted that definitional challenge. Defining big data as (#3) “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze,” the McKinsey researchers acknowledged that “this definition is intentionally subjective and incorporates a moving definition of how big a dataset needs to be in order to be considered big data.” As a result, all the quantitative insights of the study, including the updating of the UC Berkeley numbers by estimating how much new data is stored by enterprises and consumers annually, relate to digital data, rather than just big data, e.g., no attempt was made to estimate how much of the data (or “datasets”) enterprises store is big data.

Aside from focusing on size and scope (“how big is BIG? What constitutes data?”), the practical idea behind “Big Data” is the systematic collection and analysis of disparate data-sets from a variety of sources in order to deduce quantifiable trends not apparent from any single data set. For example, collecting consumer purchasing information to deduce the political leanings of individuals in a given zip code. Or predicting consumer tastes based on what similar consumers purchased in the past. Essentially, Big Data boils down to making use of very large sets of data to make informed decisions about things that are difficult to directly measure.

Thus far, big data in the gaming industry is confined to online game publishers using online metrics to measure audience behavior. There have been some notable controversies as the gaming community suspects publishers’ primary concerns have more to do with Digital Rights Management than improving game performance. The last SimCity release was so mired technical difficulties that it poisoned the brand, leading to the triumph of a rival game, Cities: Skylines.

For now, rather than focusing on games employing real-world big data sets, or the data challenges and travails confronting game publishers, I’ll focus on games that simulate and manage very large collections of information.

When I think of “Big Data” games I think of either games that track large sets of information under the hood and present the user with a variety of control panels to manipulate that information, and games that begin with a small set of data and simple interactions that grow in complexity as the game progresses and the simple interactions accumulate in more complex combinations. Chess is the classic example of this second type of “emergent” complexity.

Upon starting a game, the first type of game’s myriad control panels and available options seem overwhelming, while the second type of game’s minimalist starting point seems simplistic. Generally speaking, the first type of game is “Data Heavy,” with a lot going on at the start; the second type starts with a blank canvas (or highly-ordered initial state as in chess) that gets progressively complex as units interact.


Varieties of Data Heavy Games

The most common types of “Data Heavy” games are so-called “4X” games and Business Simulation games. 4X refers to “eXplore, eXpand, eXploit, and eXterminate,” in which the player must manage limited resources to overcome opponents in zero-sum competition. Often taking the form of military or historic conflict, notable 4X games include the Civilization series and titles published by the Swedish company, Paradox Interactive: Europa Universalis and Victoria 2. According to Wikipedia,

4X games are noted for their deep, complex gameplay. Emphasis is placed upon economic and technological development, as well as a range of non-military routes to supremacy. Games can take a long time to complete since the amount of micromanagement needed to sustain an empire scales as the empire grows. 4X games are sometimes criticized for becoming tedious for these reasons, and several games have attempted to address these concerns by limiting micromanagement, with varying degrees of success.

Business simulations emphasize process management as well as resource management and competition. Notable examples include Railroad Tycoon (and its innumerable “tycoon” knock-offs) and Capitalism.

Business simulation games, also known as economic simulation games or tycoon games, are games that focus on the management of economic processes, usually in the form of a business. Pure business simulations have been described as construction and management simulations without a construction element, and can thus be called management simulations. Indeed, micromanagement is often emphasized in these kinds of games. They are essentially numeric, but try to hold the player’s attention by using creative graphics. The interest in these games lies in accurate simulation of real-world events using algorithms, as well as the close tying of players’ actions to expected or plausible consequences and outcomes. An important facet of economic simulations is the emergence of artificial systems, gameplay and structures…

Because business simulations simulate real-world systems, they are often used in management, marketing, economics and hospitality education. Some benefits of business simulations are that they permit students to experience and test themselves in situations before encountering them in real life, they permit students to experiment and test hypotheses, and that subjects seem more real to them than when taught passively from the blackboard. They are also used extensively in the professional world to train workers in the financial industries, hospitality and management, and to study economic models (an association of professionals, ABSEL, exists for the sole purpose of promoting their use), with some simulations having in excess of 10,000 variables. Economic simulations have even been used in experiments, such as those done by Donald Broadbent on learning and cognition that revealed how people often have an aptitude for mastering systems without necessarily comprehending the underlying principles. Other games are used to study the behavior of consumers.

4X Example: Victoria 2

Victoria 2, as well as it’s American Civil War variant, A House Divided, is among Paradox Interactive’s collection of outstanding historical simulations. Because they all share the same framework, a player could begin a game in Crusader Kings II, which takes place during the 12th. Century, save the game and continue ruling your kingdom across all the subsequent titles, climaxing in 1930’s with Hearts of Iron. Which means the Holy Roman Empire or the Republic of Venice might become pivotal players in 20th. Century politics.

Business Simulation Example: Automation

Automation is a car company tycoon game in which you design and build cars from scratch. It is you who designs everything from the very core that is the engine, over the chassis, to the suspension and the car’s looks. Several games have tried this before… but were able to merely scratch the surface… Rather than start at the dawn of the automotive era, the game begins in the year 1946, just after World War 2 and focuses on bringing modern engines, platforms and automotive concepts to market through the year 2020.”

 Varieties of Emergent Games

Currently the most popular type of emergent game is the “open world,” or “sandbox” game where competition is de-emphasized in favor of experimentation and building. Minecraft and Sim City are primary examples. In these games, enormous complexity evolves from the interaction of thousands of individual units. This complexity is easier to manage, however, because the player is involved from the beginning in developing the structure. Much like a messy desk might look chaotic to an outsider, the emergent complexity of a sandbox game is intuitively organized by the player so end up knowing where everything is. As their edifice grows, the player often tweaks and adjust individual elements to create a pleasing whole.

Sandbox Example: Minecraft

Minecraft, the current game of the moment, is a great example of simple elements combined into astonishing complexity. Visiting friends in Massachusetts, their kids (age 8 and 10) were obsessed with Minecraft. They setup a Minecraft server with friends and cooperated in building elaborate castles, hideouts and dungeons within the game’s simple terrain. The game defines blocks of various materials (rock, lava, wood, etc.) with specific properties. Objects such as swords and axes help the player mine and collect the different material, combining them into new objects. The resulting possibilities continue to surprise and delight users.

The following videos show a very early version of Minecraft as a cave-exploring game, followed by a later version in which a player created an operational 16-bit computer within the Minecraft environment:


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