“According to IBM, in the present state, 2.5 quintillion data is produced on a daily basis. It is also believed that 90 percent of the data that exists in today’s world was created over the last 2 years.” With the dynamic nature of the digital sphere, the methods used to collect, create, process and transfer big data must also be equally versatile. Big data is the term often used to encompass the explosion of data and its easy availability – both in a structured form and unstructured. To get an accurate definition of big data, it can be divided into three parameters:
- Volume – This definition is mainly for the unstructured data that comes through the social media and other media forms. With the increase in sensor and machine-to-machine data being collected, it allows for large data volumes to be used for analytics, helping in relevant conclusions to be drawn.
- Velocity – This definition tracks the rate of change of data in real time. The premise for this argument is that all data that is being produced is from already existing data, therefore creating a data network. It measures the different speeds at which data activity occurs, and analyses the relationship between two data set changes.
- Variety – In the present day context, data comes in all shapes and sizes. This definition encompasses the different formats in which structured and unstructured data comes in. This kind of data is usually kept at an organizational level and is not always available for analytics, which makes managing, merging and governing of data difficult.
From a company, society or government standpoint, big data is of supreme significance because the more data that is available, the more accurate the analysis is likely to be. This in turn will lead to better decision making capabilities, better operational efficiency, economies of scale and risk management.
Big Data and Intellectual Property
However, data in its raw form cannot bring about a digital revolution. In order for it to have an impact, it needs to be appropriately collected and stored. Once it is collected, there needs to be a proper way of analyzing it and appropriate conclusions must be drawn and communicated meaningfully.
Through this process, intellectual property plays a crucial role – from the patented hardware used to collect and store data, to the copyrighted software that organizes and analyses it. Once a company decides to run analytics, the end result is protected under IP laws as a trade secret. Therefore, by extension, any reports that are published using the results of this analytics are also protected under IP law.
Intellectual Property, therefore is an intangible asset that is integral to the running of a business, and unlike any of the fixed assets, it is hard to put a price on it. This makes it difficult to explore the full depth and breadth of IP, therefore it does not allow for it to be exploited, traded or valued. However, with more stringent IP laws all across the world, there is more structure to this complex asset.
How Does Intellectual Property Protect Big Data?
- Patents – While data in its raw form cannot be patented, when it is processed and analyzed, it can be protected under patent laws. The argument to be made here is that a fair amount of innovation goes into creating the systems in place to allow for this detailed analysis. Historically, however, the system of patents has been a poor watchdog of data and its processes.
- Copyright – As is in the case of patents, the actual data is not copyrightable. The representation of data and its analysis ensues a great deal of creativity and the compilation of the database is original and therefore falls under the purview of protective expression.
- Trade secret – The data collected as well as the analytics and processes that go behind them is protected as a trade secret as it is unique from company to company. The factors that determine whether it is a trade secret or not are – economic value and reasonable efforts being made to keep this matter a secret. To this effect, big data is supported under IP law.
Limitations of Intellectual Property
Each country operates with their own intellectual property framework with offices that work independently of each other. Therefore, it becomes difficult to track down individual inventions, and more importantly keep track of their protection under different laws. This therefore leaves a grey area as far as ownership of IP and by extension, their rights are concerned.
Over the next two years, the growth of big data is projected to increase multifold, calling for more stringent and universal IP measures. The starting point is to identify the need for protection, but in order for it to be truly effective, the data needs to be collected and tabulated. Once the worldwide data is collected, it can be easily summarised and discrepancies can be spotted.