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In today’s digital age, whether we know it or not, we very much depend on data as many decisions which directly impact us are made using it, from what medicine will be included in our our health insurance plan,to how much our house will cost and everything in between.
Recently, thanks to the growth of technologies such as IoT, AI and Machine Learning, the systems data scientists use to collect, analyze and disseminate data have undergone major disruptions.
With the technological revolution, the data market has seen explosive growth with the big data industry‘s estimated worth currently holding at $42 billion with forecasts predicting it to hit $103 billion by 2027. The International Data Corporation (IDC) estimates that the amount of data in the world will reach 163 trillion gigabytes by 2025.
However, the industry is still experiencing issues stopping it from reaching its full potential, which, when solved will lead to further growth in the space.
Most profit and non-profit organizations lack the know-how and resources necessary to fully take advantage of the scientific data they generate and the majority of these firms do not utilize data generated by other organizations because they do not know how to access and make use of it.
According to a survey by PwC and Iron Mountain, only 4% of firms can extract the full value of the information they possess.
Researchers attribute the low uptake to several factors such as high data integration costs, lack of infrastructure, time required to collect and analyze data, and concerns over data quality among other issues..
The chart below shows the top problems preventing firms from turning their data into usable insights.
Source: Big Data Made Simple
It is important to note that these challenges apply to both the scientific and non-scientific research.
Blockchain offers a decentralized and highly transparent platform where individual researchers, non-profits, and for-profit organizations can trade scientific data.
Firstly, the transparency blockchain offers ensures that only reputable sources can share data and everyone can track the process through which the data is acquired and presented.
Secondly, the elimination of intermediaries means reduced costs for data buyers and maximized profits for data sellers. Traditionally, data owners have to depend on intermediaries to sell their data in centralized data marketplaces which are not only costly but are also vague about what the data will be used for.
Thirdly, the availability of a single, decentralized platform where researchers can trade data eliminates geographical and regulatory barriers associated with the conventional methods of sharing data.
A blockchain project known as SciDex is an excellent example for a decentralized solution to scientific data storage and sharing. The SciDex project takes advantage of blockchain, AI, Machine Learning and Natural Language processing to provide a platform where data providers and researchers can trade data.
So if, for example a manufacturer of prescription drugs wants to release a new drug for Asthma patients, they need to conduct a study to determine the effectiveness of the drug. For the study to be accurate, the company must consider many variables such as the change of weather and air pollution in the target area.
Instead of carrying out the studies about these variables themselves and spending huge sums on research and staff, the company can source the data from the SciDex search engine. There, they simply search for and connect with the listed providers who have similar data. If there is no relevant data for the target area, the company can make a call for contribution on the platform and data scientists in those areas will respond.
The platform utilizes Ricardian Adaptive smart contracts to match data needs and offerings and a cryptocurrency known as SciToken to facilitate transactions. The SciToken can be reused on the platform or converted into other cryptos or fiat money.
For small and medium entities without IT or legal capabilities, SciDex is working on tools to integrate them with its dashboard and Index. Also, a tool will be available to help them connect with COALA IP, a blockchain-ready community for intellectual property licensing.
The same case applies for university researchers with interest in individual or corporate data. The researchers will have an opportunity to help organizations outside the academic arena by providing their services for data collection and curation.
Even though the SciDex solution is not the only project enabling incentivized data sharing on the blockchain, it is the first to combine scientific research and blockchain. With the rate at which big data and cutting edge technologies in AI, Machine Learning and blockchain are growing, there is high hope that better things are yet to come which will change data science, making it cheaper, more accessible and more accurate leading to better decision making and more accurate results for companies and consumers alike.