The Importance Of The Eu Data Economy

Today’s economy revolves around data. As societies move into the digital age, more and more data is produced daily. The amount of data across the world is expected to increase further exponentially as data holds an enormous potential in various fields. The digital commissioner Gabriel expressed the potential importance of data: “Data lies at the core of the 4th Industrial Revolution. This is an essential resource for economic growth, competitiveness, innovation, creation and society's progress in general”.

The 2017 European Data Market study measured the size and trends of the EU data economy, and showed that the data economy is already a reality today. Approximately 6.1 million EU citizens were considered as ‘data workers’ in 2016, and this number is expected to grow by around 2 to 3% per year, potentially rising up to 10.4 million by 2020. In terms of the data market as a whole (defined as the marketplace where digital data is exchanged as “products” or “services” as a result of processing raw data), the European data market in the EU28 was estimated at EUR 54,351 million in 2015 and at EUR 59,539 million in 2016, thus exhibiting a solid year-on-year growth of 9.5%.

Recognizing the importance of the overall data economy, it is important to build a background about the different types of data and how it related to each other. Figure 1

Big Data is a popular term to describe an extremely large amount of data which can be created by humans or generated by a machine, like a purchase transaction records, digital videos and picture, etc.

Open Data refers to data that is available publicly to access, use and re-used at no technological restriction, discrimination and no cost.

Public Sector Information and Open Government Data

The Public Sector Information (PSI) is information generated, collected, created, collected, processed, preserved, maintained, disseminated, or funded by or for the Government or public institution; PSI could include economic, geographical, weather and business information. While the Open Government Data (OGD) is data produced or collected by public bodies or government-controlled entities (PSI) and made accessible, can be freely used, reused and redistributed.

Private Sector Information and Open Private Data

The private Sector Information is the data produced, collected and owned by either legal entities or private natural. The open private data is the data owned and published by private stakeholders. An example of a private Open Data portal is “Uber Movement Open Data portal” owned by the transportation network company Uber. The website provides anonymised data from over two billion transportation movements.

EU Open Data

According to the Open Data Barometer, which is a global measure of how governments are using and publishing open data; the UK is the global open data leader for many years.The EU collects and produces data in many areas in public interest such as energy, environment, transport and economy known as public sector information (PSI). In 2003, the European Commission launched a directive to allow the re-use of public sector information in order to generate value for the society and the economy through the re-use of this type of data. The directive based in the idea that the data is non-rivalrous which means that the use of the government for the data in the purpose which originally collected for does not prevent the use of data again on other purpose. However, not all the public sector data is available to reuse, according to the 2015 regulation on the re-use of Public Sector Information, the regulation only apply on data that the public sector body has been identified as available to reuse also it must be owned by that public sector and there are no intellectual property rights owned by a third party.Furthermore, on the grounds of protection, the regulation prevent the use of documents containing personal data as per the Article 8 (EU General Data Protection Regulation), national security or public security information, statistical confidentiality or commercial confidentiality.

The EU open data can be founded in the EU open data portals (EU ODP) where data been collected by government, business, academia or any organizations as the portal encourage more and more companies to be open and accountable. The open data drives innovations in many aspects. For example, in society by increasing the government transparency, growth and efficiency. In environment by improving the energy consumption, and reducing the pollution of water, soil and air etc.As well as the huge impact of the open data in economic which this part of research will focus on.

The European commission in it is Digital Signal Market review express the value of data for the EU economy. According to the Data Landscape recent report, the value of the Data Economy will nearly double from about 377 Billion Euro in 2018 to nearly 680 Billion Euro in 2025 and represent 4% of the overall EU GDP.

‘Creating Value Through Open Data’ is a study by The European Data Portal Study which determined the Open Data’s economic advantages; specifically, the size of the Open Data potential market in the EU28+ by looking at the major indicators which includes: the created jobs, the direct size of the market, efficiency gains and cost savings. The research also categorizes the economic benefits sourced from the Open Data use into indirect as well as direct benefits. To start with, the direct benefits are expressed in the form of currency benefits that are realized in terms of transactions in the market like revenues as well as Gross Value Added (GVA), jobs involved in the production of products, and the cost savings. On the other hand, Indirect advantages are i.e. new products and services, increased efficiency in public services, knowledge economy growth, time savings for users of technologies using Open Data, and development of related markets.

Usually, the advantages come from the increased use of the Open Data, a better data quality, new products and services, more areas in which Open Data is applied, the efficiency gains for both data publishers and users, increased trust and improved user satisfaction as well as a better reputation of the providers of the Open Data.

The term Open Data does not just mean the data is legally open, it is also means the data is technically open, which indicate that the file is machine readable. In practice, this means that the file format and its content can be accessed by the AI applications and are not restricted to a particular non-open source software tool.

Open data playing an important role in unlocking the potential of AI applications. It also enables the AI to gain their data from reliable resources like the public organizations which would increase the high-quality and reliability of the data which in turn would increase the AI trustworthy.

The importance of data for the AI

Data is the fuel powering the AI systems. Accessing a vast amount of high-quality data, will enhance AI decision-making process to produce a quicker and more effective results. The revolution of data is growing rapidly among the companies, companies who do not use data in their system or not accessing a high-quality data might not be able to be competitive in the market. According to recent report published by MIT Sloan Management Review and The Boston Consulting Group; 84% of companies are adopting AI to obtain or sustain a competitive advantage and 75% are adopting AI in their business in order to develop their business.

The lake of data also has a huge negative impact on the AI, as it limits the use of the data, without accessing a hyper-relevant data, the AI might be isolated and discounted.

As the AI system is a combination of statistical and mathematical techniques where there is a common debate whether the most important part of the AI are algorithms or data? To answer this question, it is important to distinguish between the AI and Machine learning ML. ML is the most popular subfield of AI where system can learn from data, identify patterns and make decisions.

In ML, data is not only crucial to operate the system, but also it is important to trine the AI model as the AI algorithms are not natively intelligent; they learn inductively by analysing data. As a result, without training the system, algorithms cannot learn.

Ravelin, is a leading company that uses ML to provides a fraud detection services to the world’s online business. It trains their ML by providing it with examples of different types of fraud to be able to recognise any attempt of fraud and give an advance warning to the company’s clients. To keep their high-reputation and quality services ,Ravelin’s ML should be updated continually to tackle any new types of fraud otherwise their fraud detection services will be limited . The founder of the company express that if a comparative company design an AI model to compete my company, they would do so by accessing a better data compared to the ML design.

There are other types of AI based on rules and mathematical techniques like Delimiting Al in which the algorithms might be more important than data.