Laying the groundwork for big data utilization through asset evaluation for AI translation data.
Since entering the 2000s and with the arrival of the internet and mobile, also came the era of big data. With the utilization of things, information, communication, augmented reality, AI, and various unstructured data since 2020,the scale of data has reached the era of zettabytes (ZB).
Thea mount of data generated and replicated in 2019 reached its peak. Due to the increased demand caused by the global pandemic of COVID-19, the amount of data has significantly exceeded previous expectations. This can be attributed to more people working and learning from home, resulting in more frequent use of home entertainment options.
According to IDC, the domestic big data and analytics tool market is expected to grow by11.1% compared to the previous year, reaching $138.886 billion (2.7054 trillion won) in 2023. With an increased annual growth rate of 10.9%, the domestic market is projected to reach $229.423 billion (3.9771 trillion won) by 2027.
According to the recent "Big Data Market" report published by 'MarketsandMarkets', the global big data market reached $138.86 billion in 2020,with a compound annual growth rate of 10.6%. It is further projected to reach$229.42 billion in 2025. The total amount of data generated, captured, copied,and consumed worldwide is expected to exceed 180 zettabytes by 2025,highlighting the importance of data assets.
With the rise of data assets as a profitable model, data monetization is considered a high-profit business model in South Korea with the enactment of the ‘Basic Data Law’.
In fact, both technology transactions and data transactions involve the trading of intangible assets.
Technology transactions are divided into technology transfer contracts, technology license agreements, technology development contracts, and technology joint development contracts, and are regulated by laws such as the ‘Intellectual Property Law’, ‘Contract Law’, and ‘Fair-Trade Law’. In the case of international technology transactions, the ‘Foreign Exchange Transactions Law’ and the ‘Foreign Investment Law’ also apply.
Data transactions, on the other hand, involve contracts for providing or using data and are regulated by laws such as the ‘Personal Information Protection Act’, the ‘Information and Communications Network Act’, and the ‘Data Industry Promotion Act’.
South Korea became the first country in the world to enact the ‘Basic Data Law’, which came into effect in April 2022, and is leading the expansion of the data economy by establishing data transaction companies in February 2023 as well.
In the case of technology transactions, after receiving a technology quality evaluation, it enters the stage of technology commercialization. At this stage, a technology valuation is conducted to assess the value of the technology, and based on this, a technology pricing policy is derived, leading to technology transaction intermediation.
Data transactions follow a similar process. After receiving a data quality evaluation and entering the stage of data commercialization, a data valuation is conducted to determine the value of the data, and based on this, a data pricing policy is derived, leading to data transaction intermediation.
On May 26th, Combiro CEO Yoon-joo Lee conducted a "Data Asset Evaluation Workshop" for the utilization of big data assets of Twigfarm, an AI translation company.
Combiro announced its plan for data asset evaluation and shared its approach with a group of data valuation experts (data transaction companies Yang-soo Park, Bok-nam Park, Sang-bok Kim, Pil-gyu Yang, Sung-hwan Kim, Geun-ho Lee), external collaborating organizations (Korea Electronics and Telecommunications Research Institute, Public Interest Technology Lab P.I.T., Korea Association for Intellectual Property Services), and sponsoring organizations (Korea R&D Industry Association).
More than 20 project participants attended the session to share and develop data asset evaluation and commercialization strategies. The theme presentations were conducted by Yang-soo Park, a data trading agent, and Sunho Baek, the CEO of Twigfarm Co., Ltd.
Twigfarm Co., Ltd. (CEO Sunho Baek), which possesses data assets, is a startup with outstanding technology that has built a large amount of AI training data for scientific and technological terms (Korean-English translation) that has been recognized for better natural language processing capabilities than Google by Telecommunications Technology Association(TTA).
Combiro Co., Ltd. (CEO Yoon-joo Lee) is the executing agency for evaluating the data assets of Twigfarm Co., Ltd. as part of the research and industry promotion project organized by the Korea R&D Industry Association.
With the advent of the big data era, the amount of data assets has been increasing exponentially, and big data is now being recognized as an asset. The participants unanimously agreed that the purpose of data asset valuation is not only to enhance corporate value but also to expand into new businesses through the establishment of data utilization strategies.
Data asset evaluation is conducted through data quality assessment, data commercialization, data valuation, data pricing policy formulation, and data transaction intermediary arrangement, presenting various utilization methods for big data.
Data quality assessment evaluates the quality of data at a level that can provide useful value to users by securing its freshness, accuracy, and interoperability. When executing these data quality rules and evaluating and providing data based on defined conditions, it presents business ideas for data utilization, data-based business models, and commercialization plans according to the type of data product, such as DB type, inquiry/subscription type, report/consulting type, processing type, and solution sales type.
Data commercialization is then carried out through the analysis of the feasibility, competitiveness, and expertise of data commercialization.
Data valuation evaluates the economic value of data traded and distributed in the market in terms of value, rating, scores, etc., thereby facilitating active data distribution and transactions in the market.
The price of data is the agreed exchange value between the seller and the user, considering market prices, inflation, and input costs. Price policies for data are established, and data transactions (intermediation) involve the establishment of measures for the transmission, use, and transfer of data between suppliers (sellers) and demanders (buyers) both online and offline.
With the increasing global trend of big data becoming a profitable business model, the perception of data transactions is changing.
Yang-soo Park emphasized, "By conducting data asset evaluation, recognizing the value of data clearly, and formulating strategies for data management and utilization, distribution and sharing can be facilitated. If we further develop data-based business models, data will be recognized as an accounting asset."
When utilizing data asset evaluation, determining the appropriate price for data and improving the transparency and reliability of data transactions, data trading will progress. Identifying the potential profitability and risks of data and enhancing the rationality and efficiency of data investment will likely lead to an increase in data investment.
Moreover, recognizing data as intangible assets of companies and incorporating them into enterprise valuation will also increase the value of data as a corporate asset. Particularly, with the utilization of data as collateral and the development of data-based financial products, it is expected that "data financial support" will become possible. Additionally, evaluating the social value and public nature of data will enable the formulation of data policies.
Yoon-joo Lee, the CEO of Combiro, stated, "The data asset evaluation conducted this time is the first case of applying data asset evaluation to actual cases in the absence of standardized models or methods." The CEO further added," Combiro will continue to lead efforts in the application and expansion of data asset evaluation in the future."