By Eneya Georgieva
Ontotext is a global provider of products and solutions in the field of semantic technologies and databases. The company integrates large volumes of structured and unstructured data, automates the access to the knowledge locked in it and analyzes this knowledge. This is how Sirma AI, better known as Ontotext, helps organizations around the world. To find out more about the technology, we interviewed Todor Primov, Head of Life Sciences and Healthcare Solutions at Ontotext – a member of Digital Health and Innovations Cluster Bulgaria.
Mr. Primov, what is the purpose of semantic technologies and how do they help companies manage their content more efficiently?
Semantic technologies are not something new and inapplicable. They follow the natural evolution of the development of technological tools from our daily life. The vision of Internet pioneers like Sir Tim Berners Lee (a British computer scientist who created the Internet format World Wide Web – WWW) also has an impact.
That’s why, after Web 2.0 (the era of social networks), we are now living in Web 3.0 (the semantic/interconnected web). The main added value of semantic technologies and all the tools they use, such as graph databases for example, is to provide the ability to trace all possible relationships between individual facts/units of knowledge that are relevant to a specific business or scientific application. For example, it would be beneficial for a general practitioner to receive automatic notifications for drug incompatibilities. Thus, if he prescribes a new drug to a patient, he will immediately know its compatibility with the drugs his patient is currently taking.
Information discovery and analysis of information are a vital part of the work in many sectors. How do your services make a difference for Healthcare and Life Sciences?
Both sectors work daily with huge amounts of heterogeneous data – internal and publicly available, well-structured or completely unstructured, etc. Very often, due to lack of resources, time and suitable technological solutions, companies fail to get the most out of the data they have. This results in inefficient work processes, untimely and inaccurate market positioning and, consequently, financial losses. No wonder it’s the more efficient way of collecting, connecting and analysing data and information that’s at the basis of digital transformation.
You help world-renowned companies such as the BBC, Financial Times and Press Association provide dynamic and personalized content to their readers. From your experience, which companies and professions rely most heavily on specialized work with data?
The truth is that the need for more efficient data analysis processes is already ubiquitous. I can’t think of an industrial sector where there is currently no need to implement more efficient processes for data analysis. This is where the role of the semantic technologies and graph databases we work with comes into play. Through them, we help enterprises turn their data into one of their main assets. As a result, they can make much more timely and adequate decisions.
Did the COVID-19 pandemic increase the interest in semantic technologies?
The global COVID-19 pandemic significantly accelerated the introduction of many new technologies to companies’ day-to-day operations, including semantic technologies and graph databases. During this period, we had the opportunity to support leading global research projects related to collecting and analyzing data on COVID-19. At the same time, we also started large-scale projects with leading pharmaceutical companies, large hospitals and health insurers.
What is essential for the development of an international niche technology company in Bulgaria?
Although Ontotext’s headquarters are in Bulgaria, we see ourselves as a global company with active presence on several continents. Our clients are in some of the most important industrial sectors such as Healthcare, Life Sciences, Finance, Automotive, Aeronautics, etc. To be globally competitive, we rely on a combination of solid technological development, mature products and solutions, narrow domain expertise and knowledge of the industry vertical that a company focuses on.
What to expect from the development of semantic technologies in the coming years?
At present, semantic technologies are mainly used to structure/extract knowledge from content. This process is done in the “old-fashioned” way – with no concern for the unambiguous naming and referencing of the objects presented in the data. When in fact, the very process of creating content and describing data has to be based on semantic technologies. The use of ontologies and specific terminologies will allow the unambiguous naming of objects and the semantic relationships between them. In this way, from its very creation, the information will be “semantic”. Then, it would be easy to use by various robotized systems (bots), it would be ready for machine learning or for the development of neural networks, which are at the basis of artificial intelligence systems.
What kind of applications of semantic technologies have you worked on in Bulgaria, and how does Digital Health and Innovations Cluster Bulgaria (DHI Cluster) contribute to making these technologies more popular?
Over the years, we’ve had different inquiries from various industry sectors such as Media, Financial institutions, Pharma, Healthcare, research organizations, etc. What they have in common is the need for an automated analysis of large volumes of dynamic and complex, structured and unstructured data for specific business goals such as increasing customer engagement and transforming legacy QnA knowledge bases into smart knowledge bases, optimizing the processes of data interoperability and data-based decision making, etc. Digital Solutions and Innovations in Healthcare (DHI), which was established only three years ago, plays an indisputable role for making these new data analysis technologies more popular and for sharing examples for their practical application in solving specific Healthcare problems. Through many national-level initiatives, the Cluster and its ecosystem of experts in various Healthcare fields has made it possible to share and exchange good practices, including Healthcare data analysis, which has contributed to increased awareness among the business community and institutions of the real potential of these technologies.