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65 Science reboot. Creation of an evidence-based literature by increasing the use of regional languages ​in science
  1. Svjatoslavs Kistkins1,
  2. Maksims Mastalers2,
  3. Aleksandra Podhvatilina2,
  4. Emil Syundyukov3,
  5. Jana Visnevska2
  1. 1Latvian Biomedical Research and Study Centre, Riga, Latvia
  2. 2University of Latvia, Riga, Latvia
  3. 3Longenesis Ltd (Hong Kong Science Park), Hong Kong, China


Objectives English as an International Language is widely used in science. Unfortunately, scientific information space is oversaturated by using International Language, while Regional Languages remain informatively poor. The oversaturation leads to the information overload1–4, reducing the quality of information and data interpretation. At the same time, non-English speaking countries publish new studies in regional journals, causing contrary effect – information deficiency in English.5

Similarly to RCSB PDB and NCBI, the authors suggest to create a novel scientific database in order to: - Enrich the regional languages allowing them to be competitive; - Concentrate on the evidence-based and up-to-date information in order to «restart the science»; - Provide information(1) in suitable for understanding way (reviews) and for accurate data description(2) (handbook). - Create more effective communication between specialists;

Methods The model of database includes:

  1. Reviews/handbooks with the appropriate translation to other languages;

  2. Comments below the topic;

  3. Discussion.

Reviews/handbooks are done by a group of scientists that works on a specific issue. The translation occurs from regional to international language and reversely. This database collects information that is written in a regional language and automatically translates it into the international language. It means that the text structure must be universal for all languages. The translation must be done by regional-international and international-regional interactions, escaping regional-regional translations. A text structure is designed for a better ‘RL-IL-RL’ translation. The structure reduces translation mistakes. After that a reader will contextually improve the text. Comments (a forum) are created below the text for the correction of mistakes, as well as suggestions to use additional information that is based on a novel scientific data. Discussion is a platform (similarly to ResearchGate) that is based on scientist’s activity suggesting topics that must be discussed. The discussion gives better verification due to variety of specialists involved in the conversation. Specialists create a community that checks information from all perspectives. Four levels of discussion will be made:

  • Red – Urgent issues (require an immediate solution);

  • Yellow – Important scientific questions;

  • Green – Novel ideas, hypothesis, future perspectives;

  • Grey – Other.

Results Thus, we can solve issues related to: - The quality of information; - Amount of information; - The quality of the language. This system also implies the constant up-to-date verification of information.


  1. Piñero D. Scientific information overload in vision: What is behind?J Optom2018;11(1):1–2.

  2. Hall A. et al. (2004), Information overload within the health care system: a literature review. Health Info Libr J, 21: 102–108.

  3. Davis D. et al. (2004), Solving the information overload problem: a letter from Canada, Med J Aust, 180, pp. 68–71

  4. Barnett G. et al. (2004). Overcoming information overload: An information system for the primary care physician. Stud Health Technol Inform 107. 273–6.

  5. Amano T. et al. (2016). Languages Are Still a Major Barrier to Global Science. PLoS biology, 14(12), e2000933.

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