Database Content Research Articles

Competencies, skills, and personal attributes in job advertisements for archivists and records managers in Finland

Purpose This study aims to increase knowledge of archives and records management as a profession by examining which kinds of competencies, skills and personal attributes employers expect of and appreciate in archives and records-management professionals in Finland. Design/methodology/approach This work compiled and analysed advertisements (201 in total) of open archive and records-management positions in Finland, then subjected these to qualitative data-based content analysis with supplemental quantitative analysis. This paper illustrates the findings via tables, charts and excerpts from the advertisements. Findings Analysis revealed the public sector to be Finland’s largest employer of archives and records-management professionals. This study indicates that employers value an academic degree with some additional archive-related and records-management education and strong practical experience of similar duties. Both knowledge of legislation and language skills are appreciated. The general skills most valued by employers are interaction and co-operation abilities and skills in information technology, in customer service and in the development of work methods. Personal attributes especially valued in prospective archive professionals and records managers are independence, accuracy, self-motivation and flexibility. Originality/value This study adds to knowledge of the archives and records-management profession of the 2020s. Findings from this work may be of particular value for curriculum development.

Database of surface water diversion sites and daily withdrawals for the Upper Colorado River Basin, 1980–2022

The Colorado River drains about 8% of the conterminous United States, provides water for 40 million people, and is one of the most overallocated rivers in the world. As the upper Colorado River Basin (UCOL) contributes an estimated 92% of the total basin natural streamflow, knowledge of the location and amount of surface water withdrawals in the UCOL is important for managing the Colorado River system. Since the UCOL encompasses portions of five states, water use data are dispersed among numerous federal and state agency databases, and there is no centralized dataset that documents surface water use within the entire UCOL at a fine spatial and temporal resolution. This article presents an inventory of 1,358 major structures that divert surface water from and within the UCOL with corresponding daily time series withdrawal records from 1980 through 2022. Data compilation efforts, processing methods, and contents of this diversion database are documented, and summary information is provided.

Identification of a newly discovered virus from Culex and Armigeres mosquitoes in China

Mosquito associated virus have always been a significant threat to global health. Metagenomics offers a straightforward and quantitative means to acquire the information of novel virus and has greatly enriched the content of mosquito associated virus databases. During an entomological surveillance for arthropod-borne viruses in China, we identified a previously unrecognized virus from mosquitoes, temporarily named Huajieling virus. In this study, a total of 3,960 mosquitoes were collected and then divided into 91 pools, according to location and species. QRT-PCR and nested PCR were performed to confirm the presence of Huajieling virus. Its genomic features and phylogenetic relationships were further analyzed. Our results showed that Huajieling virus was detected in 7 of the 91 mosquito pools and that the minimum infection rate (MIR) was 0.18% (7/3,960). One complete genome sequence and 2 viral partial sequences were obtained from the Huajieling virus-positive pools. Pairwise distances analysis indicated that these amplified sequences shared high nucleotide identity. Phylogenetic analysis demonstrated that Huajieling virus is most closely related to Wufeng shrew picorna-like virus 43, which belonging to Picornavirales. Further analyses indicated that Huajieling virus is a new member of unclassified Picornavirales, and is intermediate between the family Caliciviridae and Secoviridae in taxonomic status.

Правовые особенности определения баз данных для их свободного использования

The article examines the normative concept of databases, as well as their differentiation from other materials. Particular attention is paid to the controversy about the attribution to big data databases, the consequences of such an action and the prospects for the development of civil legislation. The author assesses the legal definition of databases with regard to its completeness and compliance with modern legal realities. Besides, the author touches upon the importance of determining the content of databases, criteria for their free use by citizens for non-commercial purposes. It is suggested to expand the possibilities of free use of databases beyond personal purposes. An attempt is made to determine the balance between copyright protection and society's need for free use of databases, especially in the context of digitalization, when copying and use of significant amounts of data is becoming more and more accessible. The study emphasizes the importance of enabling society to use information from databases to facilitate search and access to knowledge, especially when such databases become the main sources of information in a particular field.

A Spatiotemporal Empowerment Framework for China’s National 3D Mapping Program 3dRGLM

Abstract. China has launched a national 3D mapping program to build 3D Realistic geospatial Landscape Model (3dRGLm) over the whole country, covering both cities and countryside. The 3dRGLM is a digital description and representation of the real 3D geospatial spaces, and is defined as a new generation geospatial data product with 3D structures, realistic scenes, and geospatial entities. Such a national or local 3dRGLm will set up a digital 3D realistic geospatial space which can facilitate the vital connection with the real geospatial space, and will serve as a new generation of geospatial information infrastructure for our society. With the acquisition of complex 3D spatial data continues to advance, managing and utilizing the massive volumes of 3D data to provide spatiotemporal empowerment applications has become a significant technological challenge. This paper analyzes the technical characteristics of 3d realistic geospatial landscape model, and then proposes the main content and basic structure of a 3d realistic geospatial landscape model database, as well as the spatiotemporal service empowerment methods based on the database. Finally, a case analysis is provided to serve as a reference for the construction and application of 3d realistic geospatial landscape.

The O-GlcNAc database: introducing new features and tools developed from community feedback.

O-GlcNAc is a reversible post-translational modification found on serine and threonine residues of nucleocytoplasmic proteins. Four years ago, we released the O-GlcNAc Database( oglcnac.mcw.edu ), a comprehensive catalog of O-GlcNAcylated proteins that has become one of the most cited resources in the field, with hundreds of unique users per month. We are now presenting an updated O-GlcNAc Database, which includes nearly 20,000 O-GlcNAcylated proteins and 48 species, marking substantial growth in data volume and scope. This paper presents the most noteworthy features implemented over the last year, often originating from feedback from the O-GlcNAc community. Among these features, we provide a brief overview of the database content, introduce our new protein viewer mode, and discuss the implementation of subcellular localization information and its applications in the O-GlcNAc score. We also provide an interface to use CytOVS, a tool designed to evaluate and sort O-GlcNAcome datasets derived from MS experiments. In conclusion, this new and improved O-GlcNAc Database represents a significant advancement in providing a comprehensive and expanded resource for researchers in the field of O-GlcNAc biology.

Zero-Shot Prompting Strategies for Table Question Answering with a Low-Resource Language

This work explores the application of zero-shot prompting strategies for table question answering (TQA) in Portuguese, focusing specifically on the Text2SQL task. This task involves translating questions posed in natural language into Structured Query Language (SQL) queries, which can be executed against a database to answer the original question. Given the popularity of relational databases across various domains, advancements in this field can substantially impact the accessibility and democratization of data as simpler and more intuitive interfaces for database interaction are developed. Despite this significant potential, progress in developing Portuguese TQA solutions remains limited. The proposed approach leverages Large Language Models (LLMs)—specifically the GPT-3.5 and GPT-4 models—through zero-shot prompting. The primary objectives are to assess the effectiveness of such LLMs in this task and to identify the most suitable prompt styles. These are evaluated using a Portuguese translation of the popular Spider Text2SQL benchmark. Results reveal that the proposed approach can generate adequate SQL queries to answer Portuguese language questions about various databases, mainly when using GPT-4. The findings suggest that including schema information and database content in the prompts is critical for satisfactory outcomes. Doi: 10.28991/ESJ-2024-08-05-020 Full Text: PDF

Automatically Generated Texts for Fauna and Flora from Structured Data Based on a Controlled Vocabulary

Information systems like Xper3 and Fulgoromorpha Lists On the Web (FLOW) play a crucial role in managing and using biological data. These platforms store extensive collections of normalized data and structured taxonomic descriptions. By using controlled terminologies, they standardize the vocabulary, significantly enhancing the processes of identification, description, and comparison of various taxa. The massive assemblages of data hosted in these repositories could be reused to generate texts in natural languages automatically. The most immediate goal is to produce, from these information systems, more accessible and user-friendly displays in the form of taxon summary pages. This automated production of textual outputs is a great addition that can be continuously updated as the databases evolve. Can structured data be reused to provide better species pages and to ensure updating if the data evolves? Will AI assist in this process, or will specific computing be needed? To address these questions, multiple possible approaches have been identified. The most basic level of this process involves converting a single line from a taxon-by-character matrix into text that resembles natural language, similar to the descriptions found in botanical or zoological guides. The primary goal is to move beyond the rigid format of matrix lines or lists of characteristics (such as characters and states) of a species, and instead generate a coherent, easy-to-read paragraph intended for human eyes. To achieve this objective, a first solution is given by Descrxp, a tool currently developed in conjunction with Xper. The user specifies the desired key outline for the output, and Descrxp fills this canvas using the database contents. While this approach is highly reliable and adaptable to various contexts, its drawback is being labor-intensive, and requiring significant human input and oversight (Fig. 1). The second solution uses AI. Data on well-known taxa, and on more obscure taxa have been tested with ChatGPT 3.5 or 4.0. ChatGPT succeeds well at generating natural language descriptions for well-known taxa (Fig. 2), providing text that appears accurate and coherent due to the extensive information available online for these groups. However, when it comes to more obscure taxa, less represented on the internet, the results can be more inconsistent and unpredictable (Fig. 3). This variability can be explained by the quality of the data the model has been trained on, which is significantly richer for well-known species. Consequently, for lesser-known groups, the generated descriptions may lack the precision and reliability seen with more familiar taxa. However, if more careful attention is given to the output of chatGPT (Fig. 4), it is possible to notice that the AI filled part of the description with inaccurate characters. Due to its inability to recognize specific scientific terminology, and to process hierarchical information, chatGPT ends up producing an over-generalized and redundant description. To go further, it would be possible to use a comparison between taxa to produce a text that highlights the remarkable features of a taxon. Moreover, it could be interesting to try and synthesize several lines of the initial matrix to extract generalized descriptions of groups of taxa, such as the description of a genus based on its included species. Using data from FLOW, Fishbase, and Xper3, the French ACDC (Counterfactual Learning for Controlled Data-to-text) project is creating a variety of text outputs. These range from "fill-in-the-blank" canvas to fully AI-generated content, utilizing data matrices derived from these pilot databases.

Database for the Fault Displacement Hazard Initiative Project

New predictive models for fault displacement and surface rupture hazard analysis developed through the Fault Displacement Hazard Initiative (FDHI) research program require a high-quality empirical database to apply advanced statistical methods and improve hazard estimates. This article discusses the development and contents of the FDHI Project database. We systematically collected, reviewed, and organized fault displacement measurements, surface rupture maps, and supporting information from the scientific literature. A framework was developed and implemented to classify principal and distributed faulting. Best-estimate net displacement amplitudes were calculated from slip component measurements and quality codes were assigned to all net displacement values. The database contains 75 historical, surface-rupturing crustal earthquakes ranging from M 4.9 to 8.0. Thirty-five earthquakes have a strike-slip faulting mechanism, while 25 and 15 events are reverse/reverse-oblique and normal/normal-oblique, respectively. Although most of the earthquakes are from Western North America, Japan, and other active tectonic regions, there are nine reverse faulting events from the stable continental region of Australia. The database contains over 40,000 individual fault displacement measurements for various slip components from roughly 28,000 observation sites. Geographic coordinates are included for all data, and event-specific coordinate systems are provided for each earthquake that transform data into an along-strike dimension. Our new database provides a standardized collection of surface rupture and fault displacement data and metadata that is the result of a comprehensive effort to create a reliable and stable product for the FDHI model development teams and the geoscience community.

El papel del turismo agroecológico como herramienta para el diseño de productos sustentables

This paper explores the role of agroecotourism in designing sustainable tourism products, drawing upon a comprehensive review of academic literature and other relevant documents. The methodological approach is qualitative and descriptive. The literature review focused on studies on agroecotourism, tourism planning, sustainable products, tourism sustainability, and local development. Techniques such as database review and content analysis were employed. Ten academic papers were selected for analysis, from different countries such as Ecuador, Cuba, Venezuela, Colombia, Peru, and Mexico. The findings highlight that agroecotourism promotes local production, community participation, and respect for the environment, being key in the creation of responsible tourism products, from an economic, social, and environmental perspective. This approach provides a comprehensive and diverse perspective that contributes to a better understanding of the current state and future needs in the field of sustainable tourism.

Indirect channel of trade agreements in deepening global value chains

AbstractPreferential trade agreements (PTAs) between trading partners are known to have positive impact on the expanding and deepening of global value chain integration due to lower trade and investment barriers. Less is known, however, is if other PTAs of PTA partners have any impact on the value‐added trade linkages of the direct PTA partners concerned. Based on compositive indicators measuring the breadth and depth of PTAs from 2007 to 2018 and using Multiregional Input–Output Table database covering 62 countries and 35 sectors and the Content of Deep Trade Agreements database, this paper estimates the multiplicative form of the constant‐elasticity augmented gravity equation model by a Poisson Pseudo Maximum Likelihood (PPML) estimator. This study shows that indirect impact of the deepening of trade agreements of a country's PTA partner exerts positive, significant impact on value‐added exports of a country. Both backward and forward linkages of a country measured by various decomposition of valued added exports indicate this indirect channel of value chain deepening effect even outweighs the direct impact from the deepening of PTAs between direct trading partners with significant policy implications in formulating PTA strategies.

Enhancing the National Cancer Database content using natural language processing and electronic health record data

BackgroundThe prevalence of missing data in the National Cancer Database (NCDB) has marked implications on clinical care and research. The objective of this study was to enhance the NCDB by decreasing rates of missingness and adding new variables using automated statistical methodology. MethodsOne health system’s NCDB data from 2011–2021 was linked to electronic health record (EHR). Variables with frequent missingness and new clinically significant variables not yet included in the NCDB including patient Eastern Cooperative Oncology Group (ECOG) score, specific chemotherapy regimen, American Society of Anesthesiologists Physical Status Classification (ASA class), and discrete surgical procedure were identified in structured and unstructured EHR data. After automated incorporation of structured data from EHR, a natural language processing tool incorporating rule-based algorithms was designed to further extract variables from unstructured notes. Rates of missingness were compared between the original NCDB and the enhanced dataset, and example multivariable models were run to assess for altered model performance with reduced missingness and the addition of new clinically significant variables (chemotherapy regimen). ResultsA total of 6050 patients with NCDB records were linked to their EHR data. Prior to enhancement, rates of missingness for key variables ranged from 2.0% to 5.3%. Following dataset enhancement, missingness was significantly reduced, with relative missingness being reduced between 31.9% to 68.0%. Of the new variables added, 1367 (22.6%) of 6050 patients gained ECOG score, and 1099 (57.8%) of 1901 who received chemotherapy gained their chemotherapy regimen. Of 2989 who underwent surgery, 979 (32.8%) gained their procedure name and 621 (20.8%) gained ASA class. Comparison of the multivariable models demonstrated significant differences between the original NCDB and the enhanced dataset. Specifically, when replacing the binary predictor for chemotherapy in the original NCDB data with discrete regimens, the effect of ethnicity diminished, and the effect of radiation became significant. DiscussionWe applied statistical methodology to reduce rates of missingness in existing variables and add new variables to enrich the NCDB. While further refinement is needed to decrease missingness in new variables, this automated methodology can replace or augment manual chart review and improve the ability of to use the NCDB to study unanswered questions leading to clinical advancements in oncology.

What Is Rural Well‐Being and How Is It Measured? An Attempt to Order Chaos*

AbstractWhile a substantial body of literature has been built on rural well‐being, due to the great heterogeneity of rural territories, the literature is highly fragmented, even contradictory. Moreover, no systematic review of the entire domain exists to guide rural decision‐makers. Debated conceptualization, contradicting results, and pressing policy requirements make it timely to deliver a systematized state‐of‐the‐art on rural well‐being to anchor public policies in the rural development domain. By systematically reviewing the scholarly literature on rural well‐being and all documents developed by government and private entities that academia highlighted as relevant to this subject, the study provides a bibliometric and thematic analysis of the domain without a time limit. Thirty‐three rural well‐being dimensions and over 9,000 indicators within these dimensions have been identified, their interconnections established and their relevance to international development goals highlighted. The study presents the structure and content of this indicator database and provides suggestions for rural researchers and policymakers on how to use it to build their own well‐being framework. It also provides an overview of each rural well‐being dimension by discussing the key theories, the main inconsistencies, the most relevant studies and authors, the fundamental measurement frameworks, and the indicators used.

Copyright for Computer Programs and Databases

In the digital age, computer programs and databases have emerged as invaluable intellectual properties, driving technological advancements and innovation across industries. As these works become increasingly critical to modern society, ensuring adequate legal protection through copyright law is paramount. This article explores the intricate legal landscape surrounding copyright protection for computer programs and databases. Focusing on the international and national legal frameworks, the article examines the requirements for copyright eligibility, such as originality, fixation, and authorship. It delves into the scope of protection, encompassing source code, object code, user interfaces for computer programs, and the structure, arrangement, and data content of databases. The article also addresses the exceptions and limitations to copyright protection, balancing the rights of creators with the legitimate interests of users and the public. Fair use, reverse engineering, and the creation of backup copies are among the key exceptions discussed. Additionally, the article highlights the challenges of enforcing copyright protection in the digital realm, including digital piracy, transnational infringement, and the complexities surrounding technological protection measures. By providing a comprehensive overview of this intricate legal domain, the article aims to foster a deeper understanding of the critical role copyright plays in incentivizing innovation and creativity in the digital age, while also acknowledging the need for a balanced approach that promotes access and legitimate use of these invaluable works

HeinOnline’s Labor and Employment: The American Worker

HeinOnline offers a core digital library package that contains nearly 3,000 legal journals published in more than 60 different countries, including thousands of Australian, Canadian, and European legal materials and multiple international government publications. This vendor also has several other databases can be attached to this core collection, and “Labor and Employment: The American Worker” is one of them.It contains thousands of books, published from the early twentieth century to the present; hundreds of scholarly articles, ranging from 1904 to the present (with new articles added each month), on various topics, including labor contracts, collective bargaining, employment protections, and the history of the labor movement; and more than 10,000 subject-coded titles. Also available here are current reports on working conditions, legislative histories, Supreme Court case briefs, and a chart of landmark court cases in labor and employment (including the synopsis and full text of each case and an explanation of its significance in both jurisprudence and history), ranging between 1842 and 2018. When these and all the other categories of materials in this database are combined, it contains 10,984 titles, 14,659 volumes, and 5,244,894 pages.As with all databases that provide images of original documents, the readability of the materials here can vary, but thankfully none appear to be illegible. Navigating, rotating, enlarging, and reducing these documents can usually be done without difficulty. Database content can be browsed and/or searched for in numerous ways, all of which are understandable and which generally produce useful results. However, searches by title or description are often the least productive, while those in the full text are far more so. Pricing for this resource is vague, as it is determined by an institution’s location (i.e., in the United States or not), whether it has a law library, and other factors not specified by the vendor. Consortia discounts are also available. The content available here is impressive and will prove valuable to students and researchers of US labor history, especially those looking for case law, legislation, and other government publications on this topic. The licensing agreement for this database is too long, but is not unusual in its provisions, and should provide little cause for concern.

A holistic student-centred guidance framework supports Finnish vocational education and training students in building competence identity

This study deals with competence-based and student-centered Finnish initial vocational education and training (IVET). The main research question is how holistic guidance supports the building of the student’s competence identity in Finnish IVET. The holistic guidance in competence- and work-based vocational education and training is formally implemented when a personal competence development plan (PCDP) is drawn up for each student and informally in various interaction situations in studies, work, and leisure time. The guidance actors supported student’s personal growth, guided learning and provided career guidance. For this study, interviews were carried out with IVET students (n=15) and IVET teachers (n=29). The analysis carried out combined data-based and abductive qualitative content analysis methods. In the analysis results, the different guidance actors were organised into the following five levels of guidance: 1) IVET teachers, tutors, and workplace instructors, 2) IVET study counsellors and special needs teachers, 3) student welfare personnel, 4) leisure time actors and hobby instructors, and 5) employment specialists. Based on the results, a framework was designed for holistic student-centred guidance in Finnish IVET. This framework describes how active student agency and multidisciplinary guidance work can support the building and updating of the student’s competence identity. This study revealed that guidance processes are complex and highlights that many actors are, not only guidance specialists, needed to fulfil the task.

Systematic Approaches for the Encoding of Chemical Groups: A Case Study.

Regulatory authorities aim to organize substances into groups to facilitate prioritization within hazard and risk assessment processes. Often, such chemical groupings are not explicitly defined by structural rules or physicochemical property information. This is largely due to how these groupings are developed, namely, a manual expert curation process, which in turn makes updating and refining groupings, as new substances are evaluated, a practical challenge. Herein, machine learning methods were leveraged to build models that could preliminarily assign substances to predefined groups. A set of 86 groupings containing 2,184 substances as published on the European Chemicals Agency (ECHA) website were mapped to the U.S. Environmental Protection Agency (EPA) Distributed Toxicity Structure Database (DSSTox) content to extract chemical and structural information. Substances were represented using Morgan fingerprints, and two machine learning approaches were used to classify test substances into 56 groups containing at least 10 substances with a structural representation in the data set: k-nearest neighbor (kNN) and random forest (RF), that led to mean 5-fold cross-validation test accuracies (average F1 scores) of 0.781 and 0.853, respectively. With a 9% improvement, the RF classifier was significantly more accurate than KNN (p-value = 0.001). The approach offers promise as a means of the initial profiling of new substances into predefined groups to facilitate prioritization efforts and streamline the assessment of new substances when earlier groupings are available. The algorithm to fit and use these models has been made available in the accompanying repository, thereby enabling both use of the produced models and refitting of these models, as new groupings become available by regulatory authorities or industry.

Evaluating the potential of bioacoustics in avian migration research by citizen science and weather radar observations.

The study of nocturnal bird migration brings observational challenges because of reduced visibility and observability of birds at night. Remote sensing tools, especially radars, have long been the preferred choice of scientists to study nocturnal migrations. A major downside of these remote sensing tools is the lack of species-level information. With technological advances in recent decades and with improved accessibility and affordability of acoustic tools, sound recordings have steeply increased in popularity. In Europe, there is no exhaustive qualitative and quantitative evaluation of the content of such acoustic databases and therefore the value for migration science and migration-related applications, such as bird collision hazard assessments, is mostly unknown. In the present work we compared migration schedules estimated from citizen science data with quantitative temporal occurrence of species in four years of acoustic recordings. Furthermore, we contrasted acoustic recordings with citizen science observations and weather radar data from one spring and one autumn season to assess the qualitative and quantitative yield of acoustic recordings for migration-related research and applications. Migration intensity estimated from weather radar data correlated best at low levels with acoustic records including all species in spring while in autumn passerine species showed stronger correlation than the entire species composition. Our findings identify a minor number of species whose call records may be eligible for applications derived from acoustics. Especially the highly vocal species Song thrush and Redwing showed relatively good correlations with radar and citizen science migration schedules. Most long-distance passerine migrants and many other migrants were not captured by acoustics and an estimated seasonal average of about 50% of nocturnally migrating passerine populations remained undetected. Overall, the ability of acoustic records to act as a proxy of overall migration dynamics is highly dependent on the migration period and species involved.

Application of a machine learning method to model-based library approach for critical dimension measurements using CD-SEM

A model-based library (MBL) method has already been established for the accurate measurement of the critical dimension (CD) of semiconductor linewidth using critical dimension scanning electron microscope (CD-SEM) images. In this work, the MBL method is further investigated by combining CD-SEM image simulation and a neural network algorithm. The secondary electron linescan profiles were first calculated using a Monte Carlo simulation method, enabling us to obtain the dependence of linescan profiles on the selected values of various geometrical parameters (e.g. top CD, sidewall angle and height) for Si and Au trapezoidal line structures. Machine learning methods have then been applied to predict the linescan profiles from a randomly selected training set of the calculated profiles. The predicted results agree very well with the calculated profiles with the standard deviations of 0.1% and 6% for the relative error distributions of Si and Au line structures, respectively. The findings show that the machine learning methods can be practically applied to the MBL method for reducing the library size, accelerating the construction of the MBL database and enriching the content of the available MBL database.

ЦИФРОВІ БАЗИ ДАНИХ ДЛЯ ОСВІТИ І ПРО ОСВІТУ: ДОСВІД ДАНІЇ

The article analyzes the content and specifics of Denmark's open educational electronic databases with the aim of adapting the existing Danish experience to the processes of digitization of the educational sphere in Ukraine. It was noted that these processes cover the sphere of the state policy of digitization of the educational realm (organizational, methodical, management, monitoring, accumulative mechanisms), education management (data storage to reflect the history of changes, monitoring of existing services and education quality control systems, accumulation of statistical data and their prognostic analysis), methodical support of the process of forming the digital competence of the educational process’ subjects (building information profiles, developing digital didactic subsystems, increasing the level of competitiveness of educational institutions as providers), the scientific sphere (digitalization of the open scientific environment, building a space of academic integrity, cooperation between scientists and stakeholders). The common characteristics of the National Electronic Research and Information System URIS and the Danish educational database MED were analyzed. A vision model of the MED database (subjects of educational activity and the content of their activity) was built. The structure of monitoring the quality of education in Denmark, based on open electronic databases, is presented; it includes evaluation of the professional activity of teachers, compliance of educational programs with the social order, effectiveness of state/regional types of certification of graduates, standardization and unification of the evaluation system, mandatory regional analysis of statistical data. It was noted that the identified problems and shortcomings of computer testing of school graduates in the context of assessing the quality of their activities became a significant motivating factor for the creation of the MED database. The conclusion was formulated that the open electronic database makes it possible to build statistically substantiated correlations between the existing social characteristics of teachers and students of all levels and types of schools. The main advantages of the created open MED database were noted: compliance with the global requirements for the assessment of the "added value of the teacher", high frequency of data collection, prognostic nature of conclusions regarding the formation of the state's educational policy.