Open Application Programming Interface Research Articles

New Sustainable Fintech Business Models Created by Open Application Programming Interface Technology: A Case Study of Korea’s Open Banking Application Programming Interface Platform

Fintech facilitates financial inclusion by introducing new sustainable and accessible business models in developing countries. Open banking API technology is used by various fintech businesses in both developing and developed countries, with varying effects on financial markets. It changes the financial market distribution structure by separating financial product manufacturing and distribution and intensifying competition between traditional financial institutions and fintech companies. Fintech companies innovate by using this tool to create new business models. In December 2019, Korea established a standardized “open banking API platform”, sharing an interbank payment network with fintech companies. It has since shown explosive growth, surpassing the trading volume of the UK, the country that introduced open banking APIs for the first time. This study analyzes new business models fintech companies created using this API technology. Based on existing literature, statistics from the platform operator (the Korea Financial Telecommunications and Clearings Institute), and investigations of 30 Korean fintech mobile applications, this study analyzes new fintech business models that provide financial services using this platform. These companies create sustainable business models by combining multiple APIs. Four representative business models (simple funds transfer, simple payment, cross-border remittance, and asset management) are analyzed to reveal how fintech companies create business models with open APIs.

Efficient Extraction of Horizontal and Vertical Alignment Information for Roadways Using Public Data and Open Application Programming Interfaces

An open-source program was developed to extract horizontal and vertical alignment information from roadways using public data and open application programming interfaces. The program employs unsupervised analysis to detect, segment, classify, and measure curves and tangents along an individual route or a network of connected routes. The algorithms used in the horizontal and vertical alignment analyses were described. For vertical alignment, the route was segmented based on the vertical grade profile using a data structure change method. Erratic vertical grade data points at bridges were detected and replaced with estimated values. Two validation cases are provided to demonstrate the function of the program. The first case is an 11.0 km Interstate highway route. The second case is a network of 13 connected routes at a highway interchange. A visual inspection of the results showed that the program was able to detect and measure horizontal and vertical alignment segments with reasonable accuracy. Occasional inaccuracies in the vertical alignment analysis were observed, mainly at short segments near bridges. The program was developed in the R language. The complete source code of the program is publicly accessible via a dedicated GitHub repository.

Exploring and evaluating the development of an open application programming interface (Open API) architecture for the fintech services ecosystem

PurposeThe Open API (application programming interface) architecture will play an important role in promoting future FinTech service applications; however, it involves user data, and the current specialization and progression are less visible. Therefore, an evaluation framework for Open API development in the FinTech service ecosystem is constructed in this study.Design/methodology/approachThis study preliminarily selects the four most important key objects and factors of this ecosystem and conducts expert interviews to revise the evaluation framework. Then, this study uses the fuzzy analytic hierarchy process (FAHP) to evaluate the objects and their factor weights and finally uses the FAHP analysis results to further apply the evaluation based on distance from average solution (EDAS) approach to explore the strategy optimization scenarios.FindingsAccording to the analysis results, the co-creation object and productivity object are the two most significant objects, with weights of 0.275 and 0.272, respectively. The analysis shows that FinTech-related companies expect to increase productivity through co-creation. Finally, the results also indicate that mobile payment is the best Open API application scenario in the FinTech service ecosystem, followed by online banking. These results illustrate strategic and management implications.Originality/valueThis study screens key evaluation criteria with a literature review and expert questionnaire interviews to process quantitative research. It can determine the weights of objectives and criteria to clarify the strength of influence between the objectives and criteria. Next, this study measures the probable performance of Open API applied in various FinTech service ecosystem scenarios.

The relationship between gambling behaviour and gambling-related harm: A data fusion approach using open banking data.

UK-based gambling policymakers have proposed affordability checks starting at monthly losses of £125. The present study combines open banking data with self-reports of the Problem Gambling Severity Index (PGSI) and other relevant information to explore the harm profiles of people who gamble at different levels of electronic gambling behaviour. This was a data fusion study in which participants consented to share their bank data via an open banking application programming interface (API) and who also completed relevant self-report items. Hierarchical hurdle models were used to predict being an at-risk gambler (PGSI > 0) and being a 'higher-risk' gambler (higher PGSI scores among those with non-zero scores) using four specifications of electronic gambling behaviour (net-spend, outgoing expenditure, incoming withdrawals, interaction model combining expenditure and withdrawals), and by adding self-reported data across two additional steps. The study took place in the United Kingdom. Participants were past-year people who gamble (n = 424), recruited via Prolific. Self-report measures were used of gambling-related harm (PGSI), depression [Patient Health Questionnaire 9 (PHQ-9)], age and gender; bank-recorded measures of income and electronic gambling behaviour. Unharmed gamblers had an average monthly gambling net-spend of £16.41, compared with £208.91 among highest-risk gamblers (PGSI ≥ 5). Being an at-risk gambler (PGSI > 0) was predicted significantly by all four types of gambling behaviour throughout all three steps [1.08 ≤ odds ratios (ORs) ≤ 2.92; Ps < 0.001), with only outgoing expenditure being significant in the interaction model (2.26 ≤ ORs ≤ 2.81; Ps < 0.001). Higher PHQ-9 scores also predicted at-risk gambling in steps 2-3 (1.09 ≤ ORs ≤ 1.10; Ps < 0.001), as did lower age (0.95 ≤ ORs ≤ 0.96; Ps < 0.001) and male gender identity in step 3 (2.51 ≤ ORs ≤ 2.95; Ps < 0.001). Being a higher-risk gambler was predicted significantly by gambling behaviour only in the expenditure-only (1.16 ≤ ORs ≤ 1.17; Ps ≤ 0.048) and withdrawal-only (1.08 ≤ ORs ≤ 1.09; Ps ≤ 0.004) models, and was not predicted by income (0.98 ≤ ORs ≤ 1.14; Ps ≥ 0.601), age (0.98 ≤ ORs ≤ 0.99; Ps ≥ 0.143) or male gender identity (1.07 ≤ ORs ≤ 1.15; Ps ≥ 0.472). The UK government's proposed affordability checks for gamblers should rarely affect people who are not experiencing gambling-related harm. At-risk gambling is predicted well by different types of gambling behaviour. Novel insights about gambling can be generated by fusing self-reported and objective data.

Optimal design of steel exoskeleton for the retrofitting of RC buildings via genetic algorithm

In recent decades, steel exoskeletons have gathered significant attention as a seismic retrofitting technique for existing structures. The design methods proposed so far are focused on the identification of the system's overall parameters through simplified models. Although these methodologies provide helpful guidance at the preliminary design stage, they do not consider aspects such as the distribution of the exoskeletons and sizing of their components. To overcome these limitations, an optimization process based on the Genetic Algorithm is proposed in this paper to identify the optimal exoskeleton number and spatial arrangement, and to determine the optimal size of their constituent elements. The algorithm aims to minimize the weight of the retrofit solution while keeping the whole existing structure in the elastic field and ensuring the structural verification of the exoskeleton's elements. The analyses have been conducted using a finite-element code with an Open Application Programming Interface, which allows the models to be handled through automatic routines. The proposed optimization tool has been applied to several case studies, considering two different layouts for the exoskeletons. Finally, the effectiveness of the retrofit method has been demonstrated, and the proposed optimization tool has been able to significantly reduce the weight and cost of the intervention.

Development of a BIM Platform for the Design of Single-Story Steel Structure Factories

Traditional design methods for single-story steel structure factories are characterized by low levels of digitalization and high error rates. To deal with these problems, a building information modeling (BIM) platform for the design of single-story steel structure factories was developed in this paper, which aimed to improve the design process for such structures. Firstly, the components of the factory were categorized, and the Revit API was employed to automate the generation of the BIM model. Load applications and combinations were then established using the Revit API, which relied on a set of predefined parameters. Secondly, this paper proposed the creation of a dedicated database for data exchange between BIM software and finite element analysis software. Additionally, the SAP2000 Open Application Programming Interface (OAPI) was employed for the automated construction and analysis of the SAP2000 structural model. Finally, the innovative use of Dynamo–Revit API hybrid programming allowed for the visualization of internal forces directly within the Revit environment, significantly diminishing the dependency on standalone FEA software. The application results obtained on a project demonstrated that the developed platform markedly improves the efficiency of design single-story steel structure factories and ensures the accuracy of the structural analysis. This confirms that the developed platform can transform the traditional design process by integrating advanced digital tools, thereby providing a novel approach to the design of single-story steel structure factories.

THE URGENCY OF STANDARDIZING THE OPEN APPLICATION PROGRAMMING INTERFACE IN IMPLEMENTATION OF OPEN BANKING FOR CUSTOMER PROTECTION

Open banking with Open Application Programming Interface (open API) technology is an initiative aimed at streamlining the payment system in Indonesia. The open API allows banks to integrate their systems with digital financial service providers (fintech) and bold trade (e-commerce) providers by disclosing customer transaction data. This study investigates the urgency of open API standardization in implementing open banking in Indonesia. This study uses a normative juridical approach to secondary data. The data includes primary, secondary, and tertiary legal materials. In addition, it also uses qualitative normative data analysis methods. It was concluded that before the National Open API Payment Standard (SNAP) stipulation, the process of sharing data between banks and fintech and/or e-commerce still needed to be standardized but was only based on an agreement between the parties. Banking in Indonesia has various open API standards that can affect the protection of customer data. According to the Financial Services Authority Regulation Number 12/POJK.03/2018, the relationship between banks, fintech, and/or e-commerce in providing digital banking services based on agreements between parties needs to be stronger. OJK is indeed present as a supervisory agency. However, the parties will eventually come back to a deal between themselves. Unlike the Regulations of the Financial Services Authority, the Regulations of the Members of the Board of Governors, which form the legal basis for SNAP, provide standards that must be complied with by both service providers and service users. However, implementing SNAP-based open APIs still requires personal data protection regulations.

Analysis of the global level of the banking system readiness for the implementation of the open banking concept.

This research main goal is to give an a vision of current state of Electronic Banking with analysis of the modern state of Open Banking and Open application programming interface (API) initiative. The tectonic shifts in regulation from Central banks and governments digitalisation strategy required from financial institutions to became more technologically ready to comply with licensing. This face banks and financial institutions with a new type of technological challenges which recently wasn't part of regular banks routine and now banks should adopt. Different regions and countries have own regulations and strategies how banking and payments sector should adopt. For example, in Europe each bank must apply a numbers of new software services which was never available for third party companies before. It gives a boost to overall banking and payments software industry to meet the demand of the market. Many other developed countries also have own initiatives for the banking sector similar to PSD2 but with own perspective, timing for implementation and features lists. Standardization and unifications of API’s and messaging between financial organization represented in ISO 20022 and main browsers integrated payments API also a huge step forward for integrators, service providers and software development teams. The results of this research represent current stage of readiness of banking and payment industry to new regulations requirements. Banks and Financial institutions must dramatically change their current business model and initiate completely new departments which makes bank more open from technological point of as never before. World wide size companies and organizations promote new financial messaging standards and API implementation on browser levels. With all of this, banks will become more “digital friendly” and new products and services from third party companies, in collaboration with banks, will fill in the market. Inside this research discovered different aspects of the current problems which banks usually faced during implementation and conclusions what they need to expect when such projects is initiated. The information inside this research gives readers detailed information about the most important aspects of the technical side of implementation and review of new standards and tools.

LAMPPrimerBank, a manually curated database of experimentally validated loop-mediated isothermal amplification primers for detection of respiratory pathogens.

The emergence of coronavirus disease 2019 (COVID-19) has once again affirmed the significant threat of respiratory infections to global public health and the utmost importance of prompt diagnosis in managing and mitigating any pandemic. The nucleic acid amplification test (NAAT) is the primary detection method for most pathogens. Loop-mediated isothermal amplification (LAMP) is a rapid, simple, sensitive, and specific epitome of isothermal NAAT performed using a set of four to six primers. Primer design is a fundamental step in LAMP assays, with several complexities and experimental screening requirements. To address this challenge, an online database is presented here. Its workflow comprises three steps: literature aggregation, data curation, and database and website implementation. LAMPPrimerBank ( https://lampprimerbank.mathematik.uni-marburg.de ) is a manually curated database dedicated to experimentally validated LAMP primers, their peculiarities of assays, and accompanying literature, with a primary emphasis on respiratory pathogens. LAMPPrimerBank, with its user-friendly web interface and an open application programming interface, enables the accelerated and facile exploration, comparison, and exportation of LAMP primer sequences and their respective information from the massively scattered literature. LAMPPrimerBank currently comprises LAMP primers for diagnosing viral, bacterial, and fungal respiratory pathogens. Additionally, to address the challenge of false-positive results generated by nonspecific amplifications, LAMPPrimerBank computationally predicted and visualized the sizes of LAMP products for recorded primer sets in the database. LAMPPrimerBank, as a pioneering database in the rapidly expanding field of isothermal NAAT, endeavors to confront the two challenges of the LAMP: primer design and discrimination of false-positive results.

The use of professional audio external USB sound cards for building acoustics measurements

CSIRO purchased an open application programming interface for hardware with an ethernet connection from a major acoustical instrument manufacturer. Using this interface, the author developed software for fractional octave band filtering with linear and exponential averaging. He then extended this software to automatically measure reverberation time. Fast Fourier Transform and Stepped Sine software was also developed. He then realized that CSIRO also owned two professional audio external USB sound cards. One of these had eight analogue inputs and ten analogue outputs. The other had two analogue inputs and two analogue outputs. Both could supply 48 V phantom power on their analogue inputs. It is possible to purchase phantom power preamplifiers for professional measurement microphones, but CSIRO decided to purchase phantom power to IEPE pre-amplifier adaptors. This enabled the use of professional pre-polarized microphones with IEPE microphone preamplifiers and accelerometers with built-in IEPE preamplifiers. CSIRO also had external USB hardware from another acoustical instrument manufacturer. Upon opening this instrument, it consisted of a professional audio external USB sound card and an IEPE front end for the two analogue input channels. The author decided to produce a version of his software that could be used with these three external USB sound cards.

Reconfigure and evaluate consumer satisfaction for Open API in advancing FinTech

With the rise of FinTech, Open API (application programming interface) is essential in advancing FinTech applications in the future, but its customer satisfaction is a concern. Therefore, this study uses the technology acceptance model (TAM) to reconfigure and evaluate customer satisfaction of Open API in advancing FinTech by applying extended variables. This study initially applies the decision making trial and evaluation laboratory (DEMATEL) approach with the analytic network process (ANP) technique to reconfigure the modified TAM. Finally, we use Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis to evaluate customer satisfaction for examining the acceptance of Open API.The results of DANP point out ‘perceived privacy’ (0.179), ‘customer use intention’ (0.158) and ‘perceived usefulness’ (0.147) are the three most influential variables for Open API in advancing FinTech. Furthermore, VIKOR analysis indicates online security or cryptocurrency trading (0.536) performs best in which Open API can satisfy customers in advancing FinTech and online banking (0.438) has the most space for improvement. This study also indicates that privacy protection plays a very important role in consumer satisfaction of Open API. The influences of the variables demonstrate that Open API compared to conventional APIs, is more convenient and relatively beneficial in advancing FinTech.

Open Geospatial Data Integration in Game Engine for Urban Digital Twin Applications

Increasing interest has recently been shown towards the digital twins of cities. These urban digital twins utilize 3D city models together with other data sources, such as open data, which can be accessed, e.g., through application programming interfaces (APIs). A large amount of open geospatial data is already available through various open data portals and APIs, such as REST and MQTT. Game engines, on the other hand, have been seen as highly potential platforms for urban digital twins, with recent development increasing the useability of geospatial data in game engines. This study explores the possibilities of game engines for urban digital twins by integrating and visualizing API-based open geospatial datasets with a 3D city model data set in a game engine environment. Three open data integration approaches are demonstrated, and the performance of these approaches is tested for urban digital twins. Based on the results, modern game engines offer a great platform for creating urban digital twin applications; however, some problems and limitations must be overcome before the use of geospatial data in game engines becomes feasible on a larger scale.

Comparing different search methods for the open access journal recommendation tool B!SON

Finding a suitable open access journal to publish academic work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of predatory publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. A systematic requirements analysis was conducted in the form of a survey. The developed tool suggests open access journals based on title, abstract and references provided by the user. The recommendations are built on open data, publisher-independent and work across domains and languages. Transparency is provided by its open source nature, an open application programming interface (API) and by specifying which matches the shown recommendations are based on. The recommendation quality has been evaluated using two different evaluation techniques, including several new recommendation methods. We were able to improve the results from our previous paper with a pre-trained transformer model. The beta version of the tool received positive feedback from the community and in several test sessions. We developed a recommendation system for open access journals to help researchers find a suitable journal. The open tool has been extensively tested, and we found possible improvements for our current recommendation technique. Development by two German academic libraries ensures the longevity and sustainability of the system.

Automated minimum-weight sizing design framework for tall self-standing modular buildings subjected to multiple performance constraints under static and dynamic wind loads

In recent decades, the shortage of affordable housing has become an endemic issue in many cities worldwide due to the ongoing urban population growth. Against this backdrop, volumetric steel modular building systems (MBSs) are becoming an increasingly compelling solution to the above challenge owing to their rapid construction speed and reduced upfront costs. Notwithstanding their success in low- to mid-rise projects, these assembled structures generally rely on a separate lateral load-resisting system (LLRS) for lateral stiffness and resistance to increased wind loads as the building altitude increases. However, additional LLRSs require on-site construction, thereby compromising the productivity boost offered by the MBSs. To this end, this paper proposes a novel optimisation-driven sizing design framework for tall self-standing modular buildings subjected to concurrent drift, floor acceleration, and member strength constraints under static and dynamic wind loads. A computationally efficient solution strategy is devised to facilitate a meaningful sizing solution by decomposing the constrained discrete sizing problem into a convex serviceability limit stage (SLS) and a non-convex ultimate limit stage (ULS), which can be then solved using preferred local and global optimisation methods, separately. The framework is implemented by integrating SAP2000 (for structural analysis) and MATLAB (for optimisation) through SAP2000′s open Application Programming Interface (API), and demonstrated using a 15-storey self-standing steel modular building exposed to three different levels of wind intensity. A comprehensive performance assessment is conducted on the optimally designed case-study building to investigate its elastic instability behaviour, geometric nonlinear effects on wind-induced response, and impacts of global sway imperfections on member utilisation ratios under wind effects. It is concluded that tall self-standing modular buildings can be achieved economically using ordinary corner-supported modules without ad hoc structural provisions, while consuming steel at similar rates to conventional building structural systems. Furthermore, the proposed sizing framework and solution strategy have proven to be useful design tools for reconciling the structural resilience and material efficiency in wind-sensitive self-standing modular buildings.

Thai Commercial Banks on Twitter

Twitter is a social media (SM) platform that rapidly generates electronic word of mouth (e-WOM). Marketer-generated content (MGC) is controllable and could enhance the positive e-WOM. Hence, in this study, the author examined the characteristics of MGC and reactions from followers based on Thai banks' Twitter accounts. The author collected a total of 10,000 tweets from nine banks in Thailand—both high- and low-performing banks. The author conducted research with natural language processing (NLP) to uncover intents using an open application programming interface (API). The author used three data-mining techniques—association, clustering, and classification. The Twitter strategies of banks with high and low performances are quite similar. The sentiment is the intent type that dominates Thai banks' intent strategies. Several intents could be combined to draw e-WOM in terms of favorites (FAV) and retweets (RT). Six intent patterns (clusters) were extracted. Some of these clusters are classifiers for FAV and non-FAV tweets. This study guides the application of data mining in business research and suggests MGC strategies for marketers.

ANN-based optimization framework for the design of wind load resisting system of tall buildings

Conventional design methodology for tall buildings is a time-consuming and repetitive trial-and-error procedure with a limited probability of yielding an optimal solution that satisfies architectural, structural and serviceability requirements. Tall buildings are typically slender structures and mainly depend on lateral load resisting systems (LLRS) (e.g., shear walls, cores, and bracing systems) to withstand the lateral load of earthquakes and wind events, where a minor change in their layout, size, or shape will affect the cost tremendously. Consequently, an automated layout optimization procedure will result in a more economic and sustainable design. This paper develops a novel structure-wind optimization framework (SWOF) to find the optimal shear wall layout of tall buildings subjected to wind loads. SWOF is considered a genetic algorithmbased framework that uses an Artificial Neural Network (ANN) surrogate model to evaluate its constraints and objective function. These surrogate models rely on a training dataset prepared using the Finite Element Method (FEM), which has been created using an open application program interface (OAPI) MATLAB code. An optimization problem; is presented to show SWOF's efficiency. SWOF showed significant capabilities in recognizing load direction, critical load cases and inertia concepts without explicitly defining them through the developed code.

Teaching-learning-based optimization of unbraced steel frames with semi-rigid connections and column bases

The teaching-learning optimization (TLBO) technique is applied to unbraced steel frames with semi-rigid beam-to-column connections and semi-rigid column-to-base connections. The algorithm for design produces optimized steel frames by choosing appropriate sections from a set of standard steel sections. These standard steel sections, including wide-flange profiles (W), are provided by the American Institute of Steel Construction (AISC). The first example is subjected to the displacement, inter-story drift, and stress constraints of AISC-Load and Resistance Factor Design (LRFD) regulations. In addition, the displacement and stress limitations of the AISC-Allowable Stress Design (ASD) standard and the geometric (size) requirements are implemented in the last two examples. In finite element analysis, optimal designs of three alternative unbraced frames are performed with and without semi-rigid beam-to-column and column-to-base plate connections. All optimization techniques are encoded in the high-level programming language C# version 17.4.4 to integrate with SAP2000 version 22's Open Application Programming Interface (OAPI). The analysis results indicate that the rigidity of connections is determining parameter in the weight optimization of unbraced steel frames.

Evaluating robustness of a generalized linear model when applied to electronic health record data accessed using an Open API.

The Integrated Clinical and Environmental Exposures Service (ICEES) provides open regulatory-compliant access to clinical data, including electronic health record data, that have been integrated with environmental exposures data. While ICEES has been validated in the context of an asthma use case and several other use cases, the regulatory constraints on the ICEES open application programming interface (OpenAPI) result in data loss when using the service for multivariate analysis. In this study, we investigated the robustness of the ICEES OpenAPI through a comparative analysis, in which we applied a generalized linear model (GLM) to the OpenAPI data and the constraint-free source data to examine factors predictive of asthma exacerbations. Consistent with previous studies, we found that the main predictors identified by both analyses were sex, prednisone, race, obesity, and airborne particulate exposure. Comparison of GLM model fit revealed that data loss impacts model quality, but only with select interaction terms. We conclude that the ICEES OpenAPI supports multivariate analysis, albeit with potential data loss that users should be aware of.

Integration of Excel VBA with professional software for the structural analysis and design of civil structures

AbstractA feasible combined approach between structural analysis program (SAP) 2000 and Excel software is proposed in this article to develop customized numerical tools for the analysis of civil engineering structures. For such scope, the Open Application Programming Interface from SAP 2000 software is linked to the Visual Basic for Application (VBA) environment embedded within Excel. Three computer applications resembling industrial situations related to size optimization of trusses, soil−structure interaction in buildings, and automatic design of reinforced concrete slabs are presented. As the tools are parameterized, students can observe the effects of the various parameters on the output response of the structures because geometry, loading, and material properties can be easily varied. As the main concern is the educational aspect, the novelty of this research is to present the proposed combined approach in a stepwise manner with explained codes. The source codes of the developed tools are made freely available so that the applicants can modify them according to their priorities. The tools present a friendly user interface that made them attractive to use in daily design tasks at the office, but certainly, they are the result of the integration of student knowledge as part of a bachelor's dissertation in an undergraduate civil engineering educational program. The tools have been preliminarily introduced into a reinforced concrete course at the Federal University of Rio Grande do Sul (Brazil), searching for a better understanding of theoretical concepts, while integrating technology into the classroom and reducing time constraints as new configurations for the studied structures can be easily explored during class.

Using open infrastructures for alternative quality assessment of research outputs

Decision-makers are not able to follow all the changes in the open science (OS) on the policy level as fast as needed. This affects the way how research outputs are assessed. Due to this, not all research outputs are recognised, and there are no mechanisms to trace and appraise all outputs. This paper presents open infrastructures and supporting methods which are capable of overcoming these deficiencies. The Scopus and Web of Science citation indexes have a significant impact on the quality assessment of research outputs, especially when it comes to research promotion and career development. At the same time, researchers produce scientific outputs that cannot be assessed using traditional approaches (Pravilnik o sticanju istraživačkih i naučnih zvanja, 2020).Open infrastructures can support research communities by providing methods which are verifiable and available for integration with institutional infrastructures (such as repositories and CRIS systems). There are also some services that do not fall into the category of open infrastructure but support the concept by providing technical solutions that can be open access. Also, there is a tendency to make open infrastructures as compliant with OS principles as possible. Some of these infrastructures implement other closely related principles such as the FAIR data principles (GO FAIR initiative, 2022). When an institutional infrastructure adopts these principles and integrates services provided by open infrastructures, then benefits are seen by both researches and decision-makers. Dimensions is an alternative to and more open and inclusive than a traditional citation database. Also, Dimensions is integrated with other infrastructures that embrace the concept of openness (Dimensions, 2019). Thanks to functionalities available through various open application programming interfaces (APIs), Dimensions has played an important part in technical adoption of OS principles in Serbia.Alternative metrics like Altmetric could serve as another solution (Altmetric, 2018). Like Dimensons, Altmetric is not an open infrastructure, but it contributes to open infrastructures through open APIs that can track the impact of research outputs across the Internet. The main focus is on tracking research papers on social media (Facebook, Twitter) and multimedia platforms (YouTube) or their mentions in Internet communities. An important issue for each country is how to assess research outputs in humanities. Knowing that research outputs in this area focus mainly on locally relevant topics, it is difficult to track the impact of such results by relying on traditional citation databases.Unlike Dimensions and Altmetric, OpenCitations is an open infrastructure which fully embraces the concept of OS and is compliant with the FAIR data principles inasmuch as the data it collects are findable, accessible, interoperable, and re-usable. Furthermore, OpenCitations has adopted the Principles of Open Scholarly Infrastructure (POSI) (Bilder, Lin and Neylon, 2020) and its infrastructure has been upgraded with a system that provides persistent identifiers (PIDs) (Peroni, Shotton, 2019). All these solutions are mostly dealing with citations. However, there are research outputs like peerreview reports and editorial work that cannot be assessed only by the number of citations and require other metrics. Publons is far from an open infrastructure but at least provides some open access services for researchers. More relevant in this context is the recently launched OpenAlex, an open infrastructure that can serve as a search engine, research output monitor, and assessment tool. OpenAlex aggregates data from sources like Crossref and ORCID and seeks to present data in a standardised way