XML Files Research Articles

Capability knowledge base query to allocate process resources for master recipe formulation

Abstract We present a method for matching the required capabilities of general recipes with available resources to formulate master recipes. Process elements extracted from BatchML XML files are used to decompose the required capabilities and match them with the capabilities offered by components at distinct levels. A capability OWL ontology with properties aids in querying and matching capabilities with resources, enabling validation via description logic (DL) queries post-inference and integration into the master recipe. DL queries and matching within a knowledge base demonstrate AI-based knowledge processing for production systems.

Development and implementation of a method for checking the integrity of the design of an object-oriented system

Creating modern software products is a complex and long process consisting of many parts. To achieve quality, it is necessary to carry out various measures for testing and verifying software at all stages of development. This article discusses the software design stage, which is integral and one of the most important. In most software development life cycle (SDLC) models, this stage is one of the first, so design mistakes will lead to problems in all subsequent stages. Thus, due to the high cost of error, it is very important to check the integrity of the developed design at the design stage. The article examines the problem of finding contradictions in object-oriented design. The authors present a set of contradictions that can arise in such a design and aim to develop methods and algorithms for detecting and searching for these contradictions in order to improve the quality of the design, as well as writing software that will implement these algorithms and methods. The program "diagrams.net" was chosen as a tool for creating object-oriented design, the main useful feature of which is the ability to present the created diagrams in the form of an XML file in the popular drawio format. The authors of the study propose a method for parsing the XML file of the diagram and presenting it as a set of objects, such as dependency arrows, classes, methods, etc. These objects must interact according to the established rules.The violation of these rules is a contradiction of the object-oriented design. As a result of the study, a method of finding contradictions was presented and implemented in the Java programming language.

Research on Parameter Correction of Distribution Network Model Based on CIM Model and Measurement Data

The construction of an energy distribution network can improve the system’s ability to absorb new energy, and its stable and efficient operation has become more and more important. The security and stability analysis of a distribution network needs accurate distribution network model parameters as support. At present, the installation of PMU equipment in China’s distribution network synchronous phase angle measurement unit is limited, which brings challenges to the parameter correction of the distribution network. In this paper, an automatic correction algorithm of distribution network parameters based on the CIM model and measurement data is proposed for the distribution network system without PMU. Firstly, the distribution network topology construction technology based on XML files and key fields of the distribution network is proposed, and the non/small impedance devices (such as switches) are merged and reduced. The breadth-first traversal algorithm is used to verify the connectivity of the constructed topology. Then, based on the topology construction and the least squares method, an iterative parameter correction technique is constructed. Finally, the accuracy and effectiveness of the proposed algorithm are verified in a standard IEEE 33-bus system distribution network and an example of the China Southern Power Grid. The topology connections constructed based on the CIM model have significantly enhanced the efficiency of parameter correction.

Enhancing XML Data Parsing and Querying Performance on Multi-Core Architectures

With the increasing number of computer applications, the eXtensible Markup Language (XML) has become ubiquitous and is being utilized broadly on the web for exchanging and storing information. XML files of large size take more space because of redundancy, and when parsed on machines degrade the execution. This paper proposes a novel approach aimed at enhancing the performance of parsing XML files. The proposed approach initially divides the XML file into several parts concurrently and then processes it to ensure well-formedness. Each part is subsequently encoded to save memory space, efficient parsing, and querying. Multiple parse trees are then generated in parallel in the next phase, prior to querying required data from the parse trees. The parallel parsing and efficient querying make our approach perform better than other parsing approaches. The results obtained on processing XML files of diverse sizes show an increase in performance by 22.50%, 19.41%, and 30.25% over the well-known DOM, SAX, and StAX parsing approaches, respectively.

Automated Mapping Tool from Moise+ to Colored Petri Nets

The demand for systems incorporating artificial intelligence, such as multi-agent systems, is continually increasing. Simultaneously, there is a growing need for developing tools to support this field, ensuring better fault tolerance within projects. This is particularly crucial given that these systems possess characteristics that render them non-deterministic, thereby amplifying the challenge of conducting tests. To address this challenge, a mapping tool has been developed. This tool automatically generates a graphical model, facilitating the identification of test paths for a given multi-agent system. It operates by taking an XML file from Moise+, an organizational model for multi-agent systems, and translates it into a colored Petri net. The resulting mapping serves as a foundation for generating test cases essential for validating the Moise+ model, guiding system testing. Automation streamlines the process, enhancing speed, and eliminating the potential for human error.

Building a sharable literature collection to advance the science and practice of implementation facilitation.

Implementation science seeks to produce generalizable knowledge on strategies that promote the adoption and sustained use of evidence-based innovations. Literature reviews on specific implementation strategies can help us understand how they are conceptualized and applied, synthesize findings, and identify knowledge gaps. Although rigorous literature reviews can advance scientific knowledge and facilitate theory development, they are time-consuming and costly to produce. Improving the efficiency of literature review processes and reducing redundancy of effort is especially important for this rapidly developing field. We sought to amass relevant literature on one increasingly used evidence-based strategy, implementation facilitation (IF), as a publicly available resource. We conducted a rigorous systematic search of PubMed, CINAHL, and Web of Science citation databases for peer-reviewed, English-language articles with "facilitation" and a combination of other terms published from January 1996 to December 2021. We searched bibliographies of articles published from 1996 to 2015 and identified articles during the full text review that reported on the same study. Two authors screened 3,168 abstracts. After establishing inter-rater reliability, they individually conducted full-text review of 786 relevant articles. A multidisciplinary team of investigators provided recommendations for preparing and disseminating the literature collection. The literature collection is comprised of 510 articles. It includes 277 empirical studies of IF and 77 other articles, including conceptual/theoretical articles, literature reviews, debate papers and descriptions of large-scale clinical initiatives. Over half of the articles were published between 2017 and 2021. The collection is publicly available as an Excel file and as an xml file that can be imported into reference management software. We created a publicly accessible collection of literature about the application of IF to implement evidence-based innovations in healthcare. The comprehensiveness of this collection has the potential to maximize efficiency and minimize redundancy in scientific inquiry about this strategy. Scientists and practitioners can use the collection to more rapidly identify developments in the application of IF and to investigate a wide range of compelling questions on its use within and across different healthcare disciplines/settings, countries, and payer systems. We offer several examples of how this collection has already been used.

Lung Nodule Detection Interface Design and Development From Computerized Tomography Images

Lung cancer is one of the leading diseases that cause death in the world. Early diagnosis of lung cancer is as important as its treatment. Therefore, we propose the LinkNet architecture, which is a deep learning model that will detect the location and size of nodules from the lung tomography image. The study was conducted with 110 patients and 343 nodules with nodules detected in Lung Computed Tomography (CT) Images. In the study, no public dataset was used and tomography images were obtained from the hospital. In the pre-processing stage, thresholding is made according to the lung Hounsfield Unit (HU) threshold value with the Otsu method and the lung is segmented. The XML (Extensible Markup Language) files of ROIs(Region of Interest) of the nodules previously marked by the radiologist are extracted and converted into images. Using template nodules trained with LinkNet and U-Net architectures, comparison and success percentage tables for 16 different architectures were presented. Using LinkNet, the model achieved an intersection of union (IoU) score of 69% for valid and an IoU score of 94% for the train. 274 nodule data were used in the train section and 69 nodule data were used in the validation section. Experimental results show that nodules that may be overlooked by a radiologist can be detected with CAD (Computer- Aided Design) performed and will be useful in the diagnosis of lung cancer.

177 Placing Participant Experiences at the Center of Improving Research by Empowering the Participant Voice

OBJECTIVES/GOALS: Empowering the Participant Voice (EPV) is a 6-CTSA Rockefeller-led collaboration to developcustom REDCap infrastructure to collect participant feedback using the validated Research Participant Perception Survey (RPPS), demonstrate its value in use cases, and disseminate it for broad adoption. METHODS/STUDY POPULATION: The EPV team developed data and survey implementation standards, and specifications for the dashboard and multi-lingual RPPS/REDCap project XML file. The VUMC built a custom At-a-Glance Dashboard external module that displays Top Box scores (percent best answer), with conditional formatting to aid analysis, and response/completion rates. Results populate site dashboards, and aggregate to a multi-site dashboard for benchmarking. Results can be filtered by participant/study characteristics. Sites developed individual use cases, leveraging local infrastructure, initiatives and stakeholder input. Infrastructure and guides were designed for dissemination through public websites. RESULTS/ANTICIPATED RESULTS: Five sites sent 23,797surveys via email, patient portal or SMS. 4,133 (19%) participants diverse in age, race, and ethnicity, returned responses. Sites analyzed their data and acted on selected findings, improving recruitment, communication and feeling valued. Aggregate scores for feeling listened to and respected were hight (>90%%); scores for feeling prepared by the consent process were lower (57-77%) and require action. Some groups experiences were better than others. Sites differed significantly in some scores. Dissemination of EPV is underway. Infrastructure and guides are downloadable free of charge, with advice from the EPV team. In 2023, a sixth site began piloting a lower literacy survey version and syncing data to the consortium dashboard. DISCUSSION/SIGNIFICANCE: The EPV RPPS/REDCap infrastructure enabled sites to collect participant feedback, identify actionable findings and benchmark with peers. Stakeholders and collaborators designed and tested local initiatives to increase responses and diversity, address disparities, and discover better practices.

Генерация файлов формата Moodle XML на основе данных сбалансированного лингвистического корпуса

The aim of the proposed research is to develop an algorithm for generating educational (linguodidactic) content for popular learning management systems based on corpus data. The scientific novelty lies in the fact that for the first time, a linguodidactic component is added to the original author’s concept of the method for generating a balanced linguistic corpus, implemented on the general principles of maximum automation and universality of application. During the research, the structures of LMS Moodle backup files were studied, a software module was developed for converting data from the author’s balanced linguistic corpus with morphological markup into XML files, which were imported and tested for integrity and correctness in terms of solving the posed linguodidactic task. As a result, it was proved that the used linguistic corpus has a high linguodidactic potential, the created algorithm shows good results, in this case, for generating test or training tasks in German, and can be expanded to material from other languages, the support of which is provided by the software tool – the corpus generator.

Abstract B004: PISCA-box: A user-friendly interface for Phylogenetic Inference using Somatic Chromosomal Alterations (PISCA)

Abstract PISCA, originally introduced by Martinez et al. in 2018, represents a pivotal Bayesian phylogenetics tool for the modeling of tumor evolution using multi-region somatic chromosomal alteration (SCA) data. PISCA takes allele-specific copy number data, typically obtained from deep genome sequencing or SNP arrays, or absolute copy number data from low-pass genome sequencing methodologies. It extends the classic BEAST1 framework and inherits a rich repertoire of evolutionary models. Importantly, PISCA leverages longitudinal sampling to estimate SCA mutational clock rates, either employing strict clock models, where mutation rates remain constant throughout the evolutionary tree, or relaxed clocks, which allow each branch or subtree to possess its distinct mutation rate. This nuanced approach empowers PISCA to account for the heterogeneous rates of mutations, a pivotal consideration in understanding tumor evolution dynamics. However, PISCA has historically posed a formidable entry barrier for wider community adoption due to platform and Java dependencies for installation, as well as the need for manual or custom-scripted XML file generation. Here we showcase PISCA-box, a user-friendly interface designed to streamline the generation and testing of XML files. Our PISCA-box Docker image works on any desktop machine to create a locally hosted webpage, where users can input SCA data, sampling dates, select clock and demographic models, and set priors for key parameters - similar to the BEAST XML generator, BEAUTi. The Docker or Singularity installation can then be used for longer analyses using high-performance computing resources. To demonstrate its practical utility, we present novel colorectal cancer data. First, we examine data from a patient with a long-standing history of inflammatory bowel disorder (IBD), a known high-risk factor for colorectal cancer. This patient had undergone surveillance colonoscopies for many years, which provided 38 samples, and subsequently an additional 118 samples were collected from a total colectomy. All were analyzed with low-coverage whole genome sequencing. We find some samples from surveillance and colectomy form lineages with overlapping copy number events, that we used to construct a phylogeny, finding a cancer-adjacent clade that appears to evolve rapidly. A second dataset of multi-region samples from a cohort of exceptional survivors of oligometastatic colorectal cancer who lived >60 months from metastatic diagnosis with biopsies/resections across 3-10 time points is examined and temporal models are used to estimate the ages of metastatic clades. PISCA therefore harnesses the power of longitudinal SCA data to enable a comprehensive study of SCA dynamics. We are currently expanding this framework to include fluctuating methylation clocks which PISCA-box will soon include. By providing this accessible tool, we enable researchers to readily apply Bayesian phylogenetics to real-world clinical datasets to better understand tumor evolution. Citation Format: Heather E. Grant, Rachel Alcraft, Pablo Bousquets-Muñoz, Calum Gabbutt, Alison Berner, Mehmet Yalchin, Carlo C. Maley, Trevor A. Graham, Diego Mallo. PISCA-box: A user-friendly interface for Phylogenetic Inference using Somatic Chromosomal Alterations (PISCA) [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B004.

Parsing of Research Documents into XML Using Formal Grammars

Automatic information extraction of content and style format in paged documents is challenging. It requires the conversion of the original document into a granular level of details for which every document section and content is identifiable. This functionality or tool does not exist for any academic research document yet. In this paper, we present an automated process of parsing research paper documents into XML files using a formal method approach of context-free grammars (CFGs) and regular expressions (REGEXs) definable of a standard template. We created a tool for the algorithms to parse these documents into tree-like structures organized as XML files named research_XML (RX) parser. The RX tool performed the extraction of syntactic structure and semantic information of the document’s contents into XML files. These XML output files are lightweight, analyzable, query-able, and web interoperable. The RX tool has a success rate of 91% when evaluated on fifty varying research documents of 160 average pages and 8,004 total pages. The tool and test data are accessible on GitHub repo. The novelty of our process is specific to applying formal techniques for information extraction in structured multipaged documents and academic research documents thus advancing the research in automatic information extraction.

Decoupled optimal control of 3D biped for human voluntary motion.

The sit-to-stand (STS) model from a biomechanical point of view is an enormously important subject, with motor controls simulating human intended behavior. Physiological motion-based biomechanical research is important for designing whole-body prosthetics and understanding physical disabilities. The control strategies for biomechanical models can effectively synergize with the central nervous system (CNS) to facilitate the desired movements of individuals with neurological disabilities. In this study, we present our novel 3D biped model by decoupling it into healthy and neurologically deficient joints. The developed 8-segment model (i.e., 2× feet, 2× shanks, 2× thighs, 1× pelvic, and 1× Head Arm Torso (HAT) segment) with 10 joints is decoupled into 6 healthy joints and 4 deficient joints. This decoupling mimics stroke patients or subjects with neuromuscular deficiency. This novel decoupling establishes through asymmetrical torques in frontal and sagittal plane joints on a bipedal design with one foot fixed and the other a sliding tilt joint. In this design, two decoupled controllers collaborate to stabilize the nonlinear model for biped STS transfer. Utilizing the xml files from SOLIDWORKS, the model is linearized in SIMSCAPE / SIMULINK. We further imply the Linear Quadratic Regulator (LQR) optimal controller design in MATLAB / SIMULINK for torques in both the sagittal and frontal planes, respectively, for six healthy and four deficient joints. We also comprehend the forward thrust velocity controls to pragmatically model the STS of stroke patients. This decoupling enhanced the overall stability of the system and simulated more relevant angular and velocity profiles for neurologically deficient substances.

ИССЛЕДОВАНИЕ ВОПРОСА СВЯЗИ ИНФОРМАЦИОННОЙ МОДЕЛИ СТРОИТЕЛЬСТВА ОБЪЕКТА (BIM) И СМЕТНОЙ СТОИМОСТИ ОБЪЕКТА

An information model of a construction project (BIM-model) is an integral part of the project at the design and construction stages now days. The BIM-model contains parametric data about the object, the resources used and serves as a basis for making, as a rule, technological decisions. There is a need to transparently indicate the connection between the BIM model and the cost of the object, which is a key indicator when making management decisions. The information model is implemented in the IFC format, and estimating programs do not support this option for data transfer. In particular, the transfer of estimate data occurs using XML files. This discrepancy requires revision at the conceptual and software levels, including organizing a common data environment. The purpose of the work. The article is related to identifying the connection between the properties of the information model of the object and the estimate properties that should be included in the model parameters at all stages of the object's life cycle. Materials and methods. In the process of writing the article, general scientific methods and research techniques were used: descriptive method, comparison method, analogy method, generalization method, and systems approach. In preparing the work, the data of regulatory and methodological documents in the field of information modeling in the Russian Federation and international standards for the content and filling of the information model of the object were used. For testing, design and estimate documentation for the repair of an element of an administrative building was used. Results. A feature of the work is the development of the filling of the BIM-model with estimate properties depending on the level of development of the model (LOD), taking into account the requirements of regulatory and methodological documents in the field of construction and international standards. A method is proposed for the formation of a set of estimate properties, which can be further adapted to the needs of the customer depending on the type of construction, stage of the project life cycle and estimate standards. Conclusion. The results of the work can be used to form methodological documents on the organization of the general data environment at the stages of the life cycle of a capital facility.

Computational Analysis of Printed Arabic Text Database for Natural Language Processing

A frequency dictionary of printed Arabic text is essential for natural language processing. It includes 1,251 XML files of Arabic documents collected from ten newspapers and magazines from different countries and created as the PATD database. A total of 2,344 articles were created with various structures: open vocabulary, multi-font, multi-size, and multi-style text. From these articles, 1,102,078 tokens, 19,926 sentences, and 1,000,000 words were extracted. This dictionary provides detailed information for each word, including English equivalents, usage statistics, usage distribution, and the most widely used terms. A thematic vocabulary list of the top words on various topics is also provided. This frequency dictionary is a useful resource of modern Arabic vocabulary for various specialists, students, and learners. The frequency dictionary is freely available to interested researchers on the webpage.

AN IMPROVED INDEXING METHOD FOR QUERYING BIG XML FILES

The exponential growth of bioinformatics in the healthcare domain has revolutionized our understanding of DNA, proteins, and other biomolecular entities. This remarkable progress has generated an overwhelming volume of data, necessitating big data technologies for efficient storage and indexing. While big data technologies like Hadoop offer substantial support for big XML file storage, the challenges of indexing data sizes and XPath query performance persist. To enhance the efficiency of XPath queries and address the data size problem, a novel approach that is derived from the spatial indexing method of the R-tre family. The proposed method is to modify the structure of leaf nodes in the indexing tree to preserve XML-sibling connections. Then, new algorithms for constructing the new tree structure and processing sibling queries better are introduced. Experimental results demonstrate the superior efficiency of sibling XPath queries with reduced data sizes for indexing, while other XPath queries exhibit notable performance improvements. This research contributes to the development of more effective indexing methods for managing and querying large XML datasets in bioinformatics applications, ultimately advancing biomedical research and healthcare initiatives.

Creating JATS XML from DOCX

JATS XML (Journal Article Tag Suite) is an adopted XML format used for publishing scientific and scholarly content. It is an alternative way of publishing contemporary scientific and professional journals, which has multiple advantages over traditional publishing methods.One of the key advantages of JATS XML is its ability to enhance the discoverability and accessibility of journal articles. This is achieved through the use of metadata tags, which provide a standardized way of describing content and make it easier for search engines to index and retrieve articles. Additionally, the use of JATS XML allows for better preservation of content and ensures that articles are machine-readable and easily integrated with other scholarly resources.Another significant advantage of JATS XML is its ability to facilitate publishing workflows, but unfortunately although it should be the case, currently that ability is not fully realized. Despite providing a standardized structure for content, which theoretically makes it easier for publishers to manage the publication process, some challenges still exist in the practical implementation of JATS XML. Creating JATS XML requires a lot of time if the editor writes XML from scratch or significant financial resources that need to be invested in purchasing professional tools or outsourcing this work. There are almost no free and effective tools for creating complete and correct JATS XML.The team from SRCE – University of Zagreb, University Computing Centre behind the HRČAK portal decided to adapt the universal document converter called Pandoc primarily for editors and publishers in HRČAK, but with the intention that in the future it can also be used by the wider scientific and professional community. At this workshop, we will introduce the process of creating JATS XML as part of HRČAK which will allow journal editors and publishers to create JATS XML more easily. The goal of is to allow users to create complete and correct JATS XML files for their journals through a simple interface without any prior knowledge of XML.

Web Based Intrusion Detection System for SQLIA

SQL Injection Attack (SQLIA) refers to an injection attack wherein an attacker can execute malicious SQL statements that control a web application’s database server. By leveraging SQL Injection vulnerability, given the right circumstances, an attacker can use it to bypass a web application’s authentication and authorization mechanisms and retrieve the contents of an entire database. SQL Injection can also be used to add, modify and delete records in a database, affecting data integrity. The main idea of our work is to allow developers the freedom to write and execute code without having to worry about these attacks. In this paper we propose a Web Based Intrusion Detection System for SQLIA to extract a SQL query connecting to database from a PHP file. The structure of the query under observation will be converted to XML file and compared against the legitimate queries stored in the XML file using association rule mining thus minimizing attacks. WEBIDS is expected to reduce the time and manual effort as it only focuses on fragments that are vulnerable for attacks. Key Words: XML Rule Mining, PHP, SQL injection,

An Actor-Oriented and Architecture-Driven Approach for Spatially Explicit Agent-Based Modeling

Nowadays, there is an increasing need to rapidly build more realistic models to solve environmental problems in an interdisciplinary context. In particular, agent-based and spatial modeling have proven to be useful for understanding land use and land cover change processes. Both approaches include simulation platforms often used in several research domains to develop models explaining and analyzing complex phenomena. Domain experts generally use an ad hoc approach for model development, which relies on a code-and-fix life cycle, going from a prototype model through progressive refinement. This adaptive approach does not capture systematically actors’ knowledge and their interactions with the environment. The development and maintenance of resulting models become cumbersome and time-consuming. In this article, we propose an actor and architecture-driven approach that relies on relevant existing methods and satisfies the needs of spatially explicit agent-based modeling and implementation. We have designed an Agent Global Experiment framework incorporating a meta-model built from actor, agent architecture, and spatial concepts to produce an initial model from specifications provided by domain experts and system analysts. An engine is built as a tool to support model transformation. Domain knowledge including spatial specifications is summarized in a class diagram which is later transformed into the agent-based model. Finally, the XML file representing the model produced is used as input in the transformation process leading to code. This approach is illustrated on a hunting and population dynamic model to generate a running code for GAMA, an agent-based and spatially explicit simulation platform.

Automated estimation of road facilities within 5D modeling paradigm

The paper is aimed at considering the possibility of automated estimation of road facilities on the basis of data obtained from the bill of quantities at the design or construction stages. The authors accepted Tomita Parser as a for extracting facts and parameters from the bill of quantities. Further comparison of quantities of work with Federal Unit Rates and State Itemized Cost Estimate Standards is carried out by the program algorithm developed by the authors for calculating and estimating costs. The presented manual method for creating a database compiled on the basis of comparing the bill of quantities with the above federal regulations may be considered reliable. However, large data sets require machine learning technologies to be applied. The program algorithm considers many estimation settings, in particular, assigning the index to construction and installation works, the total coefficient to the positions by types of work (for example, performance of work on one half of the roadway), etc. The finished estimate is generated in a *.xml file and can be further integrated into the road information model and converted into *.gge format for using by the Federal autonomous institution “Main Department of State Expertise”. The results showed that all key parameters from the bill of quantities were taken into account by the program algorithm. The generated estimate considered all coefficients and prices to accurately reflect the cost of the works described in this bill.

Pre-Publication Data Linking in Taxonomy and Biodiversity: The ARPHA and Metotaxa-Metostem Publishing Systems

The traditional way of publishing in PDF makes it difficult to retrospectively convert the legacy literature into data. This presentation will discuss pre-publication tagging as an alternative solution for publishing FAIR (Findable, Accessible, Interoperable, Resuable) biodiversity data. The Metotaxa-Metostem workflow Тhe MetoTaxa project aims to create a new digital production chain for the European Journal of Taxonomy, which enables the pre-publication semantic structuring of text, automatic tagging and semantic enrichment (annotation). The system is based on a single-source publishing model, where the development of an XML file enables technical editors to automatically enrich text and produce multiple digital outputs. This makes it possible to structure generic or domain-specific sections of articles (e.g., Introduction; Material and methods; Taxon names or Мaterial examined). Thanks to the GoldenGate API developed by Plazi, the Text Encoding Intiative (TEI) XML source file is automatically annotated with JATS TaxPub tags: taxon names are labeled and each authorship can be checked via Catalogue of Life, each element of the material examined is parsed thanks to the preformatting of the text (Chester et al. 2019). Also, each bibliographic reference is parsed into Journal Article Tag Suite (JATS) elements (author names, title, journal, etc.), which automatically links references to their in-text citations. Pre-publication tagging will be carried out by the technical editors and then checked by the authors before publication, and will be sent to databases such as Global Biodiversity Information Facility (GBIF) or Biodiversity Literature Repository (BLR) as soon as the article is published. We will also briefly present MetoStem, which offers a technical solution for the digital transformation of monographs, and particularly floras. The tools and methods developed by this project will enable advanced publication of interoperable structured text and data. ARPHA Publishing Platform Launched in 2010 by Pensoft, ARPHA (Penev et al. 2010) is the first ever scholarly publishing platform to support pre-publication semantic tags and enhancements to entities (e.g., taxon treatments, taxon names, sequences) in the JATS TaxPub XML format developed by Plazi, which are then embedded into the HTML version of the article. Having proved advantageous for biodiversity scientists, Pensoft’s pre-publication tagging workflow has since been adopted by over 30 biodiversity journals hosted on ARPHA. The second development stage of ARPHA was marked by the launch of ARPHA Writing Tool (AWT)*1 and Biodiversity Data Journal in 2013. AWT supports import of Darwin Core structured data from GBIF, Barcode of Life Data Systems (BOLD) and Integrated Digitized Biocollections (iDigBio) directly into manuscripts. These are also exported automatically as published material citations to GBIF. AWT also provides several other unique tools encompassed within the ARPHA-BioDiv toolbox (Penev et al. 2017). Currently, AWT is being redeveloped into a standalone, freely accessible installation (AWT 2.0), based on a micro-service architecture. It enables new semantic enhancements during the authoring process, which can be confirmed by the authors before manuscript submission. Such enhancements include the in-text citations context by CiTO ontology; automated tagging of taxon names and linking to their identifiers in authoritative sources; annotator tool; nanopublication module; automated search and import of references; treatment citation module; export/import to/from JATS TaxPub; and internal communication tool for contributors.