Technical Components Research Articles

Realizing FAIR Digital Objects for the German Helmholtz Association of Research Centres

Realizing FAIR Digital Objects for the German Helmholtz Association of Research Centres

Influence of Aikido and Taijiquan-Tuishou on Contact Improvisation

Oriental Martial Arts such as Taijiquan-Tuishou and Aikido represent some of the Asian influences on western culture resulting from immigration from China and Japan to the United States of America during the middle of the 20th century. Contact Improvisation, a style of post-modern dance performed in pairs, is one of the manifestations enriched by this oriental influence. The purpose of this manuscript is to document which dynamic, proprioceptive and somatic elements were transferred to the choreographic language of Contact Improvisation from these martial arts. In the case of Contact Improvisation, the most important technical components highlighted include: center of gravity, weight sharing, point of contact, sphericity, rolling, the embryonic relationship of axial axis and limbs, ki and proprioceptive communication. Although an evolution in the interpretation of the meanings and uses of this particular dance form may exist, we can nonetheless establish some kinesthetic communication codes and strategies derived directly from its original sources. These sources belong to martial arts such as Aikido and Tuishou or Taijiquan and are essential to the intercultural communication component of the Contact Improvisation duo since they involve the learning of fundamentals and principles of non-verbal interaction considered as specific for the mastery of intercorporeality. This is discussed in light of the work of Mark Young, a Contact Improvisation choreographer who maintains Paxton's legacy of roll technique documented in “Material for the Spine” by perfecting the execution and technical variations of helix rolls in a constructed system of spirals. This concurrence of strategies adopted from Aikido and Taijiquan and the usefulness of these elements in terms of performing this partner dance would appear to be key in the understanding of Contact Improvisation.

Early career software developers and work preferences in software engineering

AbstractContext: The software engineering researchers and practitioners echoed the need for investigations to better understand the engineers developing software and services. In light of current studies, there are significant associations between the personalities of software engineers and their work preferences. However, limited studies are using psychometric measurements in software engineering.Objective: We aim to evaluate attitudes of early‐stage software engineers and investigate link between their personalities and work preferences.Method: We collected extensive psychometric data from 303 graduate‐level students in Computer Science programs at four Pakistani and one Swedish university using Five‐Factor Model. The statistical analysis investigated associations between various personality traits and work preferences.Results: The data support the existence of two clusters of software engineers, one of which is more highly rated across the board. Numerous correlations exist between personality qualities and the preferred types of employment for software developers. For instance, those who exhibit greater levels of emotional stability, agreeableness, extroversion, and conscientiousness like working on technical activities on a set timetable. Similar relationships between personalities and occupational choices are also evident in the earlier studies. More neuroticism is reported in female respondents than in male respondents. Higher intelligence was demonstrated by those who worked on the “entire development process” and “technical components of the project.”Conclusion: When assigning project tasks to software engineers, managers might use the statistically significant relationships that emerged from the analysis of personality attributes. It would be beneficial to construct effective teams by taking personality factors like extraversion and agreeableness into consideration. The study techniques and analytical tools we use may identify subtle relationships and reflect distinctions across various groups and populations, making them valuable resources for both future academic research and industrial practice.

Electric Vehicle as a Service (EVaaS): Applications, Challenges and Enablers

Under the vehicle-to-grid (V2G) concept, electric vehicles (EVs) can be deployed as loads to absorb excess production or as distributed energy resources to supply part of their stored energy back to the grid. This paper overviews the technologies, technical components and system requirements needed for EV deployment. Electric vehicle as a service (EVaaS) exploits V2G technology to develop a system where suitable EVs within the distribution network are chosen individually or in aggregate to exchange energy with the grid, individual customers or both. The EVaaS framework is introduced, and interactions among EVaaS subsystems such as EV batteries, charging stations, loads and advanced metering infrastructure are studied. The communication infrastructure and processing facilities that enable data and information exchange between EVs and the grid are reviewed. Different strategies for EV charging/discharging and their impact on the distribution grid are reviewed. Several market designs that incentivize energy trading in V2G environments are discussed. The benefits of V2G are studied from the perspectives of ancillary services, supporting of renewables and the environment. The challenges to V2G are studied with respect to battery degradation, energy conversion losses and effects on distribution system.

In-situ leakage behavior of polymer-metal hybrids under mechanical load

Abstract Tightness against media is a frequent requirement for technical components. Despite various standardized test procedures, failure regularly occurs during use. Often, no clear cause for failure can be determined afterwards. In this article, a new test setup is presented and applied, which allows an in-situ measurement during a mechanical load. A flow meter with a measuring range of 0.02 mL/min to 5 mL/min is used for this purpose. This makes it possible to determine leakage rates with time resolution and thus to identify the moment of failure or the causal failure load. This new method was applied directly to different aluminum inserts with a polyamide 66 (PA66) overmold. It was shown that no increase in leakage occurs until a maximum force is reached, even with multiple loads. This maximum force depends only on the pretreatment of the inserts and can be determined in a simple pull-out test independently of the test setup used here and can therefore be used for the design of assemblies. In the test, a maximum force of 100 N was achieved for untreated inserts, 140 N for adhesion promoter-coated parts and 600 N for etched inserts with a contact area of 48 mm2. With this results, a new link between adhesion and tightness can be shown, which of course is only valid for initial tight parts.

A Standard-Based Citywide Health Information Exchange for Public Health in Response to COVID-19: Development Study.

BackgroundDisease surveillance is a critical function of public health, provides essential information about the disease burden and the clinical and epidemiologic parameters of disease, and is an important element of effective and timely case and contact tracing. The COVID-19 pandemic demonstrates the essential role of disease surveillance in preserving public health. In theory, the standard data formats and exchange methods provided by electronic health record (EHR) meaningful use should enable rapid health care data exchange in the setting of disruptive health care events, such as a pandemic. In reality, access to data remains challenging and, even if available, often lacks conformity to regulated standards.ObjectiveWe sought to use regulated interoperability standards already in production to generate awareness of regional bed capacity and enhance the capture of epidemiological risk factors and clinical variables among patients tested for SARS-CoV-2. We described the technical and operational components, governance model, and timelines required to implement the public health order that mandated electronic reporting of data from EHRs among hospitals in the Chicago jurisdiction. We also evaluated the data sources, infrastructure requirements, and the completeness of data supplied to the platform and the capacity to link these sources.MethodsFollowing a public health order mandating data submission by all acute care hospitals in Chicago, we developed the technical infrastructure to combine multiple data feeds from those EHR systems—a regional data hub to enhance public health surveillance. A cloud-based environment was created that received ELR, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project initiation to aid in consensus and principles for data use. We measured the completeness of each feed and the match rate between feeds.ResultsData from 88,906 persons from CCDA records among 14 facilities and 408,741 persons from ELR records among 88 facilities were submitted. Most (n=448,380, 90.1%) records could be matched between CCDA and ELR feeds. Data fields absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. Less than 5% of CCDA data fields were empty. Merging CCDA with ELR data improved race, ethnicity, comorbidity, and hospitalization information data availability.ConclusionsWe described the development of a citywide public health data hub for the surveillance of SARS-CoV-2 infection. We were able to assess the completeness of existing ELR feeds, augment those feeds with CCDA documents, establish secure transfer methods for data exchange, develop a cloud-based architecture to enable secure data storage and analytics, and produce dashboards for monitoring of capacity and the disease burden. We consider this public health and clinical data registry as an informative example of the power of common standards across EHRs and a potential template for future use of standards to improve public health surveillance.

Developing a Decision Support Evaluation Model Based on the Matter Element Analysis Method to Optimize the Environmental Flows in Dammed Rivers

The large number of dams in the world has caused many ecological problems, especially in ecologically fragile areas. Appropriate environmental flow (e-flows) releases reduce stress on river ecosystems caused by the flow alterations of dams. As e-flow releasing is substantially a decision-making process, it is important to choose the right calculation method in many e-flow assessment frameworks and calculation methods or to select the proper e-flow result from many scenarios. In China, there are government guidelines to assist managers in choosing an e-flow method for their situations, but the technical components of these guidelines are too general and not very specific, even though the coverage of the framework of guidelines is comparatively complete. Thus, a high degree of subjectivity remains in the method selection, and managers are often confused about the different e-flow results and scenarios. A more detailed decision support evaluation (DSE) model which can quantify and compare the results from different calculation methods is therefore needed to provide a basic technical economy evaluation. Based on the relevant policies and the dam priority classification frameworks in China, we propose a DSE model based on the matter element analysis (MEA) method to complement the Chinese e-flow framework. First, the flow regime criteria from the related government guidelines for a variety of conservation objectives are summarized. Secondly, different scenarios of e-flows are calculated based on the formal government guidelines and using the same hydrological database. Finally, the DSE model for assessing the different e-flow scenarios are built and demonstrated. MEA helped to quantify and optimize the different results and reduce the uncertainty. The DSE model presented in this study can be applied to e-flow optimization for all dammed rivers in China and serve as a decision support tool for managers.

An external stability audit framework to test the validity of personality prediction in AI hiring

Automated hiring systems are among the fastest-developing of all high-stakes AI systems. Among these are algorithmic personality tests that use insights from psychometric testing, and promise to surface personality traits indicative of future success based on job seekers’ resumes or social media profiles. We interrogate the validity of such systems using stability of the outputs they produce, noting that reliability is a necessary, but not a sufficient, condition for validity. Crucially, rather than challenging or affirming the assumptions made in psychometric testing — that personality is a meaningful and measurable construct, and that personality traits are indicative of future success on the job — we frame our audit methodology around testing the underlying assumptions made by the vendors of the algorithmic personality tests themselves. Our main contribution is the development of a socio-technical framework for auditing the stability of algorithmic systems. This contribution is supplemented with an open-source software library that implements the technical components of the audit, and can be used to conduct similar stability audits of algorithmic systems. We instantiate our framework with the audit of two real-world personality prediction systems, namely, Humantic AI and Crystal. The application of our audit framework demonstrates that both these systems show substantial instability with respect to key facets of measurement, and hence cannot be considered valid testing instruments.

Correlation of Body Composition and Coordination of Specific Footballers’ Position among Professional Football Players

The game of football is a competitive team sport that requires an essential component of motor fitness, body composition, psychological, technical, and tactical components for enhanced performance. This study assessed the correlation of body composition and coordination of specific footballers’ positions among professional football players. This study utilised a correlational research design. Participants in this study comprised twenty-nine (29) football players who play for a professional team in Nigeria. There were 12 forwards, 6 midfielders, 4 goalkeepers, and 7 defenders among the participants. The participants’ hand-eye coordination was evaluated using the alternate hand wall toss test. The beurer diagnostic scale was used to measure the participants’ body fat percentage and muscle mass. Results were analysed using pearson’s product moment correlation and linear regression. The level of significance was set at p < 0.05. A significant positive moderate correlation was observed between muscle mass and coordination among forwards (r = 0.550, p = 0.044). There was no significant correlation between muscle mass and coordination among defenders, midfielders, and goalkeepers. Likewise, there was no significant correlation between body fat percentage and coordination among football players in all the playing positions. The hand-eye coordination of forwards is significantly correlated with their muscle mass. In other words, a forward’s muscle mass affects their degree of hand-eye coordination. Therefore, football regulatory bodies and trainers could utilise the muscle mass of forwards to predict their hand-eye coordination ability. This finding should be considered by the coaches and governing bodies of football teams before designating players to playing positions in the game of football. Furthermore, there is a need for training programs specifically designed to monitor and enhance the muscle mass of forwards in a football team in order to enhance hand-eye coordination.

Holistic evaluation of aircraft detection lighting systems for wind turbines in Germany using a multi-method evaluation framework

Transponder-based Aircraft Detection Lighting Systems (ADLS) are increasingly used in wind turbines to limit beacon operation times, reduce light emissions, and increase wind energy acceptance. The systems use digital technologies such as receivers of digital transponder signals, LTE/5G, and other information and communication technology. The use of ADLS will be mandatory in Germany both for new and existing wind turbines with a height of >100 m from 2023 (onshore) and 2024 (offshore), so a nationwide rollout is expected to start during 2022. To fully realize the benefits while avoiding risks and bottlenecks, a thorough and holistic understanding of the efforts required and the impacts caused along the life cycle of an ADLS is essential. Therefore, this study presents the first multi-aspect holistic evaluation of an ADLS. A framework for evaluating digital applications in the energy sector, previously developed by the authors, is refined and applied. The framework is based on multi-criteria analysis (MCA), life cycle assessment (LCA), and expert interviews. On an aggregated level, the MCA results show an overall positive impact from all stakeholders’ perspectives. Most positive impacts are found in the society and politics category, while most negative impacts are of technical nature. The LCA of the ADLS reveals a slightly negative impact, but this impact is negligible when compared to the total life cycle impact of the wind turbines of which the ADLS is a part. Besides the aggregated evaluation, detailed information on potential implementation risks, bottlenecks, and levers for life cycle improvement are presented. In particular, the worldwide scarcity of the required semiconductors, in combination with the general lack of technicians in Germany, lead to the authors’ recommendation for a limited prolongation of the planned rollout period. This period should be used by decision-makers to ensure the availability of technical components and installation capacities. A pooling of ADLS installations in larger regions could improve plannability for manufacturers and installers. Furthermore, an ADLS implementation in other countries could be supported by an early holistic evaluation using the presented framework.

Impact of Crisis on Sustainable Business Model Innovation—The Role of Technology Innovation

The transformation of old and new technologies, the normalized crisis situation, and global economic integration blur industrial boundaries and cause the business pattern to fluctuate and become unsustainable, especially when considering the impact of the COVID-19 pandemic. This study focuses on crisis situations and combines the types of technology innovation (introduction, socialization, and differentiation) and sustainable business model innovation (efficiency, novelty, and co-benefit innovations) to theoretically analyze the dynamic impact of technology innovation on different types of sustainable business model innovations. Using a multi-case comparative analysis method, typical enterprises are selected as the sample cases. This study discusses the influences of different technology innovation schemes on sustainable business model innovation in different crisis situations. Enterprises should consider introducing technology for rapid value updates to maintain an efficient business model in an urgent production factor crisis, search for valuable and scarce technical components or introduce other entities to facilitate technical cooperation and form a novel business model in a market environment crisis, and use big data, artificial intelligence, and other technologies to create co-benefit business model innovation in a business ethics crisis. The conclusion guides enterprises and provides a framework for the optimal technical scheme under the corresponding crisis.

Machine Vision-Based Fatigue Crack Propagation System.

This paper introduces a machine vision-based system promising low-cost solution for detecting a fatigue crack propagation caused by alternating mechanical stresses. The fatigue crack in technical components usually starts on surfaces at stress concentration points. The presented system was designed to substitute a strain gauge sensor-based measurement using an industrial camera in cooperation with branding software. This paper presents implementation of a machine vision system and algorithm outputs taking on fatigue crack propagation samples.

Proposed Polish Advertisement Levies – An Efficient Source of Public Income or Instruments of the Political Battle?

This article analyses the bill of 2nd February 2021 on additional revenues of the National Health Fund, the National Fund for the Protection of Historical Monuments and the establishment of a Fund for the Support of Culture and National Heritage in the Media Area. The draft legislation, the announcement of which has triggered an unprecedented blackout protest in private media as well as a mass anti-government protest on the Internet, provides for the introduction of new public levies called advertisement contributions and the establishment of a new state special-purpose fund – the Fund for the Support of Culture and National Heritage in the Media Area. The aim of the article is to identify and present those provisions of the draft act which have evoked most controversies and have given rise to the stiff social resistance to the proposal. The first part of the paper is devoted to the assessment of the regulations within the context of the objective of the bill that was declared by the drafters in the legislative rationale. The analysis carried out has supported the assumption that providing adequate finances for those special-purpose funds that are strongly involved in remedying the consequences of the SARS CoV-2 epidemic was not a genuine purpose of the bill. It also leads to the conclusion that there is no constitutional justification for such a special-purpose levy. In the second part, the controversies over technical components of the advertising levies have been presented and analysed. On the basis of this analysis, it is possible to conclude that some of the qualitative and quantitative elements of the so-called advertisement contributions may give rise to interpretative doubts. The implementation of the research objectives made it possible to formulate a thesis that the advertisement contributions, as drafted, would not be efficient instruments of fair taxation of digital economy but rather would form instruments for achieving certain political objectives.

Bridging the gap: A library-based collaboration to enhance data skills for clinical researchers.

Enterprise data warehouses (EDWs) serve as foundational infrastructure in a modern learning health system, housing clinical and other system-wide data and making it available for research, strategic, and quality improvement purposes. Building on a longstanding partnership between Northwestern University's Galter Health Sciences Library and the Northwestern Medicine Enterprise Data Warehouse (NMEDW), an end-to-end clinical research data management (cRDM) program was created to enhance clinical data workforce capacity and further expand related library-based services for the campus. The training program covers topics such as clinical database architecture, clinical coding standards, and translation of research questions into queries for proper data extraction. Here we describe this program, including partners and motivations, technical and social components, integration of FAIR principles into clinical data research workflows, and the long-term implications for this work to serve as a blueprint of best practice workflows for clinical research to support library and EDW partnerships at other institutions. This training program has enhanced the partnership between our institution's health sciences library and clinical data warehouse to provide support services for researchers, resulting in more efficient training workflows. Through instruction on best practices for preserving and sharing outputs, researchers are given the tools to improve the reproducibility and reusability of their work, which has positive effects for the researchers as well as for the university. All training resources have been made publicly available so that those who support this critical need at other institutions can build on our efforts. Library-based partnerships to support training and consultation offer an important vehicle for clinical data science capacity building in learning health systems. The cRDM program launched by Galter Library and the NMEDW is an example of this type of partnership and builds on a strong foundation of past collaboration, expanding the scope of clinical data support services and training on campus.

Synergy of Unidirectional and Bidirectional Smart Charging of Electric Vehicles for Frequency Containment Reserve Power Provision

Besides the integration of renewable energies, electric vehicles pose an additional challenge to modern power grids. However, electric vehicles can also be a flexibility source and contribute to the power system stability. Today, the power system still heavily relies on conventional technologies to stay stable. In order to operate a future power system based on renewable energies only, we need to understand the flexibility potential of assets such as electric vehicles and become able to use their flexibility. In this paper, we analyzed how vast amounts of coordinated charging processes can be used to provide frequency containment reserve power, one of the most important ancillary services for system stability. Therefore, we used an extensive simulation model of a virtual power plant of millions of electric vehicles. The model considers not only technical components but also the stochastic behavior of electric vehicle drivers based on real data. Our results show that, in 2030, electric vehicles have the potential to serve the whole frequency containment reserve power market in Germany. We differentiate between using unidirectional and bidirectional chargers. Bidirectional chargers have a larger potential but also result in unwanted battery degradation. Unidirectional chargers are more constrained in terms of flexibility, but do not lead to additional battery degradation. We conclude that using a mix of both can combine the advantages of both worlds. Thereby, average private cars can provide the service without any notable additional battery degradation and achieve yearly earnings between EUR 200 and EUR 500, depending on the volatile market prices. Commercial vehicles have an even higher potential, as the results increase with vehicle utilization and consumption.

Research to Improve Preventive Maintenance of Technical Equipment

Abstract In order to achieve the strategic level of military equipment exploitation, according to NATO requirements, it is necessary to continuously adapt the specific maintenance activities. The main objectives pursued in the maintenance system modernization process are: to implement reliability-based maintenance, to use management methods, to present the functional scheme, and to identify the critical points in which to intervene with maintenance operations. The use of the Pareto method in the direction research studied in the paper estimates that the first two faults among those identified, namely the imbalance of the braking force on the axle and the defective service brake, represent a significant percentage of the total downtime of the Roman-DAC trucks used for the present study. According to the AMDEC data sheet, these two defects have a criticality index of 70 and 60, respectively, compared to the following identified defects, which present a criticality index of 18 and 20, respectively. In practice, the aim will be to eliminate, in particular, the identified causes that entail defects in the first and second categories. Using this research methodology, and by extrapolation to all technical equipment components, it is possible to identify solutions to improve preventive maintenance by ranking defects and performing maintenance operations on those components more often subject to damage, before they fail.

Artistic practice of technical components of monologue speech of actors

The purpose of the work is to investigate the peculiarities of the verbal means of expression of the actor in one-man shows. The research methodology is based on the application of a set of scientific methods, including systems, analysis, synthesis, as well an art history approach, which allowed to obtain objective results. The scientific novelty of the work lies in the generalization of the theoretical analysis of monologue performances staged on the Ukrainian stage, with an emphasis on the technique of speech expression and its artistic skill in the performance of actors. Conclusions. Various elements of theatrical performance are highlighted. Consideration of theoretical studies of the role of the monogenre in the performing arts, the main means of self-expression of monomart, the triad of this form of theatrical action - text, director, actor. Analysis and classification of narrative models of one-man shows: traditional narrative of a character, literary interpretation, performance in a play, actor as the second "I" of the hero, play-emotion, play-removal, play-memory. Determining the main structural parameters of the actor's stage behavior in a solo performance in a complex relationship of roles, author and character, the degree of acting, reincarnation in the image - the inclusion of plasticity, psychophysical state of the actor, purposeful volitional action, assimilation of various forms of stage space. Based on the analysis of research by scientists and theater critics, certain aspects of the historical development of solo performances, the process of their formation and their popularity in modern theatrical art have been clarified. Keywords: mono-performances, theatrical speech, acting skills, diction, artistic theatrical practice, acting language.

MULTI-SENSOR FEEDER: AUTOMATED AND EASY-TO-USE BIRDS MONITORING TOOL FOR CITIZENS

Abstract. Nowadays, more species are threatened with extinction than ever before in the human era. Especially breeding birds are considered endangered. At the same time, it is difficult to obtain sufficient data not only to raise awareness for this situation, but also to gain a better understanding and to develop potential countermeasures. We show how a citizen science based biodiversity monitoring for birds, using an automated and easy-to-use multi-sensor feeder, can look like. In doing so, we compare different configuration options concerning technical components, casing, as well as software to be used and present our suggested prototype: A smart bird feeder including an environmental sensor, a microphone, as well as a balance and a camera in a wooden case. It identifies the type of visiting birds using AI and publishes the recognized species, including all further collected data, on an open access website. The station can be reproduced by anyone at an affordable price in a Do-It-Yourself format, making citizens a key contributor to biodiversity monitoring.

Innovation Ecosystem Evolution as Socio-technical Transition: A Case Study

The evolution of innovation ecosystems is an important topic for scholars and practitioners alike, as externalities such as market changes, competitive landscapes, and regulatory pressures demand the delivery of new customer-facing value propositions. In this paper we aim to enhance our conceptual understanding of ecosystem evolution by shining a socio-technical lens upon the innovation ecosystem. Through this perspective we understand ecosystem evolution as a socio-technical transition resulting from the emergence and resolution of development-retarding social or technical components referred to as ‘reverse salients’. Our case study of a food innovation ecosystem in regional Australia identifies numerous reverse salients that inhibit ecosystem reconfiguration and transition from its current state delivering high-quality agricultural produce, to a new state marked by greater output capacity and higher number of value-added offerings. We categorise these reverse salients as ‘actors’, ‘connections’ between actors, and ‘resources’ flowing between actors. While these categories align with the ecosystem-as-structure perspective, our findings additionally underscore the role of ecosystem ‘leadership’ and ‘rules of engagement’ within the ecosystem as further sources of reverse salience. We subsequently present a conceptual model that integrates our study findings along with a set of propositions to guide future empirical research.

Human and Machine Working Together towards High Quality Specimen Data: Annotation and Curation of the Digital Specimen

The engine for our Distributed System of Scientific Collections (DiSSCo) is running! Core technical components supporting this new research infrastructure are currently being implemented and the engine that will support it is already working. Even though some nuts and bolts may still be missing, we aim to show it in action to present how it will enable annotation and curation of the Digital Specimen. The Digital Specimen is a technical implementation based on FAIR Digital Objects (FAIR stands for Findable, Accessible, Interoperable and Reusable) to support the Digital Extended Specimen concept (Webster et al. 2021). We will also present and demonstrate how we will implement standardized quality checks as they are being developed in Biodiversity Information Standards (TDWG) to enhance the quality of the data. DiSSCo is currently in its preparation phase. This phase will end in January 2023 with the completion of the DiSSCo Prepare project funded by the European Commission. Part of that project is the design of the Digital Specimen infrastructure, which is not an easy task considering the wide range of use cases, stakeholders and the many possibilities it offers. However, as we are moving towards the end of the project, we have defined clear goals and priorities to give shape to that infrastructure. This is where we take a fail fast approach: to quickly implement the proposed solution and see if it really fits. One of the major needs we want to support with the Digital Specimen infrastructure (based on collected user stories (Fitzgerald et al. 2021)) is to provide services for improving the quality and usability of specimen data. Our infrastructure aims to support annotating and community-curation of the data by both machines and users. Examples of these annotations are image-based determinations, automated- or citizen science-contributed label translations or the semi-automated linking with other biodiversity data. Semi-automated linking is currently being piloted as part of the Biodiversity Community Integrated Knowledge Library project (BiCIKL) and will use a process of link prediction through artificial intelligence in combination with human validation. Improvements in data quality made together by human and machine through the curation and annotation services will help in producing a digital specimen data object with high quality, curated and extended data. As part of the presentation we aim to give a live demonstration with the first setup in which we will ingest a dataset, run standardized quality checks and automated data enrichment services. The end result will be a digital specimen that we will present in a user-friendly interface, which has been validated by quality checks and annotated by both a human and a machine. The result will also be accessible as a FAIR Digital Object through an API. During the demonstration, we aim to give the audience a clear view on how DiSSCo can help them create higher quality specimen data, and how we will benefit in this process from the outputs of the TDWG Data quality tests and assertions taskgroup.