Self-archiving Research Articles

The Genomic SSR Millets Database (GSMDB): enhancing genetic resources for sustainable agriculture.

The global population surge demands increased food production and nutrient-rich options to combat rising food insecurity. Climate-resilient crops are vital, with millets emerging as superfoods due to nutritional richness and stress tolerance. Given limited genomic information, a comprehensive genetic resource is crucial to advance millet research. Whole-genome sequencing provides an unprecedented opportunity, and molecular genetic methodologies, particularly simple sequence repeats (SSRs), play a pivotal role in DNA fingerprinting, constructing linkage maps, and conducting population genetic studies. SSRs are composed of repetitive DNA sequences where one to six nucleotides are repeated in tandem and distributed throughout the genome. Different millet species exhibit genomic variations attributed to the presence of SSRs. While SSRs have been identified in a few millet species, the existing information only covers some of the sequenced genomes. Moreover, there is an absence of complete gene annotation and visualization features for SSRs. Addressing this disparity and leveraging the de-novo millet genome assembly available from the NCBI, we have developed the Genomic SSR Millets Database (GSMDB; https://bioinfo.icgeb.res.in/gsmdb/). This open-access repository provides a web-based tool offering search functionalities and comprehensive details on 6.747645 million SSRs mined from the genomic sequences of seven millet species. The database, featuring unrestricted public access and JBrowse visualization, is a pioneering resource for the research community dedicated to advancing millet cultivars and related species. GSMDB holds immense potential to support myriad studies, including genetic diversity assessments, genetic mapping, marker-assisted selection, and comparative population investigations aiming to facilitate the millet breeding programs geared toward ensuring global food security. Database URL: https://bioinfo.icgeb.res.in/gsmdb/.

Repository (R)evolution: Metadata, Interoperability, and Sustainability

Introduction: Successfully managing an open-access repository requires constant attention to user community priorities in order to inform the development or selection of a platform that fulfills constantly evolving functional demands in an increasingly complex operational environment. This paper uses AgEcon Search (AES) as an example of the way that varying platforms address the metadata and other platform needs of a repository. AES is a successful subject repository with an international scope that has resided on several different platforms in its 25-year lifespan. Elements and Considerations: Critical among the technical requirements of a repository is interoperability with other information sources and the ability to accommodate and describe different types of objects, including data. Experienced in the use of easy and widely used Dublin Core (DC), as well as Machine-Readable Cataloging 21 (MARC 21)-based repository platforms, we discuss both metadata schemas from administrative and user perspectives. Reconsidering underlying metadata issues might positively impact both technical and administrative issues that are currently restricting the development of robust, interoperable systems. As managers of AES, we are uniquely placed to discuss both technical and sustainability issues. Conclusions: Although many institutional and subject repositories are on platforms that use DC for their metadata, other options are available. MARC, the well-established library standard, can provide the wide range of fields needed to fully and accurately describe the variety of document and data types that are included in repositories.

MDRepo-an open data warehouse for community-contributed molecular dynamics simulations of proteins.

Molecular Dynamics (MD) simulation of biomolecules provides important insights into conformational changes and dynamic behavior, revealing critical information about folding and interactions with other molecules. The collection of simulations stored in computers across the world holds immense potential to serve as training data for future Machine Learning models that will transform the prediction of structure, dynamics, drug interactions, and more. Ideally, there should exist an open access repository that enables scientists to submit and store their MD simulations of proteins and protein-drug interactions, and to find, retrieve, analyze, and visualize simulations produced by others. However, despite the ubiquity of MD simulation in structural biology, no such repository exists; as a result, simulations are instead stored in scattered locations without uniform metadata or access protocols. Here, we introduce MDRepo, a robust infrastructure that provides a relatively simple process for standardized community contribution of simulations, activates common downstream analyses on stored data, and enables search, retrieval, and visualization of contributed data. MDRepo is built on top of the open-source CyVerse research cyber-infrastructure, and is capable of storing petabytes of simulations, while providing high bandwidth upload and download capabilities and laying a foundation for cloud-based access to its stored data.

Leveraging textured flickers: a leap toward practical, visually comfortable, and high-performance dry EEG code-VEP BCI.

Reactive Brain-Computer Interfaces (rBCIs) typically rely on repetitive visual stimuli, which can strain the eyes and cause attentional distraction. To address these challenges, we propose a novel approach rooted in visual neuroscience to design visual Stimuli for Augmented Response (StAR). The StAR stimuli consist of small, randomly-oriented Gabor or Ricker patches that optimize foveal neural response while reducing peripheral distraction.

Methods: In a factorial design study, 24 participants equipped with an 8-dry electrode EEG system focused on series of target flickers presented under three formats: traditional Plain flickers, Gabor-based, or Ricker-based flickers. These flickers were part of a five-class Code Visually Evoked Potentials (c-VEP) paradigm featuring low-frequency, short, and aperiodic visual flashes.

Results: Subjective ratings revealed that Gabor and Ricker stimuli were visually comfortable and nearly invisible in peripheral vision compared to plain flickers. Moreover, Gabor and Ricker-based textures achieved higher accuracy (93.6% and 96.3%, respectively) with only 88 seconds of calibration data, compared to plain flickers (65.6%). A follow-up online implementation of this experiment was conducted to validate our findings in naturalistic operations. During this trial, remarkable accuracies of 97.5% in a cued task and 94.3% in an asynchronous digicode task were achieved, with a mean decoding time as low as 1.68 seconds.

Conclusion: This work demonstrates the potential to expand BCI applications beyond the lab by integrating visually unobtrusive systems with gel-free, low-density EEG technology, thereby making BCIs more accessible and efficient. The datasets, algorithms, and BCI implementations are shared through open-access repositories.

The development of the water supply on the Peloponnese in Greco-Roman times

It has long been clear that the water supply in ancient Greece was transformed over time, with the relative number of various types of water sources varying in time and space. Yet, what patterns this produced has never been explored, and the degree to which trends suggested by local or qualitative studies are representative for larger areas and patterns is unknown. The root of this uncertainty lies largely in the difficulty assembling an extensive and representative material beyond individual sites or cities. Following this, the present article has two aims. The first is to test and evaluate a method for collecting an extensive and (more) representative material for the investigation of the water supply in ancient Greece on a regional scale, based on a systematic review of the material from the Peloponnese published in Archaeological Reports 1887–2012. The second aim is to discuss how the collected data can be used to explore the transformations of the water supply systems on the Peloponnese in the period 900 BC–AD 300. Together the results are intended to develop further the WaterWorks project, which aims to create a better understanding of the development of the ancient water supply. The method produced a considerably better dataset than previously available. The dataset, recorded in an Access database, suggests that some hitherto acknowledged trends are probably valid for larger areas while others are less prominent than previously believed. However, in the end, the dataset is too limited to allow firm conclusions concerning how, and to a larger degree why, the water supply system was transformed over time. The dataset will be made publicly accessible in an open access repository.

Neurodivergence resource bank showcase

An awareness of neurodiversity is important for educators as there has been an increase in the number of neurodivergent students accessing higher education (HE) in recent years (HESA, 2022). Additionally, universities have a legal obligation under the Equality Act 2010 to provide anticipatory reasonable adjustments to reduce barriers to learning (Equality Challenge Unit, 2010). In this wildcard session, the authors presented the journey of the ALDinHE Neurodiversity/ Inclusivity Community of Practice (CoP). They invited new members to become involved with the CoP. CoPs are ‘socially configured spaces that necessarily involve learning as an aspect of membership’ (Tummons, 2018, p.4). Community members can become involved by joining the bi-monthly meetings, hosting a session on a topic they are passionate about, or reviewing submissions for the Neurodivergence Resource Bank. The session offered delegates the chance to explore the Neurodivergence Resource Bank. This open-access repository is available through ALDinHE’s website, meaning all HE staff can access the resources. This is key as all HE staff ‘should be aware of inclusive teaching practices, to ensure an equitable learning experience for all students’ (Dettmer and Welton, 2023, p.64). Participants gave feedback on the submissions. They were also encouraged to submit their resources to it. This session explained how to submit resources and the benefits of evidencing impact for professional development.

E-Health Technologies: Implications for Quality in Public Health Services

Objective: The research sought to investigate the implications of e-Health technologies on the quality of public health services in Brazil, in order to identify opportunities and challenges. Methodology: Using a bibliographic research methodology, materials already published were analyzed, with emphasis on telemedicine studies and electronic health records. The bibliographic survey was carried out on platforms such as SciELO, Scopus and Google Academic, besides national repositories, such as the Capes Thesis Bank and other Brazilian open access repositories. Data Results and Analysis: The results show that these technologies can increase the efficiency, accessibility, and continuity of care, especially in remote areas, by enabling better management of information and services. However, significant challenges arise, such as digital inclusion, the empowerment of health professionals and the protection of patient data. Conclusion: As a conclusion, it is highlighted that although e-Health technologies have the potential to transform the health system, their implementation must be accompanied by policies that guarantee inclusion and safety, ensuring that all citizens benefit from these innovations.

Machine learning force field for thermal oxidation of silicon.

Looking back at seven decades of highly extensive application in the semiconductor industry, silicon and its native oxide SiO2 are still at the heart of several technological developments. Recently, the fabrication of ultra-thin oxide layers has become essential for keeping up with trends in the down-scaling of nanoelectronic devices and for the realization of novel device technologies. With this comes a need for better understanding of the atomic configuration at the Si/SiO2 interface. Classical force fields offer flexible application and relatively low computational costs, however, suffer from limited accuracy. Ab initio methods give much better results but are extremely costly. Machine learning force fields (MLFF) offer the possibility to combine the benefits of both worlds. We train a MLFF for the simulation of the dry thermal oxidation process of a Si substrate. The training data are generated by density functional theory calculations. The obtained structures are in line with abinitio simulations and with experimental observations. Compared to a classical force field, the most recent reactive force field, the resulting configurations are vastly improved. Our potential is publicly available in an open-access repository.

Restoring protein glycosylation with GlycoShape

Despite ground-breaking innovations in experimental structural biology and protein structure prediction techniques, capturing the structure of the glycans that functionalize proteins remains a challenge. Here we introduce GlycoShape (https://glycoshape.org), an open-access glycan structure database and toolbox designed to restore glycoproteins to their native and functional form in seconds. The GlycoShape database counts over 500 unique glycans so far, covering the human glycome and augmented by elements from a wide range of organisms, obtained from 1 ms of cumulative sampling from molecular dynamics simulations. These structures can be linked to proteins with a robust algorithm named Re-Glyco, directly compatible with structural data in open-access repositories, such as the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and AlphaFold Protein Structure Database, or own. The quality, performance and broad applicability of GlycoShape is demonstrated by its ability to predict N-glycosylation occupancy, scoring a 93% agreement with experiment, based on screening all proteins in the PDB with a corresponding glycoproteomics profile, for a total of 4,259 N-glycosylation sequons.

The Influence of Open Access on Institutional Scientific Research Output in MENA Countries: A Comparative Analysis

The release of scientific research has substantial consequences for both the research and the institution in which it was carried out. The selection of publishing methods for scientific articles, such as journal type, quartile, indexed databases, and publishing models, plays a crucial role. Various publishing models exist, including platinum, gold, and green open access. In this study, we examine the implications of open access publishing on reputable journals for Middle East and North Africa (MENA) countries. Additionally, we explore the correlation between open access publishing and MENA country classification according to the World Bank. Bibliometric data from Scopus database are used, focusing on researchers from each MENA country. The World Bank determines if a country is low, middle, or high income. The total number of published documents and open access publications are also considered. The study investigates how open access publishing affects university and research center rankings within MENA countries, utilizing Scopus database information. This encompasses the number of open access documents indexed in Scopus and citations from MENA countries. Multiple ranking systems, such as 2024-QS World University Ranking (QSWUR) and 2023-Scimago Institutions Ranking, are assessed. Findings reveal that open access articles contribute to 72% to 95% of citations received by institutions in MENA countries, highlighting the influence of this publishing model. Additionally, the percentage of open access publishing ranges from 32% in low-income countries to 56% in other MENA countries. The study also demonstrates that MENA countries with higher numbers of open access publications are more likely to have institutions ranked in prestigious systems such as QS World University Ranking and Scimago Institutions. It is discovered that the average percentage of citations received from open access publications indexed in Scopus for MENA countries is 82%, indicating the significant impact of open access publishing on academic citations in these nations. We believe that the procedures done in this study for MENA countries can be generalized further for global countries.

Challenges and opportunities when studying movement ecology in science and practical conservation

Movement is a key mechanism influencing biodiversity patterns and ecosystem processes. Movement ecology science aims to understand the causal relationships between environmental conditions, animal movements, interactions and coexistence of species, as well as effects of movement patterns on ecosystem processes. In contrast, practical conservation primarily aims to understand organisms' movements to improve species management, protection, legal monitoring or risk assessment, and species-habitat interactions. Despite the many studies of movement ecology in basic and applied sciences as well as in practical conservation in terrestrial ecosystems, knowledge gain and transfer between disciplines are limited. Better integration and linking of both disciplines would result in diverse science-practice synergies, but these are currently constrained by numerous challenges that need to be overcome. From a scientific perspective, knowledge gain from practice is limited by multitude of case studies with limited spatial and temporal resolution. This can be overcome by improving access and combining the diversity of data for a research area that often deals with small sample sizes. From a practical perspective, the movement ecology framework which is often dedicated to basic research, and access and language barriers of scientific publications limit the application of scientific results in practice. Here movement ecologists should be encouraged to consider conservation issues more frequently in addition to basic research. The transfer of scientific results could be improved by scientists providing sufficient details for practitioners to extract relevant information and publish at least an open-access abstract in local language with clear management recommendations. Further, the use of open-access repositories allows both, scientists and practitioners an overview of the multitude of studies and helps to share data in order to derive general conclusions. Challenges impacting science and practice can be conceptual, organisational and technical in nature. Such constrains can be overcome, for example, by providing verified trapping protocols, using recent technological developments and analytical methods combined with trainings on these state-of-the-art tracking and analysing tools. In particular, collaborative project planning between scientists and practitioners can help to improve the sampling design of applied studies and broaden the data base for science in order to significantly advance the movement ecology framework and gain comprehensive knowledge for practical conservation.

Dealing with Multilingualism and Non-English Content in Open Repositories: Challenges and Perspectives

Several organizations and initiatives have recently called for more support of multilingualism in research to promote epistemic plurality and raise awareness of the adverse effects of an anglocentric research ecosystem. But this support for and practice of multilingualism and linguistic diversity cannot happen in a digital or technological vacuum. Open repositories can play an important role in ensuring that research infrastructures have the ability to implement and promote multilingualism at scale in an Open Science environment. This implementation, however, is complex and does not come without its own theoretical and technical challenges. One of these challenges is to recognize that the implementation of multilingualism in open repositories can hardly be dissociated from wider concerns of discoverability, research assessment practices, and the anglocentric nature of digital infrastructures and metadata standards or protocols. Drawing on the COAR (Coalition of Open Access Repositories) recommendations report produced by the COAR Task Force on Supporting Multilingualism and non-English Content in Repositories, this article presents and critically examines how and why three particular recommendations of this document are particularly well suited to support a decolonial trajectory for the management of multilingualism in open repositories. More specifically, this article discusses the decolonial aspects and praxis underlying guidelines such as declaring the language(s) of the resource and of its metadata, writing personal name/s using the writing system used in the deposited document while providing a persistent identifier to disambiguate author/s identification and, overlapping with the latter, enabling UTF-8 support so as to promote use of the original alphabet / the writing system whenever possible, without negating the possibility to transliterate metadata by means of recognized standards (e.g. ISO). In so doing, we argue that these recommendations enable a multifaceted technology and politics of recovery that promotes a form of linguistic revitalization and strengthens linguistic diversity.

Historical review of inclusive educational theories through digital archives

Introduction: This study is framed in the field of social inclusion of people with disabilities, following the guidelines of the United Nations Convention (2006) and the Sustainable Development Goals (SDGs) of the 2030 Agenda. The main objective is to provide a historical overview of inclusive theories to undestand their social impact and their application in the educational field. Methodology: The methodology is qualitative and is approached from a hermeneutic-interpretative perspective, based on the analysis of bibliographic and documentary sources. Results: Among the results obtained, the sources found and the organisations that advocate for the social model of functional diversity stand out. However, for its actual implementation, more support resources are required in the educational sphere. Discussions: The digitization of archival materials demonstrates that knowledge becomes accessible when adapted to an open publication format, which can be accessed anywhere. Conclusions: The creation of an open-access learning resource repository is another inclusive measure proposed, to share adapted materials. Following the principles of the SDGs, a successful sustainable development program is achieved by creating partnerships with civil society and promoting initiatives that reduce inequalities.

Whale Collections and Exhibitions at the Natural History Museum of the University of Pisa (Italy)

The Natural History Museum of the University of Pisa hosts the most important osteological collection of extant cetaceans in Italy as well as one of the most relevant all over Europe. Furthermore, it also preserves a significant palaeontological collection that includes several holotypes and otherwise unique specimens of Archaeoceti (archaic cetaceans), Mysticeti (baleen whales) and Odontoceti (toothed whales). Here, we provide a historical overview of these collections and the corresponding displays, with special attention paid to the origin, development and design of the ‘Archaeocete Hall’ and ‘Cetacean Gallery’. These comprise what may be the largest exhibition worldwide among those dedicated exclusively to cetaceans—one that includes 28 complete skeletons and one skull belonging to 27 extant species as well as fossils of nine extinct species. Our review also reveals that the museum exhibitions feature the oldest known specimen of Mesoplodon bowdoini and the type specimen of Ziphius savi, the latter being a validly described species that is currently regarded as a junior synonym of Ziphius cavirostris. Also significant is the display of several holotype specimens of fossil species such as the protocetid archaeocete Aegyptocetus tarfa, the balaenid baleen whales Balaena montalionis and Balaenula astensis, and the monodontid Casatia thermophila. The Archaeocete Hall and Cetacean Gallery are highly appreciated by visitors as well as perused by the museum’s educational team. The online archiving of 3D models of many of the MSNUP specimens on the open-access digital repository Sketchfab and their subsequent dissemination through the Wikimedia platforms has led to the creation of a major osteological resource—one that is broadly accessible to internet users worldwide.

Impacts of Open Access and Open Repositories on Acquisitions and Collection Development

Impacts of Open Access and Open Repositories on Acquisitions and Collection Development

MIPDS: a comprehensive database on the molecular interactions in protein dimer structures

Although many studies have addressed the significance of interactions in the dimeric structures of proteins, there is no dedicated database of these interactions. To this end, the Molecular Interactions in Protein Dimer Structure (MIPDS) database has been developed; it is an open-access repository containing 60 298 3D structures of dimeric proteins sourced from the Protein Data Bank. This helps researchers comprehend the types of interaction, which include those mediated by water, small molecules or ligands and direct interactions, in 3D structures at the molecular level. The database is accessible through a user-friendly interface, where users can conduct searches based on PDB accession number, interaction type and geometric parameters. It can be viewed in textual and graphical formats using the plug-in JSmol. MIPDS is updated weekly using programmed scripts to incorporate newly released dimeric structures and analyses of their interaction types. The database is intended for the scientific community working in structural biology, structural bioinformatics, drug discovery and development. MIPDS is freely accessible to users worldwide at http://dicsoft1.physics.iisc.ac.in/mipds.

MRI Brain Tumor Classification and Extraction using Deep Learning-Based Decision Level Image Fusion Technique

Objectives: The proposed work emphasizes the tumor region extracted from the multimodal MRI brain scan by deep learning-based decision-level image fusion technique. Methods: Convolutional Neural Network (CNN) architectures such as AlexNet, ResNet50, and VGG16 perform brain tumor classification with multimodal MRI images Flair, T2, and T1c respectively. Flair images are fed to the AlexNet architecture, T2 images are fed to the ResNet50 architecture, and T1c images are fed to the VGG16 architecture to classify brain tumor images. The classification results from these architectures are fused together to perform the decision on the given inputs. If the inputs come under the decision of the tumor affected then the tumor portion will be extracted using the fusion of three images as a post-processing operation. Findings: The experiments are done using BraTS datasets an open-access brain tumor image analysis research repository. The three CNN architectures' performance is measured by accuracy and gives 0.87 for AlexNet, 0.91 for ResNet50, and 0.99 for VGG16. The extracted tumor region from the fused output image is compared with the ground truth image by metrics such as SSIM with 0.93, DC 0.96, and PSNR with 66.57. Better results are received for the proposed work in the evaluation analysis than the existing works. Novelty: Decision level image fusion limitedly experimented with Deep Learning techniques in state-of-art methods. In this proposed method, the decisions made based on the classification result of three CNN architectures. Keywords: MRI, Brain tumor, Deep Learning, Convolutional Neural Network Architectures, Image Fusion, AlexNet, ResNet50, VGG16

Metrology for sensor networks: metrological traceability and measurement uncertainties for air quality monitoring

Abstract In situ calibration of sensors delivering SI traceable measurement results still provides an open question to the design and operation of sensor networks. Particularly when addressing low-cost sensors, currently, the use of sensor networks for air quality monitoring is limited by the low or unknown accuracy of measurements that they can achieve, while the data quality of individual sensor networks is mainly derived by algorithms. Standardization bodies like DIN and CEN therefore announced the need for investigations of validation methods on gas phase species and particulate matter on the one hand side, and for the development of fully digitized quality assurance/quality control and calibration techniques for sensor networks on the other (CEN/CENELEC, Opportunity for Standardisation to Contribute to the European Partnership on Metrology EPM under Horizon Europe). This contribution concentrates on the metrological traceability of sensor networks for air quality monitoring to the international system of units (SI) based on FAIRified intra-network communications (M. Wilkinson, et al., “The FAIR guiding principles for scientific data management and stewardship,” Sci. Data, vol. 3, 2016, Art. no. 160018) and including delocalized Optical Gas Standards operated according to the digital TILSAM method (O. Werhahn, et al., The TILSAM Method Adapted into Optical Gas Standards – Complementing Gaseous Reference Materials, PTB Open Access Repository, 2021). Informed by related activities in EURAMET (Partnership project FunSNM, EMNs COO & POLMO, TC-IM 1551) (European Metrology Network Climate and Ocean Observation (COO), European Metrology Network Pollution Monitoring (POLMO), EURAMET Project TC-IM 1551, Project Database) this contribution discusses the importance of measurement uncertainties in the context of sensor networks, comprising different sensor principles and promoting an efficient uptake of state-of-the-art methods. We discuss how the sensor network case can be addressed with sensors individually using the GUM principles (Joint Committee for Guides in Metrology, Guide to the Expression of Uncertainty in Measurement (GUM), JCGM 100: 2008 (E)). For sensor network measurements becoming metrologically traceable to the SI, documented and unbroken chains of calibrations need to be implemented each contributing to the measurement uncertainty. This applies to each individual sensor of the network including the potential gold standard among them, but also to the network’s output viewed as a single entity. The contribution provides first approaches to be tested and validated that are underpinned by fundamental design strategies for sensor networks. It follows on practical applications in real world scenarios aside from model uncertainties discussed in artificial intelligence prospects.

Aerial Wildlife Image Repository for animal monitoring with drones in the age of artificial intelligence.

Drones (unoccupied aircraft systems) have become effective tools for wildlife monitoring and conservation. Automated animal detection and classification using artificial intelligence (AI) can substantially reduce logistical and financial costs and improve drone surveys. However, the lack of annotated animal imagery for training AI is a critical bottleneck in achieving accurate performance of AI algorithms compared to other fields. To bridge this gap for drone imagery and help advance and standardize automated animal classification, we have created the Aerial Wildlife Image Repository (AWIR), which is a dynamic, interactive database with annotated images captured from drone platforms using visible and thermal cameras. The AWIR provides the first open-access repository for users to upload, annotate, and curate images of animals acquired from drones. The AWIR also provides annotated imagery and benchmark datasets that users can download to train AI algorithms to automatically detect and classify animals, and compare algorithm performance. The AWIR contains 6587 animal objects in 1325 visible and thermal drone images of predominantly large birds and mammals of 13 species in open areas of North America. As contributors increase the taxonomic and geographic diversity of available images, the AWIR will open future avenues for AI research to improve animal surveys using drones for conservation applications. Database URL: https://projectportal.gri.msstate.edu/awir/.

Six years of high-resolution climatic data collected along an elevation gradient in the Italian Alps

The complex meso- and microclimatic heterogeneity inherent to mountainous regions, driven by both topographic and biotic factors, and the lack of observations, poses significant challenges to using climate models to predict and understand impacts at various scales. We present here a six-year dataset (2017–2022) of continuous climatic measurements collected at five elevations from 983 m to 2705 m above sea level in the Val Mazia - Matschertal valley in the Italian Alps. The measurements include the air temperature, relative humidity, wind speed and direction, solar radiation, soil properties, precipitation, and snow height. Collected within the European Long-Term Ecological Research program (LTER), this dataset is freely available in an open access repository. The time series may be valuable for the validation of regional climate models, atmospheric exchange modelling, and providing support for hydrological models and remote sensing products in mountain environments. Additionally, our data may be useful for research on the influence of elevation on ecological processes such as vegetation growth, plant composition, and soil biology. Beyond its utility in advancing such fundamental research, meteorological monitoring data contribute to informed socio-political decisions on climate adaptation strategies, land management, and water resource planning, enhancing the safety and resilience of mountain communities and biodiversity.