Introduction: What is this call about?

Via this call, NI4OS-Europe opens opportunities for scientists to access the advanced services on-boarded to EOSC (thematic, generic and repositories). The services provided have already been tested in use-cases ran by assigned scientific teams and are now offered via the open call.

Check out the list of services at the NI4OS-Europe Catalogue.

The call enables researchers from Europe to obtain access to the advanced services, which have been on-boarded on the European Open Science Cloud with the support of NI4OS-Europe. Throughout the open call, all research teams participating in the call are expected to harmonize the management of their data according to the FAIR principles throughout the whole lifetime of their work, thus, engaging with the rules of Open Science.

Read more…

 

Scope and criteria of access

80% of the projects participating in the open call would belong to the flagship scientific communities, namely Life Sciences, Climatology, Digital Cultural Heritage and Computational Physics, while the other 20% include projects in any other scientific domain.

NI4OS-Europe aims at a balanced provision of resources to the whole spectrum of scientific fields between the four target communities that this call addresses, as well as to as many as possible countries in the European region.

See project eligibility criteria here…

 

Eligibility

There are specific eligibility criteria regarding the applicants, collaborators, and industrial partners. It is also expected to create a draft idea of the research data management process applied. 

See eligibility details here… 

 

Available services

Available services within the NI4OS-Europe are categorized into repositories, thematic and generic services. Repositories group various literature and data collections that hold and preserve scientific information. Generic services provide generic capabilities and address technical needs common to multiple research areas, while thematic services are research community-specific services that provide value to the corresponding research groups.

Generic services

The HPC resources of the project consist of clusters with low-latency interconnection or supercomputers. Service providers allocated resources to support open call projects. In total, 6.2 million CPU-core hours, 402,000 GPU-card hours, and 10,000 Xeon Phi-card hours are allocated as listed below.

System

Allocation for the open call

CPU-core hours

GPU-card hours

Phi-card hours

ARIS

3,000,000

15,000

 

Avitohol

1,000,000

 

10,000

Isabella

1,000,000

 

 

PARADOX

500,000

2,000

 

Cyclone

500,000

15,000

 

Leo HPC

200,000

370,000

 

 

ARIS

ARIS is a high-performance computing resource hosted by GRNET (National Infrastructures for Research and Technology). All compute nodes are connected via SLURM resources/workload manager. Access to the system is allowed only via SSH from specific IPs/networks to login nodes from which all data management/transfers and job submission could be performed.

The ARIS infrastructure consists of a total of five computing system nodes, based on Intel x86 architecture, interconnected into a single Infiniband FDR14 network offering multiple options and processing architectures. More specifically, the infrastructure consists of:

  • Thin Nodes island based on the IBM NeXtScale platform and on Intel Xeon E5-2680v2 processors. It has 426 computing nodes and offers a total of 8,520 CPU cores.
  • Fat Nodes island consisting of 44 Dell PowerEdge R820 servers. Each server offers 4 Intel Xeon E5-4650v2 processors and 512 GB of central memory.
  • GPU accelerator nodes comprised of 44 Dell PowerEdge R730 servers. Each server contains 2 Intel Xeon E5-2660v3 processors, 64 GB of memory and 2 NVidia K40 GPU cards, and
  • Xeon Phi accelerator nodes consisting of 18 Dell PowerEdge R730 servers, each containing 2 Intel Xeon E5-2660v3 processors, 64 GB of memory and 2 Intel Xeon Phi 7120P co-processors.
  • Machine Learning node consisting of 1 server, containing 2 Intel E5-2698v4 processors, 512 GB of central memory and 8 NVIDIA V100 GPU card.

In addition, the system offers 2 PB storage space through IBM’s General Parallel File System (GPFS). The infrastructure is complete with an IBM TS3500 library of maximum storage capacity of about 6 PB.

Avitohol

The supercomputer Avitohol was at 331st place in the TOP 500 list of supercomputers. It is built with HP Cluster Platform SL250S GEN8 (150 servers), Intel Xeon E5-2650 v2 8C 2.6GHz CPUs (300 CPUs), non-blocking InfiniBand FDR, 300 Intel Xeon Phi 7120P co-processors. It provides 412 TFlops of performance for diverse scientific and industrial applications. Users from science and industry with substantial computational needs use it to achieve their results faster and to solve bigger problems that are beyond the reach of ordinary clusters.

Isabella

Isabella consists of 135 worker nodes with 3100 processor cores, 12 GPUs and 756 TB data space. As a shared resource of all scientists in Croatia, it allows using significant computational resources in demanding data processing of scientific and research projects.

PARADOX

PARADOX-IV cluster represents the fourth major upgrade of the PARADOX cluster and became operational in September 2013. The cluster consists of 106 working nodes and 3 service nodes. Working nodes (HP ProLiant SL250s Gen8, 2U height) are configured with two Intel Xeon E5-2670 8-core Sandy Bridge processors, at a frequency of 2.6 GHz and 32 GB of RAM (2 GB per CPU-core). The total number of new processor cores in the cluster is 1696. Each working node contains an additional GP-GPU card (NVIDIA Tesla M2090) with 6 GB of RAM. With a total of 106 NVIDIA Tesla M2090 graphics cards, PARADOX is a premier computer resource in the wider region, which provides access to a large production GPU cluster and new technology. The peak computing power of PARADOX is 105 TFlops.

One service node (HP DL380p Gen8), equipped with an uplink of 10 Gbps, is dedicated to cluster management and user access (gateway machine). All cluster nodes are interconnected via Infiniband QDR technology, through a non-blocking 144-port Mellanox QDR Infiniband switch. The communication speed of all nodes is 40 Gbps in both directions, which is a qualitative step forward over the previous (Gigabit Ethernet) PARADOX installation.

Cyclone

The Cyprus Institute provides the Cyclone cluster. It has a theoretical peak performance of 600 TFlop/s. It consists of 17 compute nodes and 16 GPU nodes and is the new production HPC system of The Cyprus Institute since its deployment in 2020. All nodes are equipped with two Intel Xeon Gold 6248 CPUs. The GPU nodes have 4 NVIDIA Tesla V100-SXM2 32GB each. The memory on the compute nodes is 96GB and on the GPU nodes is 192GB. The machine has a flash storage capacity of 135TB and is also connected to the 3PB HPC storage. An HDR100 Infiniband network connects all the system components.

Leo HPC

Leo HPC is a cluster-type machine located in Wigner DC, Budapest. The overall processing power of the 1344 CPU cores and the 252 GPUs is around 254 Tflops. Concerning the storage capacity, a total of 585 TB can be used for computational purposes. More than 380 projects have used the Leo cluster so far, and nearly 850,000 tasks have been submitted since its start. Over the years, approximately 70 disciplines have been registered, such as theoretical/computational chemistry, biology, physics, etc.

In total, five different cloud instances are on-boarded within the framework of the NI4OS-Europe project. The amount of allocated VM-cores for the open call purposes is given below.

System

Allocation for the open call

VM-cores

FINKI

140

ICIPRO

64

Avitohol

80

GCoud.ge

64

ASNET-AM

16

 

FINKI

FINKI is an Openstack-based cloud infrastructure deployed at the Faculty of Computer Science and Engineering, UKIM. FINKI is hosted on 15 Huawei servers, each with 128GB RAM and 20 HT CPU cores, totalling 300 vCPU cores and 37TB SSD and 32 TB SAS storage. The system has been in production since 2017 as a National cloud system. The connectivity to the Internet is 1 Gbit through MARNET provided link to GEANT. Currently, the system hosts templates for all popular Linux distributions and Windows variations.

ICIPRO Cloud

ICIPRO offers Infrastructure as a Service service (IaaS) to Public Sector beneficiaries that need flexibility, modularity, dynamics, and access to state-of-the-art technologies. Currently, there are three types of subscriptions available for the virtualization platform, with the following characteristics: Bronze, Silver, and Platinum. Details can be found in https://www.icipro.ro/doc/EN%20-%20Manual%20Tenants.pdf.

Avitohol

The Avitohol Cloud service allows users to launch virtual machines on servers from the Avitohol supercomputer described above. It allows user groups to launch long-running virtual machines with substantial flexibility. It is used by diverse research groups, which need for both advanced computing and data storage.

GCoud.ge

GRENA is offering a cloud service – GCloud. Besides the standard IaaS (Infrastructure as a Service) platform, GRENA offers a wide range of applications that can be installed automatically within a few minutes. Additionally, we have integrated various useful services for developers to make their work easy. Details can be found at https://www.gcloud.ge/.

ASNET-AM Cloud

ASNET-AM cloud is based on Openstack and deployed at the Institute for Informatics and Automation Problems of NAS RA, Yerevan, Armenia. ASNET-Cloud provides Infrastructure as a Service (IaaS) to academia and stakeholders based on OpenStack middleware. The users launch virtual machines (1-64 CPU cores) via a dashboard distributed in the three zones (596 CPU cores in total).

 

 

Data analysis service or PARADOX Hadoop cluster consists of a single name node that runs the YARN resource manager, and three additional data nodes. The name node is hosted on a machine with a 4-core Intel Xeon E3-1220v3 CPU running at 3.1 GHz, with 4 GB of RAM, and 500 GB of local hard disk storage. Each of the data nodes, which perform the computation and storage, are hosted on machines with 24-core Intel Xeon E5-2620 CPUs at 2.4 GHz, with 64 GB of RAM and 2 TB of storage. In total, the cluster provides access to 60 CPU cores, 180 GB of RAM and 5.3 TB of storage in HDFS.

In the analysis of very large datasets, the movement of data can present a far more severe bottleneck than the actual computation. Therefore, the PARADOX Hadoop cluster is designed to overlap computation and data storage operations, i.e., to enable performing of computation on the same machine(s) that store the corresponding data.

For the open call purposes, 200,000 CPU-hours of the Data analysis service are allocated.

 

 

ARIS archival

Data archiving is the practice of moving data that is no longer being used or are being used on a less frequent fashion into a separate storage device. It is a single set or a collection of historical records specifically selected for long term retention and future reference. The Archival service is based on the tape-based tertiary storage of the ARIS HPC system.

Projects accepted in the open call will be offered with 10 TB of storage space.

Simple storage service

The Simple Storage Service (SSS) is a secure data storage service provided to researchers for storing and sharing research data as well as keeping it synchronized across different devices. SSS is functionally similar to Dropbox, Office 365, or Google Drive. Files are stored in conventional directory structures, accessible via WebDAV. User files are encrypted during transit and can be synchronized with local clients running Windows, macOS, or various Linux distributions. The service is based on the NextCloud platform.

Projects accepted in the open call will be granted 100 GB of storage space at the Simple storage service per created user account.

RePol – Repository Policy Generator

RePol – Repository Policy Generator is an open-source web application that guides users through the process of defining policies for repositories and web-based services. It helps in defining and maintaining comprehensive and clear repository and privacy policies. Generated privacy policies are suitable for any kind of service. RePol uses a step-by-step wizard and self-explanatory forms to guide users through the process. By choosing options in a form, users shape a policy document with predefined policy clauses formulated in line with the current best practice. The resulting policy document may be downloaded as an XML file, additionally customized, and integrated into the service or repository. The collected data and the key elements of the generated policy are provided in a machine-readable format. This allows for an automated interpretation of created policies and extraction of repository-level metadata for inclusion in registries, catalogues and various operational and data discovery tools. The resulting policy document may be downloaded, additionally edited, and integrated into a repository.

RePol is a free service, and it is publicly available. It does not require registration. We will fully support projects from the open call using this service. It is supported via the project’s helpdesk.

LCT – License Clearance Tool

LCT aims to facilitate and automate the clearance of rights (copyright) for datasets, media, software and other content before they are released under an open licence or stored at a publicly trusted FAIR repository. It helps in the certification of datasets and other outputs in terms of licence compatibility analysis and selection as well as other related constraints. LCT helps in open research data management and certification for data repositories, aligning with activities and results of INFRAEOSC-5c.

LCT check for equivalence, similarity and compatibility between licenses if used in combination, particularly for derivative works. In one scenario, the user (data manager) aims to find an appropriate open-source licence for the set of the elements with separate licences or to select a licence for derivative work based on the content or components with various licences or that are not licensed at all. In the second scenario, the user declares the desired out-license and verifies the compatibility of the existing in-licences with the derivative work, also getting the options for licensing of the existing unlicensed content.

The LCT user may register or use it as a guest. The data provided by the guest is not preserved after the report is produced. For the authenticated user, the content and all parts of the procedure are kept in the licensing clearance history and user history, allowing to resume the work or share the work and data with others. Clearance with LCT is not bound to the user who initiated the procedure and can be continued by others with granted access.

RoLECT – EOSC RoP Legal & Ethics Compliance Tool

This tool aims to help in addressing the need of researchers to publish in FAIR/open modes. RoLECT targets open and FAIR assessors’ needs in terms of IPR, ethics and data protection compliance both at the policy and legal level and aligned with the EOSC governance. RoLECT aims at providing an aggregated procedure for legal and ethics compliance by integrating a set of model procedures including: model procedures for copyright acquisition, management and dissemination policies; model copyright clearance processes, documentation and tools; model data protection (GDPR compliant) processes, consent forms and data sharing agreements; decision support trees for data protection policies; model IPR and data protection documentation.

The intended use of the tool is to provide an aggregated guided assessment for EOSC Rules of Participation (RoP) focusing on legal and ethical aspects of compliance. Targeted users may be service providers, researchers and research organisations. The RoLECT platform will eventually evolve to automatically check the validity of the provided resources for at least the obligatory steps of the assessment.

RoLECT is fully operational and stable and will be aligned with the forthcoming input from the EOSC RoP Task Force.

dion Content

Application-specific (Thematic) services

RS2C Remote Sensing Scene Classification

RS2C is a RESTful web service and web application for remote sensing scene classification based on convolutional neural networks. Currently, ResNet-50 pre-trained on ImageNet and fine-tuned on MLRSNet is used for classification. The web service is implemented in Python using TensorFlow Serving and Flask. The RS2C API provides methods for single- and multi-label classification.

Clowder4DCH

The scope of the “Clowder4DCH” (C4DCH) service (https://clowder.hpcf.cyi.ac.cy/) is to offer a highly extensible active curation-based research data management platform. It enables users to form an online collaborative environment to support research communities and activities, and disseminate results. Clowder is a web-based data management system that allows users to share, annotate, organize and analyze large collections of datasets. It provides support for extensible metadata annotation and distributed analytics for automatic curation of uploaded data. In our use case, C4DCH gives the user the chance to organize files in three different ways, datasets, spaces and collections.

CHERE

One-stop shop for digitizing cultural heritage.

CHERE Tools stands for Cultural Heritage Repository Tools and represents a set of web-based tools. It aimed at people working in cultural heritage preservation and digitization, but is not limited to those who use it as individual services since it can be used in a variety of ways. The service currently provides the following functions:

  • Structure from Motion – reconstruction of a textured 3D object from a series of photographs of the object.
  • Measurement of 3D objects – either reconstructed or user-provided.
  • Conversion of BigBlueButton meetings’ recordings to standalone video files.

FEPrepare

FEP prepare is a web server, which automates the set-up procedure for performing NAMD/FEP simulations. Automating free energy perturbation calculations is a step forward to delivering high throughput calculations for accurate predictions of relative binding affinities before a compound is synthesized, and consequently, save enormous time and cost.

DREAMM

DREAMM is a novel machine learning tool that predicts the protein-membrane interfaces of peripheral membrane protein, and optionally predicts binding sites near the predicted membrane-penetrating residues in protein conformational ensembles. As an output, the user can retrieve the membrane-penetrating residues in a .csv file and if the user’s choice was to predict binding sites, a .zip file will be downloaded including the abovementioned .csv file, the binding pocket predictions, the visualizations, and summarized the binding site clustering results.

NanoCrystal

NanoCrystal is a novel web-based crystallographic tool that creates nanoparticle models from any crystal structure guided by their preferred equilibrium shape under standard conditions according to the Wulff morphology (crystal habit). Users can upload a .cif file, define the Miller indices and their corresponding minimum surface energies according to the Wulff construction of a particular crystal, and specify the size of the nanocrystal. As a result, the nanoparticle is constructed and visualized, and the coordinates of the atoms are output to the user.

ChemBioServer 2.0

ChemBioServer is a web server for filtering, clustering and networking of chemical compound libraries facilitating both drug discovery and repurposing. It provides researchers the ability to (i) browse and visualize compounds along with their physicochemical and toxicity properties; (ii) perform property-based filtering of chemical compounds; (iii) explore compound libraries for lead optimization based on perfect match substructure search; (iv) re-rank virtual screening results to achieve selectivity for a protein of interest against different protein members of the same family, selecting only those compounds that score high for the protein of interest; (v) perform clustering among the compounds based on their physicochemical properties providing representative compounds for each cluster; (vi) construct and visualize a structural similarity network of compounds providing a set of network analysis metrics; (vii) combine a given set of compounds with a reference set of compounds into a single structural similarity network providing the opportunity to infer drug repurposing due to transitivity; (viii) remove compounds from a network based on their similarity with unwanted substances (e.g. failed drugs) and (ix) build custom compound mining pipelines.

Ingredio Application

Ingredio application is a natural processing language (NLP) application that offers a pipeline of three services related to the biomedical text. The application classifies biomedical text based on certain features of its content, extract compound names and infer causal relations from the text; however, it is experimental and is not meant to replace human curation. Its main use is to showcase how this can be used as a high-throughput and high precision language filtering software for large scale biomedical data.

OpenBioMaps

OpenBioMaps is a web-based, open-access database framework project maintained by the OpenBioMpas Consortium and the databases involved are at least partially open-access or contain free content. The OpenBioMaps provides an open-access web application, which is designed to create and use open-content biological databases, specifically for scientists and conservationists, and its customizable toolset allows for the easy access and management of data.

Reduce and Visualize Gene Ontology

REVIGO is a web server that summarizes long, unintelligible lists of Gene Ontology (GO) terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views.

eeghub.ge

EEGHUB.GE (http://eeghub.ge) is a Big Data EEG (Electroencephalogram-Brain Electrical Activity) online dataset in Georgia. The service is free for European (or national) researchers following the principles of findability and accessibility. Service has a convenient search engine, which allows users to identify any recordings that correspond to specific requirements. The recordings are easily accessible and can be downloaded for further exploitation. The target users are open-source groups of researchers/practitioners, lecturers/students, Scientific Organization, Hospitals, Universities, etc. It is envisaged that EEG collection “eeg.hub.ge” will support researchers in the field of neuroscience, psychophysiology, medicine, psychology, neurophysiology, cognitive and social science.

GRENA supported this research by providing technical assistance and computing resources for the establishment of an EEG online database portal EEGHUB.GE (http://eeghub.ge). The collected EEG data was systematized, curated, and stored in an online database in EDF format.

DICOM Network

“DICOM Network” service provide full set of functionalities for data collect, storage, distribution and exchange DICOM medical investigations. It’s implements all the standard PACS interfaces as well as integrated security features. various imagistic investigations like tomography, Roentgen, ultrasound, angiography, etc. Familiarization and working experience accumulation by medical specialists in using such systems offer obvious advantages in imagistic investigations and forming treatment decisions, allow supporting collaborative work and appealing for support from the best local and foreign specialists who have extensive experience in the field.

MelGene

The MelGene database provides a comprehensive and regularly updated field synopsis and meta-analysis of all published genetic association studies performed in Cutaneous Melanoma (CM). In addition, dozens of up-to-date meta-analyses are available for all eligible polymorphisms with sufficient data.

 

 

Gaussian API

Gaussian regression (GPR), along with other emerging machine learning techniques, has become more and more popular in computational chemistry, physics, biology and life sciences. In conjunction with the molecular dynamics simulations (MD), these approaches are rather useful for the prediction of a wide variety of molecular and materials’ properties and functionalities. However, due to the novelty of techniques, the procedures for their application as well as their validation are far from being standardized.

At the same time, GPR approach can be used to tune the parametrization in approximate computational techniques in a bias-free manner. A typical example of a popular and rather useful approximate technique is the Density functional tight-binding method (DFTB). This method aims to approximate the Density functional theory (DFT) approach, providing comparable accuracy at only a fraction of its computational expense. With DFTB, simulations on time- and length-scales, which are unfeasible with DFT, have become reality.

Aside from the above-mentioned advantage, DFTB also allows direct access to electronic properties, unlike other empirical approximate methods. This is a great advantage of DFTB, compared to other computational approaches with similar computational costs. Still, all these advantages come into play at the expense of the complication that empirical parameters need to be introduced. Due to this drawback, the method transferability (as compared to other more exact quantum chemical approaches) is significantly reduced. The DFTB segment related to its electronic structure part allows for the construction of workflows for transferable parametrization. However, the repulsive part of the potential is rather tricky to treat in this context. This service provides methods for fitting the repulsive part of the potential based on the GPR approach. The training data that can be used are DFT-DFTB energy or force residues. The methods can be applied to many elements at once, i.e. for computing the repulsive potentials in the case of molecules that contain multiple “organic elements”, such as C, H, O, etc.

Schrödinger API

In many subdisciplines of computational molecular sciences, computational physics, chemistry, biology, materials science, exact treatment and analysis of a wide variety of phenomena has to rely on the rigorous quantum description of the underlying processes. Numerous phenomena taking place in the nano-world are inherently quantum in nature. Their description and, more important, quantitative treatment, therefore, requires the usage of the apparatus of quantum mechanics. The basic paradigm of today’s “mainstream” quantum mechanics is the Schrödinger equation, which is considered as a “quantum analogue” to the famous Newton’s second law equation in classical physics. The effort required to solve the Schrödinger equation is heavily dependent on the dimensionality and complexity of the problem itself (e.g. the exact form of the Hamiltonian, number of the relevant degrees of freedom of the studied system etc.). Numerous methods have been proposed in the literature to achieve the mentioned aim. However, the available codes are most often user-hostile, the procedures for computation and generation of relevant data are non-standardized, and there is a clear lack of in-depth, thorough comparison of performances of various methods for solving the Schrödinger equation for various purposes. The proposed service will provide user-friendly (as much as possible) computational platforms for the solution of time-independent Schrödinger equation, implementing several algorithms that uses the Hermite discrete variable representation technique (DVR) approach.

OMApp (domain: Engineering & Technology)

OMApp is a cloud application for automatic image mosaicking and georeferencing. The application is designed to support several users, whereby each user can upload a set of captured images via a web interface, begin their processing and make an overview of already created maps. OMApp uses numerous open-source image processing tools and libraries, where the most computationally demanding among them can perform multi-core parallel processing, which provides better usage of the cloud resources.

Repositories

Short name

Full name

Description

CHERRY

CHEmistry RepositoRY

CHERRY provides open access to the publications, as well as to other outputs of the research projects implemented in this institution.

CeR

Central Repository of the Institute of Chemistry, Technology and Metallurgy

The aim of the repository is to provide open access to publications and other research outputs resulting from the projects implemented by the Institute of Chemistry, Technology and Metallurgy.

DAIS

Digital Archive of the Serbian Academy of Sciences and Arts

The aim of the repository is to provide open access to publications and other research outputs resulting from the projects and other activities implemented by the SASA and its institutes, as well as to ensure their long-term preservation. DAIS responds to the requirements of national and international funding bodies to share the outputs of publicly funded research and is compliant with the Open Science Platform of the Ministry of Education, Science and Technological Development of the Republic of Serbia.

Digital Library

Digital Library of University of Maribor

It supports open access to scientific, research and professional works, and research data, which are results of research and education at the University.

DKUM includes works from all University of Maribor members. Next to diplomas, master’s degrees, doctorates and other works by students it also includes reviewed publications from funded projects, electronic academic textbooks and materials, and other works whose authors are the University of Maribor staff or if they are published by the University of Maribor.

HELIX Data

Hellenic Data Service

A data catalogue and repository, with a dual role in storing and preserving data that are self-deposited by researchers and in harvesting data records from other national data sources and catalogues, such as HARDMIN.

NI4OS-Europe repository service

 

NI4OS Repository Service (NRS) is the main storage service of a community that holds “Regional Community Datasets”. The NRS is also the platform to host all kinds of additional data such as publications (and their associated data), software (or references to software), workflow descriptions (e.g. how to generate research data) or even materials targeting the general public (e.g. images, videos, etc.). NRS is integrated with a persistent identifier service, as an assigned PID is required for each digital object (item, collection, community).

Repository of Faculty of Science, University of Zagreb

 

The repository provides access to publications and research data produced by the employees and the students of the faculty. Content of the repository is open to all users for searching and downloading with clearly stated usage rights.

Repository of the Institute of Public Finance, Zagreb

 

The repository provides access to publications and research data produced by the employees of the institute, papers published in scientific journals, conference proceedings, dissertations, books, manuals, guides and complete documentation related to the Institute’s activities. Content of the repository is open to all users for searching and downloading with clearly stated usage rights.

SZTE repository of publications

 

The SZTE Repository of Publications makes the full text of publications created as a result of scientific and artistic activities at the University available for the widest possible academic audience. Depositing works at the repository secures their long term archiving, and can also increase their visibility and number of citations. This is because uploaded documents are indexed by general search engines (e.g. Google, Google Scholar) and professional databases (e.g. BASE, MTA OAI).

Social Scientific Research Documentation Centre Repository

 

The Research Documentation Centre of the Centre for Social Sciences provides information on and access to research conducted at the Centre. The metadata and some of the documents of the Research Documentation Centre (RDC) are available to all visitors, but many are restricted to registered users. The interface can be set to many languages and contains RSS feeds to alert users of new content.

University of Zadar Institutional Repository of evaluation works

 

The repository provides access to publications and research data produced by the employees and the students of the faculty. Content of the repository is open to all users for searching and downloading with clearly stated usage rights.

VideoLectures.Net

 

VideoLectures.NET is an award-winning free and open access educational video lectures repository. The lectures are given by distinguished scholars and scientists at the most important and prominent events like conferences, summer schools, workshops and science promotional events from many fields of Science. The portal is aimed at promoting science, exchanging ideas and fostering knowledge sharing by providing high-quality didactic content not only to the scientific community but also to the general public. All lectures, accompanying documents, information and links are systematically selected and classified through the editorial process taking into account also users’ comments.

Georgian Integrated Library Information System Consortium 2017

National repository of scientific works

Georgian Integrated Library Information System Consortium GILISC was founded in 2017 to assist educational institutions in their development. GILISC gives them access to the electronic databases of scientific journals, helps them to use modern electronic catalogues/integrated library systems, store their scientific works in the digital repository (openscience.ge), publishes scientific articles of their students and staff in electronic journals (openjournals.ge), helps them to increase the quality of their student’s scientific works. GILISC has been cooperating with the National Science Library of Georgia since its establishment and one of the results of their interaction is the repository openscience.ge

Meteorological and Hydrological Service of Croatia Repository

Institutional repository

The repository provides access to publications and research data produced by the employees of the institute. Content of the repository is open to all users for searching and downloading with clearly stated usage rights.

NaRDuS – National Repository of Dissertations in Serbia

National repository of PhD theses

NaRDuS (National Repository of Dissertations in Serbia) is a common portal of PhD dissertations and thesis evaluation reports from all Serbian universities. It is based on the Law on Higher Education (Amendments, Sept. 2014).

All universities are obliged to deposit basic information about the dissertation – together with the thesis evaluation report and the dissertation itself to NaRDuS within three months period starting from the date of PhD dissertation defence.

Veterinar – Repository of the Faculty of Veterinary Medicine

Institutional digital repository of the University of Belgrade, Faculty of Veterinary Medicine.

Veterinar – Repository of the Faculty of Veterinary Medicine is the institutional digital repository of the University of Belgrade, Faculty of Veterinary Medicine. The aim of the repository is to provide open access to publications and other research outputs resulting from the projects implemented by the Faculty of Veterinary Medicine.

 

 

About the application process

All proposals should be submitted electronically by clicking the the button below. 

Fill out the application form now!

The application form is also available in a pdf format in order for applicants to have the full list of questions available. Please note that you have to fill in the online form for your application to be taken into account!

NI4OS-Europe Access Team will be available to answer questions while the call is open. You can contact the access team by sending e-mail to: service-access@ni4os-europe.eu

Deadline for submission of proposals to the call is Wednesday 25th of May 2022

 

Evaluation process – assignment of resources

After the deadline of the call, the organizing committee will validate the applications, and if any clarifications are needed, they will have to be provided by the 27th of May 2022.

All project proposals collected during the open call will undergo a technical and scientific review to determine the eligibility and suitability of applications for the requested services. Applications requesting HPC/Cloud/Storage resources will also be reviewed by independent scientific reviewers from the region, considering conflict of interest and fairness issues. Applications not requiring HPC/Cloud/Storage resources will undergo a more lightweight review from scientific community leaders or other scientists.

After the review process, the NI4OS-Europe access committee will prioritize the applications based on the criteria set in the scope and criteria of access of the call.

All applicants will be notified of the final results of the evaluation. Successful applicants will receive further details regarding the resources and the process to obtain user accounts for granted resources. The project will fully support the usage of provided services via the NI4OS-Europe helpdesk.

Important dates

 

Contact

For any queries related to applications, please contact: service-access@ni4os-europe.eu

 

About

This call provides a framework for scientists to perform their work, extract and publish results based on Open Science FAIR principles. The call is designed and implemented to use and test the NI4OS-Europe services, which are part of the European Open Science Cloud. These services are thematic services, generic services, as well as repositories.

National Initiatives for Open Science in Europe – NI4OS Europe, is a 3,5 year project that aims to be a core contributor to the European Open Science Cloud (EOSC) service portfolio, commit to EOSC governance and ensure inclusiveness on the European level for enabling global Open Science.

The project kicked-off in September 2019 and the consortium consists of 22 eInfrastructure and Open Science partners in 15 Member States & Associated Countries.

The NI4OS-Europe project is funded by the European Commission under the Horizon 2020 European research infrastructures grant agreement no. 857645.