Instance maps as an organising concept for complex experimental workflows as demonstrated for (nano)material safety research

• Benjamin Punz,
• Maja Brajnik,
• Joh Dokler,
• Jaleesia D. Amos,
• Litty Johnson,
• Katie Reilly,
• Anastasios G. Papadiamantis,
• Amaia Green Etxabe,
• Lee Walker,
• Diego S. T. Martinez,
• Steffi Friedrichs,
• Klaus M. Weltring,
• Nazende Günday-Türeli,
• Claus Svendsen,
• Christine Ogilvie Hendren,
• Mark R. Wiesner,
• Martin Himly,
• Iseult Lynch and
• Thomas E. Exner

Beilstein J. Nanotechnol. 2025, 16, 57–77, doi:10.3762/bjnano.16.7

• characterisation, exposure science, toxicology, and computational approaches, resulting in complex experimental workflows and diverse data types. Managing the data flows, with a focus on provenance (who generated the data and for what purpose) and quality (how was the data generated, using which protocol with

• which controls), as part of good research output management, is necessary to maximise the reuse potential and value of the data. Instance maps have been developed and evolved to visualise experimental nanosafety workflows and to bridge the gap between the theoretical principles of FAIR (Findable

• models to be used, and the data flows arising from study execution. Application of the InstanceMaps tool (described herein) to research workflows of increasing complexity is presented to demonstrate its utility, starting from (i) documentation of a nanomaterial’s synthesis, functionalisation, and

Integrating high-performance computing, machine learning, data management workflows, and infrastructures for multiscale simulations and nanomaterials technologies

• Fabio Le Piane,
• Mario Vozza,
• Matteo Baldoni and
• Francesco Mercuri

Beilstein J. Nanotechnol. 2024, 15, 1498–1521, doi:10.3762/bjnano.15.119

• , Turin, Corso Duca degli Abruzzi 24, Italy 10.3762/bjnano.15.119 Abstract This perspective article explores the convergence of advanced digital technologies, including high-performance computing (HPC), artificial intelligence, machine learning, and sophisticated data management workflows. The primary

• , leading to improved reproducibility and quality control. By combining these digital technologies with integrated data management workflows, materials scientists can, in principle, smoothly organize, share, and analyze large volumes of materials data, fostering collaboration and enhancing the overall

• computational workflows and minimizes manual effort. This automation not only improves efficiency but also enhances reproducibility and reduces the potential for human error. User-friendliness of software platforms and frameworks used for materials modelling tasks has also significantly improved in recent years

The steep road to nonviral nanomedicines: Frequent challenges and culprits in designing nanoparticles for gene therapy

• Yao Yao,
• Yeongun Ko,
• Grant Grasman,
• Jeffery E. Raymond and
• Joerg Lahann

Beilstein J. Nanotechnol. 2023, 14, 351–361, doi:10.3762/bjnano.14.30

• measurement. For NTA, ASTM 2834 provides workflows for planning NP experiments. Through the study of nanoscale extracellular vesicles, Bachurski et al. [68] provide some additional insights comparing the performance of different NTA systems to cryo-TEM and single-particle interferometric reflectance imaging

Bio-imaging with the helium-ion microscope: A review

• Matthias Schmidt,
• James M. Byrne and
• Ilari J. Maasilta

Beilstein J. Nanotechnol. 2021, 12, 1–23, doi:10.3762/bjnano.12.1

Nanocuration workflows: Establishing best practices for identifying, inputting, and sharing data to inform decisions on nanomaterials

• Christina M. Powers,
• Karmann A. Mills,
• Stephanie A. Morris,
• Fred Klaessig,
• Sharon Gaheen,
• Nastassja Lewinski and
• Christine Ogilvie Hendren

Beilstein J. Nanotechnol. 2015, 6, 1860–1871, doi:10.3762/bjnano.6.189

• nanocuration, 2) the influence of organizational goals or purpose on the workflow, 3) established workflow practices in other fields, 4) current workflow practices in nanocuration, 5) key challenges for workflows in emerging fields like nanomaterials, 6) examples to make these challenges more tangible, and 7

• ) recommendations to address the identified challenges. Throughout the article, there is an emphasis on illustrating key concepts and current practices in the field. Data on current practices in the field are from a group of stakeholders active in nanocuration. In general, the development of workflows for

• groups) and providing nanocuration resources (e.g., training) will likely prove crucial for the wider application of nanocuration workflows in the scientific community. Keywords: curation; informatics; nanoinformatics; nanomaterials; workflows; Introduction A tremendous growth in resources and tools to

The Nanomaterial Data Curation Initiative: A collaborative approach to assessing, evaluating, and advancing the state of the field

• Christine Ogilvie Hendren,
• Christina M. Powers,
• Mark D. Hoover and
• Stacey L. Harper

Beilstein J. Nanotechnol. 2015, 6, 1752–1762, doi:10.3762/bjnano.6.179

• the details of the interactive needs and workflows of data customers, data creators, and data analysts. Initial responses from stakeholder liaisons throughout the nanoinformatics community reveal a shared view that it will be critical to focus on integration of datasets with specific orientation

• ) provide opportunities for similar publication series on the details of the interactive needs and workflows of data customers, data creators, and data analysts. The specific objectives of the NDCI paper series include: to capture a snapshot of current nanomaterial data curation practices and issues, to

Experiences in supporting the structured collection of cancer nanotechnology data using caNanoLab

• Stephanie A. Morris,
• Sharon Gaheen,
• Michal Lijowski,
• Mervi Heiskanen and
• Juli Klemm

Beilstein J. Nanotechnol. 2015, 6, 1580–1593, doi:10.3762/bjnano.6.161

• WG established a subgroup focused on developing guidelines for data curation, and is in the process of writing a series of consensus papers on curation workflows, data completeness and quality, curator responsibilities, metadata, and integration between datasets and databases, as an overview of

• DOI-based search for samples by publication. This option is available under the Publication tab once the user has initiated a publication search. caNanoLab data submission and search workflow. A graphic available upon login that illustrates the functionality in caNanoLab. Both workflows provide active