Identification and evaluation of currently available electronic lab notebook solutions for the use within the Berlin University Alliance

Identification and evaluation of currently available electronic lab notebook solutions for the use within the Berlin University Alliance Sven Paßmann and Fadwa Alshawaf Humboldt-Universität zu Berlin Abstract The Berlin University Alliance (BUA) is committed to strengthening research data management (RDM) practices in support of Open Science and in alignment with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). As part of the CARDS project (Collaboratively Advancing Research Data Support), a range of tools and frameworks are being developed to promote resource sharing and foster a collaborative RDM ecosystem across the Alliance’s four partner institutions. Within this context, our sub-project aims to develop a comprehensive strategy for the integration of electronic lab notebooks (ELNs) tailored to the diverse needs of BUA researchers. A key focus lies in conducting detailed needs assessments and evaluating currently available ELN solutions with respect to scalability, cost, interoperability, discipline-specific adaptability, and long-term sustainability. Particular attention is given to the role of open-source ELNs and their community-driven development, which offers flexibility in integrating external devices and customizing workflows across various disciplines. We also examine critical challenges such as administrative overhead, transferability of data, interoperability of ELN solutions, and the limited adoption of standardized export formats, which influence the long-term viability of ELN implementation. Through this evaluation, we aim to identify ELNs that not only meet current institutional requirements but also support futureproof, FAIR-aligned data practices for a large-scale academic setting. This paper serves as a transparent record of the criteria, evaluations, and strategic considerations guiding our recommendation for an ELN solution across the BUA. It documents the assessment process that informs the selection of an ELN for the BUA. Sven Paßmann 0000-0001-9251-8269 Fadwa Alshawaf 0009-0004-2091-1802 Corresponding Author: sven.passman[email protected]e Cite: Paßmann, S., & Alshawaf, F. (2025). Identification and evaluation of currently available electronic lab notebook solutions for the use within the Berlin University Alliance. Zenodo. https://doi.org/10.5281/zenodo.17876025 Introduction In empirical and experimental research, digital recording and annotation of laboratory work are integral to good scientific practice in research data management (RDM). For a long time, research work relied on analogue methods and tools for generating, collecting, and archiving data. In many laboratories, paper lab notebooks (PLNs) were essential for planning, conducting, recording, and documenting experiments. However, the advent of digitization has profoundly transformed research practices. As digital transformation advances, these analogue tools are increasingly being replaced by digital alternatives designed to enhance efficiency, collaboration, security, and the long-term preservation of information and knowledge. One of the most significant outcomes of this transformation is the way research data is stored and managed. While digital tools offer many advantages, they have also introduced new challenges. The multitude of possibilities has led to data being scattered across multiple locations, including personal computers, local drives, cloud storage, institutional servers, instrument PCs, paper notebooks, and external hard drives. This fragmentation is further compounded by a lack of standardization in file formats, persistent identifiers (PIDs), ontologies, and comprehensive documentation throughout the data lifecycle (Manu & Gala, 2019). Additionally, documenting data to meet compliance requirements can be labour-intensive and prone to oversights, often omitting critical details. To fully maximize reuse, research data must be well-structured and machine-readable. This raises the central question of how to identify an ELN that meets BUA-wide requirements while ensuring long-term interoperability and FAIR-aligned data practices. Electronic laboratory notebooks as a solution To address these challenges, electronic laboratory notebook (ELNs) have emerged as a digital alternative to PLNs, offering a more structured and efficient approach to data documentation and management. ELNs replace traditional PLNs by providing systems to create, store, retrieve, and share records in compliant ways (Vandendorpe et al., 2024). These tools are known by various names, including electronic laboratory notebooks, digital laboratory notebooks, electronic field notebooks, and electronic engineering logbooks. ELNs not only emulate the core functions of PLNs but also introduce advanced features that enhance data documentation, sharing, and compliance with international policies. As research environments become increasingly data-driven, demand for institution-wide ELN implementation has grown significantly in recent years. This solution provides a modern, efficient, and secure way to document laboratory activities, enhancing data exchange, accessibility, and security. It enables the standardized recording of experimental details, results, and observations while allowing researchers to share data, collaborate on experiments, and exchange comments in real time. ELNs also automate and streamline the data recording process, providing functions for categorization, tagging, and data storage, improving retrievability and traceability, aligning with FAIR principles. Another key advantage is that ELNs record user identity, date, and time for each action through authentication and identification, which supports verification processes, such as those related to patents. The integration of cloud technology further enhances ELN functionality, enabling secure remote access and seamless collaboration among researchers worldwide. Some ELNs also include built-in analysis and visualization tools. Additionally, integrating an ELN with laboratory instruments, when applicable, and other information systems enable the direct transfer of measurement data and metadata, improving research efficiency, data quality, and collaboration among researchers. Given these advantages, ELNs are increasingly adopted across research and development settings, including industry, academia, and hospitals, to encourage efficient research data management and foster collaboration. For example, ELNs play a crucial role in ensuring Good Research Practice (GRP; Deutsche Forschungsgemeinschaft, 2025; MRC Working Group, 2012) by enabling transparent tracking and tracing of research workflows. They also support the FAIR data principles (Wilkinson et al., 2016) by optimizing the assignment of metadata, tags, and persistent identifiers (PIDs), enhancing the findability, accessibility, interoperability, and reusability of research data. These advantages, along with the growing demand for systematic RDM over the years, led the Berlin University Alliance (BUA)1 to conclude that a solution should be made available centrally to the partner institutions organised within the BUA. The project CARDS The Berlin University Alliance consists of four institutions: Freie Universität Berlin (FU), Humboldt-Universität zu Berlin (HU), Technische Universität Berlin (TU), Charité – Universitätsmedizin Berlin (Charité). It was founded to implement joint projects between these four institutions under one single umbrella organisation. One of the goals of the BUA is to create an IT infrastructure that provides a shared, secure, and controlled environment where data can be collected, processed, analysed, stored, and shared. Various BUA-funded projects are dedicated to this topic. One of these is the project "Collaboratively Advancing Research Data Support" (CARDS, 2024–2026, see Table 1) focusing on the sustainable development and expansion of tools, services and educational offers for research data management (RDM) within the BUA. Table 1. Subprojects of the BUA-funded project CARDS (Collaboratively Advancing Research Data Support) TP1 Implements the open source software "Research Data Management Organiser (RDMO)", enhanced with BUA-specific extensions to simplify and improve research data management planning for BUA researchers. TP2 A Data Steward will implement RDM measures for research groups within clusters of excellence to increase both internal and, when applicable, external data usability TP3 Expands RDM competency development and training programs to embed RDM expertise within institutions, meet BUA requirements, and establish cooperative connections with other regional and national initiatives. 1 Berlin University Alliance (2025-12-10). Homepage of the Berlin University Alliance. berlin-universityalliance.de https://www.berlin-university-alliance.de/. TP4 Identifies the specific requirements and expectations of BUA partners regarding an electronic lab notebook (ELN) solution and develops a concept for introducing an ELN system within BUA. Here, the fourth sub-project focuses on piloting electronic laboratory notebooks and, based on the experience gained in the piloting phase, is developing an operating and architecture model for an at least one permanent, centralised ELN offering at the BUA in collaboration. The rationale for this strategic approach arises due to the fact that various research groups and departments at the BUA institutions have already started using ELN applications such as the commercial Labfolder, as well as eLabFTW, Chemotion, NOMAD, Open Enventory and openBIS (all references can be found on Finder2). As there is currently no centrally managed ELN application for BUA institutions, the incompatibility of ELN tools would have hindered collaboration between the universities of excellence and thus efficient RDM, which in turn would have affected the quality and reusability of the collected data. However, a centralised software solution must be able to strike a balance between the flexibility to cover the workflows of different disciplines and specific functions that meet the requirements of certain academic areas as well as the individual workflows of specific research groups. This is even more essential in a research cluster as large as the BUA with more than 20.000 researchers. In the following, we evaluate the available ELN tools based on requirements of the BUA partner institutions leading to the selection of a suitable, comprehensive ELN solution by weighing flexibility and scalability against compliance with the FAIR principles (Wilkinson et al., 2016). Challenges The selection of an ELN is – among others – based on considerations such as user-friendliness, technical requirements and legal principles (including data protection), which should always be aligned with user needs (ZBMed, 2020) and reviewed in relation to local circumstances (ZBMed, 2020; Dirnagl & Przesdzing, 2016). While the latter aspects are set out in so-called framework service agreements at the institutes (FSA), legal aspects (related to data protection) are regulated in European and national legislation (General Data Protection Regulation, GDPR3; Bundesdatenschutzgesetz, BDSG4). The legal aspects, in turn, can be further clarified by institutional guidelines, which are often based on FAIR (Wilkinson et al., 2016) and open science principles (Vincente-Saez & Martinez-Fuentes, 2018). The BUA faces a particular challenge when it comes to the criteria for selecting a specific ELN. Although the GDPR and the BDSG apply equally to all partner institutes, the policies and FSAs of the institutions differ in some respects. Moreover, the Charité is administratively linked to the FU and HU and therefore does not maintain an independent research data policy. However, an IT-specific FSA has been drawn up there, given that patient data is also processed using digital 2 TU Darmstadt. (2025-12-10). ELN Finder Home. eln-finder.ulb.tu-darmstadt.de. https://eln-finder.ulb.tudarmstadt.de/home. 3 Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) [2016] OJ L 119/1 4 Federal Ministry of Justice and Consumer Protection. (2025-12-10). Federal Data Protection Act. gesetzeim-internet.de. https://www.gesetze-im-internet.de/englisch_bdsg/englisch_bdsg.html. services in addition to research. In addition, no generally IT-FSA is currently in use at the TU and FU. In its policy, the FU5 provides the most comprehensive information regarding the handling of research data. Requirements for metadata linked to research data are already mentioned here, and the documentation of data generation, processing, indexing and analysis of relevant methods and tools is highlighted as a central point. The latter point is only referred in the HU6 policy, while metadata is addressed in the TU policy. However, the TU7 has specific recommendations for handling research data in addition, specifying many aspects in a similar way to the FU policy. All policies share a commitment to the FAIR and open science principles. The IT-FSAs of HU8 and Charité9 indicate that no service may be misused for behavioural monitoring services must be barrier-free and must enable compliance with user data protection regulations. Another challenge in selecting an ELN is the number of potential users in the BUA. All four partner institutions employ around 20,000 researchers covering a very broad spectrum of disciplines – with varying requirements in terms of user-friendliness, workflows and specific needs for ELN functions. An ELN to be selected (unless no one is considering an ELN portfolio) must be suitable for the majority of researchers – knowing that it is not possible to cover all needs. One way to compensate for this gap in coverage is to develop further an ELN independently. This is possible, though, only when the source code of a software is freely available (so-called open-source), which would allow the BUA to develop the specific requirements necessary for its partner institutions itself and make them available to researchers. Identification of ELNs To identify an ELNs suitable for the BUA which also meets the principles of Open Science (Vincente-Saez & Martinez-Fuentes, 2018) and FAIR principles (Wilkinson et al., 2016), we collected relevant information from multiple sources. Step 1: Identifying Available ELNs 5 Freie Universität Berlin. (2025-12-10). Team Forschungsdatenmanagement Home. fu-berlin.de. https://www.fu-berlin.de/sites/forschungsdatenmanagement/policy/index.html. 6 Humboldt-Universität zu Berlin. (2025-12-10). Research data policy of the Humboldt-Universität zu Berlin. cms.hu-berlin.de. https://www.cms.hu-berlin.de/de/dl/dataman/policy. 7 Technische Universität Berlin. (2025-12-10). Research data policy of the Technical University Berlin. tuberlin.de. https://www.tu.berlin/ueber-die-tu-berlin/organisation/rechtliches/richtlinienleitlinien/forschungsdaten-policy. 8 Humboldt-Universität zu Berlin. (2025-12-10). IT framework service agreement of the HumboldtUniversität zu Berlin. gremien.hu-berlin.de. https://gremien.hu-berlin.de/de/amb/2018/1111/111_2018_it-rahmendienstvereinbarung-der-hu_druck.pdf. 9 Charité University Medicine Berlin. (2025-12-10). IT framework service agreement of the Charité University Medicine Berlin. klinikpersonalrat.charite.de. https://klinikpersonalrat.charite.de/fileadmin/user_upload/microsites/sonstige/Klinikpersonalrat/Diens tvereinbarungen/20230509_DV_Einf%C3%BChrung_und_Anwendung_von_IT_Systemen_01.pdf. We began by identifying existing ELNs using the publications by Rubacha et al. (2011) and Higgins et al. (2022), as well as the online resource ELN-Finder10, hosted by Technische Universität Darmstadt (Technical University Darmstadt). We selected ELN-Finder as the primary reference due to its structured feature catalog, which enables reproducible comparison across tools. Since Higgins et al. (2022) provide the most up-to-date overview (compared to the somewhat outdated publication by Rubacha et al., 2011), but do not cover all ELNs compared to the ELNFinder, we conducted our own research to verify the current availability of ELNs to ensure that our information is up to date. For this purpose, we reviewed the internet addresses provided in the sources and/or searched for information using search engines such as Google. Step 2: Evaluating ELNs for Open Science and FAIR Principles Given that ELN Finder provides the most detailed information regarding the features of ELNs (compared the other sources), we have used it as a basis for evaluating ELNs in terms of open science and FAIR principles. We gathered information regarding several aspects (software type, payment model, provider location, customization options for user interfaces, integration with secure online services and external devices, compliance with data sovereignty requirements, supported operating systems, and regulatory compliance) and cross-checked through independent research by reviewing the available information on ELNs websites and documentations if available. Furthermore, we took into consideration that with the growing commitment to open and FAIR data, and given limited financial resources — particularly for scalable solutions — open-source and freely available applications are highly valued at both the university and working group levels. So, we used these two differentiation categories, open-source/proprietary and free/paid, to classify ELNs and to evaluate the different aspects in relation to the needs specified in the chapter above (next chapter). Evaluation Of Available ELNs By consolidating data from Rubacha et al. (2011), Higgins et al. (2022), and ELN-Finder11, we identified 92 ELNs currently available on the market. However, Rubacha et al. (2011) and Higgins et al. (2022) do not provide details on the specific features of the ELNs they list. Thus, we focused our further analysis on the 39 ELNs which ELN-Finder lists as currently available and verified systematically the accuracy and relevance of its data. One of the key questions is the one about specific software licences and payment models as it is likely to be of particular interest to scientific institutions due to financial challenges and the possibility of independently developing these tools in line with individual requirements. Thirteen of the 39 ELNs are open-source, but only eleven are available completely free of charge. RSpace and SciNote, are only available for a licence fee, even though they are open-source. Please note that even with open source software and freely available software, additional costs may arise, for example for support contracts, operating expenses for implementation and maintenance, and user training, which may also be incurred with paid systems. The remaining 26 ELNs are proprietary, commercially available solutions (see Table 2 for further details). 10 TU Darmstadt. (2025-12-10). ELN Finder Home. eln-finder.ulb.tu-darmstadt.de. https://elnfinder.ulb.tu-darmstadt.de/home. 11 TU Darmstadt. (2025-12-10). ELN Finder Home. eln-finder.ulb.tu-darmstadt.de. https://elnfinder.ulb.tu-darmstadt.de/home. Table 2. Overview of suitable operating systems for ELNs. Note, open-source ELNs in bold font are fee-based. All references can be found on ELN-Finder. open - source N = 13 AI4Green, Chemotion, eLabFTW, HERBI, Kadi4Mat, Labintegrated Data, NOMAD ELN, OpenEnventory, openBIS, PASTA ELN, RSpace, SampleDB, SciNote, proprietary N = 26 Agilent SLIMS, Arxspan, Benchling Notebook, BIOVIA Notebook, CDD Vault, Dotmatics Platform ELN, ecLabNote, eLabJournal, IDBS e-WorkBook, LabArchives, LabCloud, LabCollector, Labfolder, LabGuru, LABII ELN, Labstep, LabWare, Limsophy, LOGS ELN, Mbook Chemistry, NuGenesis, quattro/LJ, Sapio ELN, SciCord, SciFormation, Uncountable Since the BUA is a very large science cluster with about 20.000 researchers, the scalability is inherently tied to costs. Even though scalability fundamentally depends on the host's resources, such a potential scale also has corresponding consequences, e.g., increases in administrative support and costs regardless of whether management is handled internally (e.g., across different departments) or outsourced to the provider. It is therefore essential to evaluate whether a selfhosting remains more cost-effective than a user-based licensing scheme, especially since commercial licenses often include support services. Given that most ELNs are proprietary, they run a per-user annual licensing model — ranging from approximately €200 to as much as $2,400. On the other side, open source does not necessarily mean free of charge: two of the most common open-source ELNs, RSpace and SciNote, even though they are open-source projects, their functional full versions require institutional licenses. However, even if you opt for an ELN without a fee model, there are still administrative costs. Although they offer support for a fee, it is worth calculating precisely whether this is worthwhile and under what conditions it takes place (e.g., can hosting also be provided on your own local servers, or do you have to use the operator's servers). Open-source ELNs, often free of licensing fees, offer a promising solution to reduce such costs by a significant amount. Yet it should not be forgotten that even free software involves costs such as implementation, administration, training and maintenance. While some of these responsibilities can be outsourced to providers or freelance experts (e.g., through support contracts), they should be factored into institutional workflows and sustainability models, alongside other considerations discussed in detail elsewhere (Dirnagl & Przesdzing, 2016; Higgins et al., 2022; Vandendorpe, 2024). However, a key advantage of open-source ELNs lies in the strength and engagement of their user communities. By leveraging publicly available source code, these communities actively contribute to further development, particularly in adapting the software to subject-specific needs or integrating external devices and third-party tools. This is particularly advantageous for the BUA, which, unlike a single institution, has to cover the needs of many thousands of researchers and a much wider range of research questions and approaches. Beyond these rather general issues, however, the BUA still faces very specific challenges. While an institution must consider the needs of their researcher and adhere to its own guidelines when introducing new tools, this is a much greater challenge for a research cluster as large as the Berlin University Alliance. Aspects such as researchers' needs, IT framework service agreements and policies for handling research data must be taken into account not only by one, but by four institutions. This requires, more than usual, a balance between functionality, flexibility and, above all, compliance with the various guidelines and framework agreements for services. In addition, many disciplines that do not traditionally rely on lab notebooks must first become familiar with the concept of an ELN. Yet the increasing demands from funding bodies and scientific journals for robust research data management (RDM) plans and strategies for FAIR data practices apply across all fields. In order to match these issues, you need to find an ELN which works for the most of the disciplines and matches the needs of the majority of researchers. Thus, you have to consider when implementing an ELN in a research workflow whether it should be generic or discipline-specific (Vandendorp et al., 2024). In general, it is difficult to make a clear distinction between so-called generic and disciplinespecific ELNs. Many ELNs (e.g., RSpace, Labfolder, eLabFTW) are designed to be easy to use with a simple user interface and adaptable to individual needs, making them accessible to a wide range of disciplines. On the other hand, some ELNs have been developed within specific disciplines (e.g., Chemotion, NOMAD) reflecting the underlying workflows in that field. These ELNs also feature the editors and tools necessary for that discipline to adequately document data (e.g., documenting certain types of data, such as chemical formulas or DNA code snippets). Such aspects are also integrated in some ELNs mentioned at the beginning (e.g., RSpace, eLabFTW, etc.) or are in the planning stage in order to make them usable for specific subject areas. This openness to other disciplines is much more difficult for ELNs developed in a specific environment, even though efforts12 are being made in this regard. As a rule, so-called generic ELNs are in the majority compared to those developed in a specific discipline environment. Most of the latter are proprietary and require a purchase (e.g., Benchling, ecLabNote, LabGuru, Mbook Chemistry), and just a few less are open-source and freely available (e.g., Chemotion, NOMAD, OpenEnventory). In order for the BUA to meet the needs of as many researchers as possible, such specialised ELNs are rather unsuitable unless extensive adjustments are made. This is particularly true since such adjustments based on the needs of researchers can then only be implemented with open source code or by submitting extensive requests to the software operator, who will only consider this from a market economy perspective (or in return for appropriate payment). As a result, it is advantageous for the BUA to rely on generic ELNs since features such as customization and the ability to create reusable templates, offered by most ELNs, serve as low-barrier entry points, making it easier to adopt these tools and meet emerging requirements (Nielsen, 1994). Yet the choice of a distinct generic ELN for the BUA also depends on other requirements, which may vary from institute to institute. One such requirement is compliance with legal regulations (at regional, national or EU level, i.e. the GDPR). Since the protection of personal data is primarily the responsibility of the users of an ELN, all generic ELNs are basically eligible. It would therefore be more important to clarify which functions the ELNs offer to facilitate the implementation of such requirements, e.g., through comprehensive rights and role management that can be specifically configured at different user levels. One feature that makes it somewhat easier to implement these requirements is multi-client capability. Multi-client capability refers to the extent to which an instance of an application allows the data of a research group to be viewed by users from other teams within an instance only if the appropriate rights to view and/or modify the data have been assigned. It is about the capability of an application to enable different, separate teams, each of which can make specific adjustments that are only valid for that team, and also to enable communication with external devices and/or software only for that team, without affecting other teams on the same instance. 12 LabIMotion ELN. (2025-12-10). LabIMotion Home. chemotion.net https://chemotion.net/docs/labimotion. However, it should be noted that the scope of role and rights management varies from ELN to ELN. Some ELNs are designed in such a way (e.g., eLabFTW, openBIS, Labfolder, RSpace) that it eases administration, as only one instance needs to be set up with separated team spaces managed through role-based access control. The choice in favor of an ELN with multi-client capability, though, may lead to other issues, which has to be taken into account. For example, an instance can only be set up in a specific way, so that certain settings (e.g., templates for data entry or connections to equipment) are effective across all teams. Team-specific customizations and settings (if possible, up to the API level13, as enabled by eLabFTW, for example) is therefore another criterion the BUA must consider in order to offer the greatest possible benefit to researchers. Nevertheless, the multi-client capability enables ELNs to have one advantage over their analogue predecessors: the facilitation of collaboration, both within and across research groups. Although a few tools still have limitations in this area (e.g., LOGS is primarily designed for individual users; HERBI lacks real-time functionality), collaboration features are widely supported across most ELNs, though implemented in varying ways. Version control and even audit trail, on the other hand, is a quite common feature. The same applies to the exchange of data and information, which can be done via local server hosting, as supported by LabFolder, RSpace, eLabFTW, Chemotion, NOMAD and openBIS, for example. On the other hand, all ELNs are subject to the restriction that ELN instances cannot communicate with each other – although a solution is currently being developed. For the BUA, this means that – in order to enable collaboration across the BUA's various locations – only one central instance can be set up, which can be compensated for by means of a potentially existing multi-client capability. The ELN's data storage location also plays an important role in data security. For the BUA, it is crucial that these comply with the data protection requirements applicable in the EU, which either necessitates the use of a local server or that the relevant servers are located in the EU. However, this aspect may not only be relevant for the BUA in general. Researchers of the BUA also have specific expectations regarding the location of data storage and therefore want to ensure that it is within the network of their host institution, which they consider to be secure. In this regard, the BUA can choose from a couple of ELNs supporting local data storage or even EU-hosted servers (e.g., eLabFTW, SciNote, Labfolder, RSpace). In addition to these functionalities, the partner institutes of the BUA emphasise accessibility, as it is essential for enabling as many researchers as possible to access the infrastructure. Accessibility is evaluated at the BUA institutions as part of so-called co-determination procedures when introducing new tools14,15, even if some ELNs are already proactively striving to meet the WCAG 2.1 as a standard for accessibility (e.g., eLabFTW, RSpace). Equally important are user-friendliness and the ability to adapt to the workflow of different working groups or disciplines, since improving the user’s workflow is a critical factor for user acceptance, as highlighted in Nielsen’s usability heuristics (1994). In this regard, the majority of ELNs listed in ELN-Finder offer easily adaptable interfaces tailored to user requirements. These include flexible text, table, and figure editors, as well as the ability to create custom templates for recurring procedures within a project or across multiple projects. Even if discipline-specific ELNs provide discipline-specific functions, such as editors for chemical formulas and molecular 13 Wikipedia. (2025-12-10). Application Programming Interface. en.wikipedia.org https://en.wikipedia.org/wiki/API. 14 Humboldt-Universität zu Berlin. (2025-12-10). Co-determination procedures at Humboldt-Universität zu Berlin. vertretungen.hu-berlin.de. https://vertretungen.hu-berlin.de/de/gpr/themen/IT-Datenschutz. 15 Free University Berlin. (2025-12-10). Co-determination procedures at Free University Berlin. fu-berlin.de. https://www.fu-berlin.de/sites/gpr/it-verfahren/index.html. ELN Name Compliance Security Labfolder HIPAA FDA CFR 21 Part 11, SOC2, ISO 27001, AES-256, HTTPS/SSL, SAML, MFA/2FA, etc LabArchives HIPAA FDA CFR 21 Part 11, SOC2, ISO 27001, AES-256, HTTPS/SSL, SAML, MFA/2FA, etc LOGS no data available SAML, MFA/2FA, etc Benchling GDPR, HIPAA FDA CFR 21 Part 11, SOC2, AES-256, HTTPS/SSL, SAML, MFA/2FA, etc LabCollector HIPAA FDA CFR 21 Part 11, SOC2, AES-256, HTTPS/SSL, SAML/LDAP, MFA/2FA, etc Labii ELN GDPR, HIPAA FDA CFR 21 Part 11, AES-256, HTTPS, SAML, MFA/2FA, etc SciNote GDPR FDA CFR 21 Part 11, SOC2, HTTPS, SAML, MFA/2FA, etc RSpace GDPR, HIPAA FDA CFR 21 Part 11, SOC2, ISO 27001, AES-256, HTTPS/SSL, SAML, MFA/2FA, etc eLabFTW GDPR, HIPAA FDA CFR 21 Part 11, HTTPS/SSL, SAML/LAPD, MFA/2FA, etc Chemotion GDPR HTTPS, SAML, MFA/2FA, etc Kadi4Mat GDPR HTTPS, SAML, MFA/2FA, etc PASTA-ELN GDPR no data available HERBI GDPR, DPDP, and NESA ISO 27001:2022, HTTPS, SAML, MFA/2FA, etc NOMAD no data available HTTPS, SSO, MFA/2FA, etc openBIS GDPR FDA CFR 21 Part 11, SAML/LAPD, MFA/2FA, etc Open Enventory no data available HTTPS/SSL, MFA/2FA, etc 2FA, two-factor authentication; AES, Advanced Encryption Standard; CFR, Code of Federal Regulations; FDA, Food and Drug Administration; LDAP, Lightweight Directory Access Protocol; MFA, multi-factor-authentication; SAML, Security Assertion Markup Language; SOC, Service Organization Control. ELN Name Data Export Backup Options Labfolder PDF, XHTML, JSON, etc. cloud, local server, data export LabArchives PDF, HTML, XML, CSV, XLSX, etc. cloud, data export, bi-hourly, encrypted backups LOGS no data available no data available Benchling PDF, HTML, DOCX, CSV, XLSX, PZFX, etc. no data available LabCollector PDF, HTML, XML, CSV, XLSX, etc. local server, data export, database Labii ELN TSV, XLSX, etc. API, cloud, data export SciNote PDF, HTML, CSV, XLSX, ELN, etc. s3 compatible storage, database, data export RSpace PDF, HTML, XML, DOC, etc. s3 compatible storage, local server, database, data export eLabFTW PDF, HTML, XML, CSV, JSON, ELN, etc. s3 compatible storage, local server, full virtual machine backup, manual/automated backups Chemotion HTML, DOCX, ODT, CSV, XLSX, ZIP, etc. cloud, local server Kadi4Mat ELN, RDF, etc. s3 compatible storage, local server, data export, PASTA-ELN ELN, etc. local server, database, data export, repositories HERBI no data available cloud, local server, data exports NOMAD JSON, ELN (import only), ZIP, etc. cloud, local server, database, data export openBIS PDF, TSV, XLSX, JSON, ZIP, etc. cloud, local server, database Open Enventory PDF, CSV, XLSX, XLS, SDF, etc. no data available ELN Name Collaboration and Sharing Integration with Other Software Labfolder supports collaboration, sharing possible, version control, audit trail Supports API integration with common platforms LabArchives supports collaboration, sharing possible, version control, audit trail Supports integration with external apps and databases LOGS basic collaboration options (primarily for individuals), sharing possible, version control Supports integration, requires custom configuration Benchling supports collaboration (especially for team-based research), sharing possible, version control, audit trail Multiple integrations with other lab software and databases LabCollector supports collaboration (primarily for individuals), sharing possible, version control, audit trail Basic integrations, mostly with own ecosystem Labii ELN supports collaboration, cloud sharing, version control, audit trail Integration with popular LIMS systems, external apps SciNote supports collaboration, cloud sharing, version control, audit trail Integration with external platforms supported RSpace supports collaboration ( also options via cloud), sharing possible, version control, audit trail Supports integration with external tools due to open source code, mostly with native tools eLabFTW supports collaboration (cloud and server-based), sharing possible, version control, audit trail Supports integration with external tools due to open source code Chemotion supports collaboration (cloud and server-based), sharing possible, version control, audit trail Supports integration with external tools due to open source code Kadi4Mat supports collaboration, sharing possible Few integrations, mostly internal tools PASTA-ELN supports collaboration (cloud and server-based), sharing possible Easy integration with cloud services, Wide range of integrations with data systems HERBI supports collaboration (but lacks real-time features), mainly cloud sharing Supports integration with external tools due to open source code NOMAD supports collaboration, sharing possible, version control Limited third-party integrations openBIS lacks collaboration tools for research teams, version control, audit trail Supports integration with external tools due to open source code Open Enventory supports collaboration, basic sharing features (useful for teams), version control Supports integration with external tools due to open source code ELN Name Customization and Usability Labfolder highly customizable, advanced setup required LabArchives limited customization options, user-friendly, LOGS highly customizable, interface is a bit dated Benchling customizable for molecular biology, user-friendly LabCollector some level of customization, outdated interface Labii ELN customizable fields and templates, intuitive interface SciNote customizable workflows, easy to use RSpace multiple customization options and templates, intuitive eLabFTW highly customizable, requires technical setup Chemotion customizable workflows, highly user-friendly Kadi4Mat customizable templates PASTA-ELN custom workflows and templates, good usability HERBI customization requires programming, intuitive NOMAD limited customization, easy-to-use openBIS hard to customize, intuitive Open Enventory moderate flexibility