diff --git a/docs/00_intro/10_fair.mdx b/docs/00_intro/10_fair.mdx index 2836c690..9abfed7c 100644 --- a/docs/00_intro/10_fair.mdx +++ b/docs/00_intro/10_fair.mdx @@ -5,7 +5,7 @@ slug: "/fair" ![FAIR Data](/img/topics/FAIR_data_principles.png) -Image Attribution: SangyaPundir, [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0). +_Image Attribution: SangyaPundir, [CC BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0)._ ## Introduction diff --git a/docs/00_intro/20_data_life_cycle.mdx b/docs/00_intro/20_data_life_cycle.mdx index 193c3372..c3310e90 100644 --- a/docs/00_intro/20_data_life_cycle.mdx +++ b/docs/00_intro/20_data_life_cycle.mdx @@ -26,7 +26,7 @@ You should be aware of the various **requirements** of the research funder, your ## Phase 2: Experiment/ Data Collection -**New data** is created or collected in this phase, e.g. through chemical synthesis, simulations of molecules, or measurements carried out on samples. When conducting the respective experiment, make sure that you also create or record the **relevant [metadata](/docs/metadata)** that describes the data. The [documentation](/docs/data_documentation) of the created data with all further information and metadata should be recorded in an [(electronic) laboratory notebook](/docs/eln). +**New data** is created or collected in this phase, e.g. through chemical synthesis, simulations of molecules, or measurements carried out on samples. When conducting the respective experiment, make sure that you also create or record the **relevant [metadata](/docs/metadata)** that describes the data. The [annotation](/docs/data_description_annotation) of the created data with all further information and metadata should be recorded in an [(electronic) laboratory notebook](/docs/eln). If you use existing data or samples, **clarify the rights of use**. In this case, provenance metadata may provide you with information. In addition, a link should be created between the existing data and the newly generated data. This is relevant information and helps you in the [reuse phase](#phase-6-re-use). diff --git a/docs/40_smartlab/00_smartlab.mdx b/docs/00_intro/30_smartlab.mdx similarity index 99% rename from docs/40_smartlab/00_smartlab.mdx rename to docs/00_intro/30_smartlab.mdx index 467e6c87..796be4ac 100644 --- a/docs/40_smartlab/00_smartlab.mdx +++ b/docs/00_intro/30_smartlab.mdx @@ -1,5 +1,5 @@ --- -title: "Smartlab" +title: "SmartLab" slug: "/smartlab" id: "smartlab" --- diff --git a/docs/00_intro/30_contribute.mdx b/docs/00_intro/40_contribute.mdx similarity index 100% rename from docs/00_intro/30_contribute.mdx rename to docs/00_intro/40_contribute.mdx diff --git a/docs/20_role/10_research_group_leader.mdx b/docs/20_role/10_research_group_leader.mdx index d113b154..0a0e2297 100644 --- a/docs/20_role/10_research_group_leader.mdx +++ b/docs/20_role/10_research_group_leader.mdx @@ -27,7 +27,7 @@ Digitisation of research data only **after** the end of the production process i Therefore, it is more efficient to capture the data and their corresponding [metadata](/docs/metadata) as early as from the planning of the experiment. Here, [electronic lab notebooks (ELN)](/docs/eln) facilitate everyday work considerably: the planning of the experiment, the documentation of experimental procedures, the analysis of the obtained spectroscopic data as well as the peak assignment can all be completed in one digital environment. And even better: complete experiment reports with analytical data (e.g. for the supporting information for [publications](/docs/data_publishing)) can be generated automatically by the ELN. -The time invested to set up the ELN and to organise the experiments thus pays off in numerous ways: In addition to facilitating [documentation](/docs/data_documentation), the storage of the produced data in a FAIR format in a [repository](/docs/repositories) is simplified. Also, the [data organisation](/docs/data_organisation) for the research group can be improved by setting up an internal database. This is invaluable for growing working groups. +The time invested to set up the ELN and to organise the experiments thus pays off in numerous ways: In addition to facilitating [annotation](/docs/data_description_annotation), the storage of the produced data in a FAIR format in a [repository](/docs/repositories) is simplified. Also, the [data organisation](/docs/data_organisation) for the research group can be improved by setting up an internal database. This is invaluable for growing working groups. ## How to start diff --git a/docs/20_role/20_research_group_member.mdx b/docs/20_role/20_research_group_member.mdx index 928caa66..46cc7163 100644 --- a/docs/20_role/20_research_group_member.mdx +++ b/docs/20_role/20_research_group_member.mdx @@ -11,7 +11,7 @@ This article applies to research group members (PhD students, Postdocs and other ## Motivation -As a research group member, you are the one who is doing the actual research. That means, you are generating lots of data while working practically or theoretically, e.g. analytical data or reaction protocols. All these data are accompanied by [metadata](/docs/metadata). As a scientist, you are responsible for the [documentation](/docs/data_documentation) of this data in order to ensure that the data can be archived in a [FAIR](/docs/fair) (**F**indable, **A**ccessible, **I**nteroperable, **R**e-usable) manner. Many funding institutions encourage or even enforce the publication of FAIR data. Therefore, your [supervisor](/docs/research_group_leader) should provide you with information on how to handle your data or even a [data management plan](/docs/dmp) for good [data organisation](/docs/data_organisation) practices. +As a research group member, you are the one who is doing the actual research. That means, you are generating lots of data while working practically or theoretically, e.g. analytical data or reaction protocols. All these data are accompanied by [metadata](/docs/metadata). As a scientist, you are responsible for the [annotation](/docs/data_description_annotation) of this data in order to ensure that the data can be archived in a [FAIR](/docs/fair) (**F**indable, **A**ccessible, **I**nteroperable, **R**e-usable) manner. Many funding institutions encourage or even enforce the publication of FAIR data. Therefore, your [supervisor](/docs/research_group_leader) should provide you with information on how to handle your data or even a [data management plan](/docs/dmp) for good [data organisation](/docs/data_organisation) practices. ## Data handling @@ -23,7 +23,7 @@ As a research group member, you are the one who is doing the actual research. Th In recent years, many new digital tools have been developed to support researchers with their RDM needs. The technical possibilities are briefly explained below. For more details, please refer to the linked related chapters. If you want to learn more about domain-specific data production methods, have a look at the [domain-specific profiles](/docs/role_guide). -The most efficient way to properly handle your research data and corresponding [metadata](/docs/metadata) starts when planning the experiment according to the [data life cycle](/docs/data_life_cycle) (see figure on the right). In order to have all data directly available in a digital format, the use of [electronic lab notebooks (ELNs)](/docs/eln) is strongly recommended. ELNs can support you in your daily work, from planning experiments to data processing and analysis. For example, after peak assignment in an obtained spectroscopic dataset—which can be performed entirely in one digital environment—peak lists can automatically be generated by ELNs such as the [Chemotion ELN](https://www.chemotion.net/) for theses or publications. Furthermore, ELNs are very powerful in preparing your data for [data publishing](/docs/data_publishing) in suitable [repositories](/docs/repositories) as well as for [data storage and archiving](/docs/data_storage). You are therefore facilitating future research in your working group by assembling an internal database in an invaluable manner. In addition to the group you are working in, publishing [well-organised](/docs/data_organisation) and [documented](/docs/data_documentation) research data can help other researchers significantly in terms of searching and re-using your data. [Best practice examples](/docs/best_practice) can guide you to better understand how efficient data handling works. +The most efficient way to properly handle your research data and corresponding [metadata](/docs/metadata) starts when planning the experiment according to the [data life cycle](/docs/data_life_cycle) (see figure on the right). In order to have all data directly available in a digital format, the use of [electronic lab notebooks (ELNs)](/docs/eln) is strongly recommended. ELNs can support you in your daily work, from planning experiments to data processing and analysis. For example, after peak assignment in an obtained spectroscopic dataset—which can be performed entirely in one digital environment—peak lists can automatically be generated by ELNs such as the [Chemotion ELN](https://www.chemotion.net/) for theses or publications. Furthermore, ELNs are very powerful in preparing your data for [data publishing](/docs/data_publishing) in suitable [repositories](/docs/repositories) as well as for [data storage and archiving](/docs/data_storage). You are therefore facilitating future research in your working group by assembling an internal database in an invaluable manner. In addition to the group you are working in, publishing [well-organised](/docs/data_organisation) and [annotated](/docs/data_description_annotation) research data can help other researchers significantly in terms of searching and re-using your data. [Best practice examples](/docs/best_practice) can guide you to better understand how efficient data handling works. ## Recommendations – how to start diff --git a/docs/20_role/30_student.mdx b/docs/20_role/30_student.mdx index a876c321..b9ecf903 100644 --- a/docs/20_role/30_student.mdx +++ b/docs/20_role/30_student.mdx @@ -20,15 +20,15 @@ If you want to learn more about domain-specific data production methods, you can ## Data documentation :::danger Why: -The use of [well-organised](/docs/data_organisation) and [documented data](/docs/data_documentation) plays an important role in finding, searching, and using research data throughout the [data life cycle](/docs/data_life_cycle). +The use of [well-organised](/docs/data_organisation) and [annotated data](/docs/data_description_annotation) plays an important role in finding, searching, and using research data throughout the [data life cycle](/docs/data_life_cycle). ::: :::info How: -For the [documentation of these data](/docs/data_documentation), a classic paper-based lab journal or an [electronic lab journal](/docs/eln) (ELN) can be used. +For the [description and annotation](/docs/data_description_annotation) of these data, a classic paper-based lab journal or an [electronic lab journal](/docs/eln) (ELN) can be used. ::: :::caution Considerations: -The use of a paper-based lab journal seems to be an easy and efficient way to [document data](/docs/data_documentation). But the use of an [ELN](/docs/eln) like [Chemotion](https://www.chemotion.net/chemotionsaurus/index.html) has plenty of advantages in the long run. For example, in [Chemotion](https://www.chemotion.net/chemotionsaurus/index.html) all data obtained from an experiment can be linked to your protocol, which is an easy way to have a [well-organised research data set](/docs/data_organisation) at the end of the thesis. Additionally, the reaction protocol can be exported in a [standardised form](/docs/data_formats), which is suitable for [publication](/docs/data_publishing) in the experimental section of a thesis or a paper.
Furthermore, the data are machine readable and therefore easily findable which is one aspect for [FAIR data](/docs/fair) (**F**indable, **A**ccessible, **I**nteroperable, **R**eusable). Also the other aspects should be fulfilled, this increases the machine-actionability for future use of the data. Another advantage of an [ELN](/docs/eln) is that it can be coupled with a [repository](/docs/repositories), which will ease the [publication process](/docs/data_publishing). [Choose a repository](/docs/choose_repository), that is suitable for your data. +The use of a paper-based lab journal seems to be an easy and efficient way to document data. But the use of an [ELN](/docs/eln) like [Chemotion](https://www.chemotion.net/chemotionsaurus/index.html) has plenty of advantages in the long run. For example, in [Chemotion](https://www.chemotion.net/chemotionsaurus/index.html) all data obtained from an experiment can be linked to your protocol, which is an easy way to have a [well-organised research data set](/docs/data_organisation) at the end of the thesis. Additionally, the reaction protocol can be exported in a [standardised form](/docs/data_formats), which is suitable for [publication](/docs/data_publishing) in the experimental section of a thesis or a paper.
Furthermore, the data are machine readable and therefore easily findable which is one aspect for [FAIR data](/docs/fair) (**F**indable, **A**ccessible, **I**nteroperable, **R**eusable). Also the other aspects should be fulfilled, this increases the machine-actionability for future use of the data. Another advantage of an [ELN](/docs/eln) is that it can be coupled with a [repository](/docs/repositories), which will ease the [publication process](/docs/data_publishing). [Choose a repository](/docs/choose_repository), that is suitable for your data. ::: ## Data processing @@ -42,7 +42,7 @@ Data can be processed by different software for each method. But an [ELN](/docs/ ::: :::caution Considerations: -By [documenting](/docs/data_documentation) and processing data in the same software tool synergies will be obtained. For example Chemspectra can control automatically, if the integral of the NMR spectra fits to the target molecule of the connected synthesis. After processing your data in Chemspectra you can export your data in a standardised peak list, which can be added in the experimental section of a thesis or a [publication](/docs/data_publishing). +By documenting and processing data in the same software tool synergies will be obtained. For example Chemspectra can control automatically, if the integral of the NMR spectra fits to the target molecule of the connected synthesis. After processing your data in Chemspectra you can export your data in a standardised peak list, which can be added in the experimental section of a thesis or a [publication](/docs/data_publishing). ::: ## Sharing, preserving and re-using data diff --git a/docs/30_data/00_data_guide.mdx b/docs/30_data/00_data_guide.mdx index 8c16d4d3..f7530ec9 100644 --- a/docs/30_data/00_data_guide.mdx +++ b/docs/30_data/00_data_guide.mdx @@ -23,11 +23,17 @@ Learn how to organise your data, e.g. via appropriate file naming conventions an -### Documentation +### Data Formats -Find out more about the tools, resources and software that can support you with data documentation. +Learn about the different data formats and their advantages and disadvantages. Find out which formats are suitable for your data and how to convert between them. - + + +### Data Description and Annotation + +Learn how to describe and annotate your data to make it more discoverable and reusable. + + ### Data Storage and Archiving diff --git a/docs/30_data/30_data_organisation.mdx b/docs/30_data/20_data_organisation.mdx similarity index 92% rename from docs/30_data/30_data_organisation.mdx rename to docs/30_data/20_data_organisation.mdx index e93afd40..02c0ebf6 100644 --- a/docs/30_data/30_data_organisation.mdx +++ b/docs/30_data/20_data_organisation.mdx @@ -6,7 +6,7 @@ nfdi4chem-tags: [data_organisation, data_storage, repositories] slug: "/data_organisation" --- -Besides [documentation of your research data](/docs/data_documentation), another aspect which requires attention is the way how data are named, organised, shared, and referenced during a research activity. Small amounts of data can be just organised in files and folders; when working with many or large data sets, it can be convenient to organise them in a database. For an idea about storage locations and storage methods see [Data Storage and Archiving](/docs/data_storage). +Besides [description and annotation](/docs/data_description_annotation) of your research data, another aspect which requires attention is the way how data are named, organised, shared, and referenced during a research activity. Small amounts of data can be just organised in files and folders; when working with many or large data sets, it can be convenient to organise them in a database. For an idea about storage locations and storage methods see [Data Storage and Archiving](/docs/data_storage). ## Files: naming conventions @@ -19,7 +19,7 @@ myfinaldata_V2.csv myfinaldata_V2_ready.csv ``` -We need short and descriptive file names as an identifier for a document. Useful names give information on what the files contain and helps in sorting them. Pay attention to your naming scheme when working with others: It is important to follow the same file naming convention, so develop an adapted scheme when the project starts and write it down including explaination of abbreviations in your [data documentation](/docs/data_documentation). +We need short and descriptive file names as an identifier for a document. Useful names give information on what the files contain and helps in sorting them. Pay attention to your naming scheme when working with others: It is important to follow the same file naming convention, so develop an adapted scheme when the project starts and write it down including explaination of abbreviations in your data documentation. Try to think about the different statuses (raw data, draft, temporary, finished, ...) and types (editable source format like textfiles or csv in contrast to export formats such as PDF) of your documents. @@ -100,7 +100,7 @@ Different disciplines use established standards, see [Data Formats](/docs/data_f ## Folder structure -Everything should be immediately intuitively understandable. The folder structure helps you to navigate through the individual pieces of information. Develop a convention when the project starts and write it down including explaination of abbreviations in your [data documentation](/docs/data_documentation). Try to consistently apply the same strategy in every project within the research group. +Everything should be immediately intuitively understandable. The folder structure helps you to navigate through the individual pieces of information. Develop a convention when the project starts and write it down including explaination of abbreviations in your data documentation. Try to consistently apply the same strategy in every project within the research group. Folders should: diff --git a/docs/60_topics/62_data_formats.mdx b/docs/30_data/30_data_formats.mdx similarity index 100% rename from docs/60_topics/62_data_formats.mdx rename to docs/30_data/30_data_formats.mdx diff --git a/docs/60_topics/63_data_description_annotation/10_metadata.mdx b/docs/30_data/35_data_annotation/10_metadata.mdx similarity index 100% rename from docs/60_topics/63_data_description_annotation/10_metadata.mdx rename to docs/30_data/35_data_annotation/10_metadata.mdx diff --git a/docs/60_topics/61_identifiers/10_pid.mdx b/docs/30_data/35_data_annotation/10_pid.mdx similarity index 100% rename from docs/60_topics/61_identifiers/10_pid.mdx rename to docs/30_data/35_data_annotation/10_pid.mdx diff --git a/docs/60_topics/63_data_description_annotation/20_ontology.mdx b/docs/30_data/35_data_annotation/20_ontology.mdx similarity index 100% rename from docs/60_topics/63_data_description_annotation/20_ontology.mdx rename to docs/30_data/35_data_annotation/20_ontology.mdx diff --git a/docs/60_topics/63_data_description_annotation/00_data_description_annotation.mdx b/docs/30_data/35_data_annotation/35_data_description_annotation.mdx similarity index 87% rename from docs/60_topics/63_data_description_annotation/00_data_description_annotation.mdx rename to docs/30_data/35_data_annotation/35_data_description_annotation.mdx index bbbca725..24bd5d55 100644 --- a/docs/60_topics/63_data_description_annotation/00_data_description_annotation.mdx +++ b/docs/30_data/35_data_annotation/35_data_description_annotation.mdx @@ -4,6 +4,17 @@ slug: "/data_description_annotation" id: "data_description_annotation" --- +import FloatImage from "@site/src/components/commons/FloatImage"; + +# Data Description and Annotation + + + To best understand a dataset at hand, whether it be for yourself, your working group, or others in the scientific community, it must be clearly described. To this end, data annotation and data description are both important aspects of data management and analysis and enable reuse of research data. Data description involves providing a detailed overview of the data, including its characteristics, format, structure, and any relevant context. Research data annotation is the process of adding labels or notes to data to make it more easily understandable and accessible for analysis. In using rich machine-readable [metadata](/docs/metadata), data annotation and description allows both humans and machines to make informed decisions about the suitability of the data for their research. diff --git a/docs/60_topics/63_data_description_annotation/_category_.json b/docs/30_data/35_data_annotation/_category_.json similarity index 100% rename from docs/60_topics/63_data_description_annotation/_category_.json rename to docs/30_data/35_data_annotation/_category_.json diff --git a/docs/30_data/40_data_documentation.mdx b/docs/30_data/40_data_documentation.mdx deleted file mode 100644 index 4f8c3d7c..00000000 --- a/docs/30_data/40_data_documentation.mdx +++ /dev/null @@ -1,90 +0,0 @@ ---- -title: "Data Documentation" -nfdi4chem-description: description of everything that "your future-self" would need to know -nfdi4chem-id: data_documentation -nfdi4chem-tags: [data_organisation, data_storage, repositories] -slug: "/data_documentation" ---- - -import FloatImage from "@site/src/components/commons/FloatImage.js"; - -:::note summary quote: - -> Simply making your data „open“ does not make your data usable. Usability is the result of other people being able to make sense of your data: the quality of your filenames, your folder structure and your documentation greatly contribute to the level of reusability of your data. It is neither difficult nor time-consuming to maintain your data in a way that invites other researchers to investigate and explore. - -_Andreas von der Dunk, Technische Universität Dresden, Service Center Research Data_ -::: - -## General basics - - - -A clean and comprehensible organisation of data and documents are an important part of good research practice and an important step to realise research data management according to the [FAIR data principles](/docs/fair). - -An essential task is defining in advance the organisation and storage of data, documents, and their [metadata](/docs/metadata), and documenting the relevant measures. - -Central requirements are the definition of [formal responsibilities, organisational conventions](#formal-responsibilities-and-organisational-conventions) and [technical implementations](#technical-implementations) to organise the data and meta information produced. The information collected for this purpose is recorded in the [Data Management Plan](/docs/dmp). Note that a good data organisation also estimates the costs (see [costing tool and checklist](https://ukdataservice.ac.uk/learning-hub/research-data-management/plan-to-share/costing/) for example) in the early application phase. - -### Formal responsibilities and organisational conventions - -An essential part of the data documentation is the definition of the actors working with the data and the procedures. These are possible first steps: - -- Documenting the responsibilities of primary researchers and project staff. -- Creating user roles: Defining detailed rights for users / groups / roles to access data and sensitive information. -- Describing processes of quality assurance including protected storage, sharing, and accessibility in the short term and on the long run. -- Data processing: How, where, how fast. Description of input and output data; decisions on naming and structuring conventions for files and folders. - -The result should be a set of descriptive documents associated with the files used during the daily work routines, which unambiguously determine: - -- the status (for example original file, temporary work file; Draft, intermediate version, final version), -- the location (workstation PC, central file server, database), -- the availability time frame (short, project length, long-term), -- the format in which they are saved. - -![small data handout](/img/data/en_data_handout.png) - -### Technical implementations - -Get an overview of the occurring data and document flows. A short description, easy to understand for every user, should be accessible on a low level and explain the main concepts. The data itself needs to have a bulletproof [Data Organisation](/docs/data_organisation), including [Metadata](/docs/metadata/) and suitable [Data Formats](/docs/data_formats/). Find out more about the usual [Best Practice](/docs/best_practice/) at your institute or within your discipline. Plan how documents can be shared between project staff and what needs to be accessed for [Data Publication](/docs/data_publishing/) with [PIDs](/docs/pid/). - -Data security affects all technical and organisational issues to protect the data from alteration, loss, and destruction. In this context, storage methods, backup procedures, necessary physical resources as well as automated and administrative routines must be planned and put in place. Ask local contacts or external experts about already established technologies for [Data Storage and Archiving](/docs/data_storage) as well as suitable [Repositories](/docs/repositories/). - -## Synopsis - - - -Good data documentation does not happen over night - take small steps first. The documentation of research data is primarily an organisational problem that is accompanied and supported by technological measures: - -- Record of status quo: - - Which organisational processes have been used so far and which technologies support them? - - What are the regulatory boundaries and technical limits? - - Which personal roles are involved? - - Which devices or file formats are or have been used? - - Are there any special features? -- Awareness: Who produces (meta)data, and who continues to use data and how? -- Define internal rules and processes: What are the targets of RDM, and how can they be achieved? -- Apply and evaluate rules iteratively: Learn, set, follow, repeat. Keep it simple and smart (KISS). -- Develop suitable technology: Determine specific requirements in the first project phase and adapt them continuously to changing conditions. -- Establish supporting technology: Evaluate and test software like [ELN](/docs/eln/) and [Repositories](/docs/repositories/); train your staff. -- Obtain legal advice, considering local and higher-level policies and procedures: Contact the legal department at your institution or [NFDI Querschnittssektion "Ethik und Recht"](https://www.nfdi.de/einrichtung-von-ersten-sektionen/) -- Make rules and decisions accessible to everyone at an early stage, for example in the form of a short handout. -- Check the concept regularly and update it if necessary. - -## Sources and further information - -- https://rdmkit.elixir-europe.org/metadata_management.html -- https://www.data.cam.ac.uk/data-management-guide/organising-your-data -- https://rfii.de/en/topics/ -- https://datascience.codata.org/articles/10.5334/dsj-2020-032/ -- German: "Was Forschende wollen – Bericht aus der Beratungspraxis zum Forschungsdatenmanagement" [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5524930.svg)](https://doi.org/10.5281/zenodo.5524930) -- German: https://www.researchgate.net/publication/221657547_Handbuch_Forschungsdatenmanagement -- German: https://www.degruyter.com/document/doi/10.1515/9783110657807/html?lang=en -- German: https://handbuch.tib.eu/w/Lehrbuch_Forschungsdatenmanagement/_Druckversion diff --git a/docs/40_smartlab/10_eln.mdx b/docs/40_eln/00_eln.mdx similarity index 77% rename from docs/40_smartlab/10_eln.mdx rename to docs/40_eln/00_eln.mdx index db97aa66..f074f52a 100644 --- a/docs/40_smartlab/10_eln.mdx +++ b/docs/40_eln/00_eln.mdx @@ -18,42 +18,31 @@ The world around us is constantly evolving. For example, the smartphones in our Bringing advances in information technology to our labs (smartlab) does not necessarily mean tablets & touchscreens everywhere in your lab. The term smartlab is more about the interconnectivity of the entire workflow and the handling of research data according to the [FAIR principles](/docs/fair). ELNs help assign rich [metadata](/docs/metadata) to experiments and make the data collected traceable and reusable. With the ability to transfer data from instrumentation directly into the ELN, the ELN has all the data in one place. From the ELN, data can be easily published to repositories and transferred to long-term [archiving](/docs/data_storage). +## What is the difference between generic documentation system and an ELN or LIMS? + One of the most important things that distinguishes an ELN from a blank piece of paper is the ability to document [metadata](/docs/metadata) in a structured and ideally human and machine-readable manner. For more information on the differences between simple systems, ELNs, and Laboratory Information Management Systems (LIMS), see the following overview. - - -

Simple system

-
    -
  • Enter text
    • -
  • Add notes
    • -
  • Add files as attachments
    • -
  • Sharing
    • -
  • Searching
    • -
- e.g., Evernote GoogleDrive, Dropbox, MS Sharepoint - - -

Electronic Lab Notebook (ELN)

-
    -
  • Structured metadata in human and machine-readable formats
    • -
  • Discipline-specific functions / editors
    • -
  • Rights management
    • -
  • Audit trail
    • -
  • API
    • -
- e.g., Labfolder, RSpace, eLabFTW, Labguru - - -

Laboratory Information Management System

-
    -
  • Sample management
    • -
  • Instrument integration
    • -
  • Electronic signatures
    • -
  • Reporting or statistics modules
    • -
- e.g., Benchling, Starlims, Limesophy - - +### Typical features of different documentation solutions + + +| | Generic solution | Electronic Lab Notebook (ELN) | Laboratory Information Management System (LIMS) | +|-------|:-------:|:-------:|:-------:| +| Examples | _Evernote, GoogleDrive, Dropbox, MS Sharepoint_ | _Labfolder, RSpace, eLabFTW, Labguru_ | _Benchling, Starlims, Limesophy_ | +| Enter text | ✅ | ✅ | ✅ | +| Add notes | ✅ | ✅ | ✅ | +| Add files as attachments | ✅ | ✅ | ✅ | +| Sharing | ✅ | ✅ | ✅ | +| Searching / findability | ✅ | ✅ | ✅ | +| Structured metadata | | ✅ | ✅ | +| Rights management | | ✅ | ✅ | +| Audit trail | | ✅ | ✅ | +| API / system integration | | ✅ | ✅ | +| Sample management | | | ✅ | +| Instrument integration | | | ✅ | +| Process management | | | ✅ | +| Electronic signatures | | | ✅ | +| Accounting / reporting / statistics | | | ✅ | + ## Advantages of an ELN diff --git a/docs/40_eln/10_chemistry_eln.mdx b/docs/40_eln/10_chemistry_eln.mdx new file mode 100644 index 00000000..45f540a8 --- /dev/null +++ b/docs/40_eln/10_chemistry_eln.mdx @@ -0,0 +1,14 @@ +--- +slug: "/chemistry-eln" +title: "Chemistry ELNs" +--- + +import ElnFinder from "@site/src/components/eln/ElnFinder.js"; + +# Chemistry Electronic Lab Notebooks + +The [ELN Finder](https://eln-finder.ulb.tu-darmstadt.de/home) is comprehensive collection of ELNs for all scientific disciplines. It provides in-depth information on the features of each ELN, including scientific, technical, and licensing aspects. The ELN Finder is a valuable resource for researchers seeking to select the most suitable ELN for their specific needs. + +Below is an overview of ELNs in the ELN Finder that are specifically designed for chemistry. + + diff --git a/docs/40_smartlab/15_choose_eln.mdx b/docs/40_eln/20_choose_eln.mdx similarity index 86% rename from docs/40_smartlab/15_choose_eln.mdx rename to docs/40_eln/20_choose_eln.mdx index 4f3679ca..45251309 100644 --- a/docs/40_smartlab/15_choose_eln.mdx +++ b/docs/40_eln/20_choose_eln.mdx @@ -1,14 +1,20 @@ --- -title: "Choose the right ELN" +title: "Start using an ELN" slug: "/choose_eln" id: "choose_eln" --- import useBaseUrl from "@docusaurus/useBaseUrl"; -To date, there is not one ELN, that fits the requirements for all chemical disciplines. Furthermore, only a few ELNs meet the basic requirements for chemical sciences. This is most likely due to the challenges arising from drawing and processing chemical structures, a crucial and central step in being able to correlate research data to the corresponding chemical reaction or structure. The organisation of work with ELNs that support chemistry-specific functions can offer several benefits, such as the availability of [chemical structure identifiers](/docs/machine-readable_chemical_structures) and [standardised formats](/docs/data_formats) as well as the integration of manifold tools and workflows that facilitate scientific work. The direct integration of tools enables a direct support of the scientist without the need to search for additional services and software, thus bringing new developments and information directly to the scientists’ awareness. Some Open Source examples for systems in chemistry that offer the necessary support for chemical structures include [Indigo-ELN](https://lifescience.opensource.epam.com/indigo/eln/index.html), [LabTrove](https://sourceforge.net/projects/labtrove/), [OpenEnventory](http://www.open-enventory.de/), and [Chemotion ELN](https://chemotion.net/docs/eln). +# How to start using an ELN -Therefore, choosing the right ELN is crucial for a successful implementation of an ELN in a laboratory. Three steps should be taken to establish an ELN: 1) Needs assessment, 2) Testing and 3) Introducing the chosen ELN. +To date, there is not one ELN that fits the requirements for all chemical disciplines. Furthermore, only a few ELNs meet the basic requirements for chemical sciences. This is most likely due to the challenges arising from drawing and processing chemical structures, a crucial and central step in being able to correlate research data to the corresponding chemical reaction or structure. The organisation of work with ELNs that support chemistry-specific functions can offer several benefits, such as the availability of [chemical structure identifiers](/docs/machine-readable_chemical_structures) and [standardised formats](/docs/data_formats) as well as the integration of manifold tools and workflows that facilitate scientific work. The direct integration of tools enables a direct support of the scientist without the need to search for additional services and software, thus bringing new developments and information directly to the scientists’ awareness. Some Open Source examples for systems in chemistry that offer the necessary support for chemical structures include [Indigo-ELN](https://lifescience.opensource.epam.com/indigo/eln/index.html), [LabTrove](https://sourceforge.net/projects/labtrove/), [OpenEnventory](http://www.open-enventory.de/), and [Chemotion ELN](https://chemotion.net/docs/eln). + +Therefore, choosing the right ELN is crucial for a successful implementation of an ELN in a laboratory. Three steps should be taken to establish an ELN: + +1. Needs assessment, +2. Testing and +3. Introducing the chosen ELN. :::caution Needs assessment diff --git a/docs/40_smartlab/41_chemotion_eln/10_chemotion.mdx b/docs/40_eln/41_chemotion_eln/10_chemotion.mdx similarity index 100% rename from docs/40_smartlab/41_chemotion_eln/10_chemotion.mdx rename to docs/40_eln/41_chemotion_eln/10_chemotion.mdx diff --git a/docs/40_smartlab/41_chemotion_eln/20_chemotion_experimentDesign.mdx b/docs/40_eln/41_chemotion_eln/20_chemotion_experimentDesign.mdx similarity index 100% rename from docs/40_smartlab/41_chemotion_eln/20_chemotion_experimentDesign.mdx rename to docs/40_eln/41_chemotion_eln/20_chemotion_experimentDesign.mdx diff --git a/docs/40_smartlab/41_chemotion_eln/30_chemotion_experiment.mdx b/docs/40_eln/41_chemotion_eln/30_chemotion_experiment.mdx similarity index 100% rename from docs/40_smartlab/41_chemotion_eln/30_chemotion_experiment.mdx rename to docs/40_eln/41_chemotion_eln/30_chemotion_experiment.mdx diff --git a/docs/40_smartlab/41_chemotion_eln/50_chemotion_dataCollection.mdx b/docs/40_eln/41_chemotion_eln/50_chemotion_dataCollection.mdx similarity index 100% rename from docs/40_smartlab/41_chemotion_eln/50_chemotion_dataCollection.mdx rename to docs/40_eln/41_chemotion_eln/50_chemotion_dataCollection.mdx diff --git a/docs/40_smartlab/41_chemotion_eln/60_chemotion_analysis.mdx b/docs/40_eln/41_chemotion_eln/60_chemotion_analysis.mdx similarity index 100% rename from docs/40_smartlab/41_chemotion_eln/60_chemotion_analysis.mdx rename to docs/40_eln/41_chemotion_eln/60_chemotion_analysis.mdx diff --git a/docs/40_smartlab/41_chemotion_eln/70_chemotion_dataPublication.mdx b/docs/40_eln/41_chemotion_eln/70_chemotion_dataPublication.mdx similarity index 100% rename from docs/40_smartlab/41_chemotion_eln/70_chemotion_dataPublication.mdx rename to docs/40_eln/41_chemotion_eln/70_chemotion_dataPublication.mdx diff --git a/docs/40_smartlab/41_chemotion_eln/_category_.json b/docs/40_eln/41_chemotion_eln/_category_.json similarity index 100% rename from docs/40_smartlab/41_chemotion_eln/_category_.json rename to docs/40_eln/41_chemotion_eln/_category_.json diff --git a/docs/40_eln/_category_.json b/docs/40_eln/_category_.json new file mode 100644 index 00000000..36711254 --- /dev/null +++ b/docs/40_eln/_category_.json @@ -0,0 +1,7 @@ +{ + "label": "Electronic Lab Notebooks", + "link": { + "type": "doc", + "id": "eln" + } +} diff --git a/docs/40_smartlab/_category_.json b/docs/40_smartlab/_category_.json deleted file mode 100644 index 857dc609..00000000 --- a/docs/40_smartlab/_category_.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "label": "SmartLab", - "link": { - "type": "doc", - "id": "smartlab" - } -} diff --git a/docs/60_topics/00_topics_guide.mdx b/docs/60_topics/00_topics_guide.mdx deleted file mode 100644 index 64ad702d..00000000 --- a/docs/60_topics/00_topics_guide.mdx +++ /dev/null @@ -1,21 +0,0 @@ ---- -title: "Guide to Topics" -slug: "/topics_guide" -id: "topics_guide" ---- - -:::info Info: -The topics and concepts section offers topic-specific articles on very specific subjects in research data management and digitalization in chemistry This section is sub-divided into further categories for easy reference. -::: - -For data to be interoperable and reusable, [data formats standards](/docs/data_formats) are of utmost importance. Development here is ongoing and we will continue to add information on formats. - -In order to ensure that data are permanently referenced and cited, repositories assign unique [persistent identifiers (PIDs)](/docs/pid). By linking the journal publication to the data publication, findability of the data files for re-use is guaranteed. - -Annotating data with machine-readable [metadata](/docs/metadata) plays into nearly all aspects of FAIR and ensures data are understood by machines and humans alike. Here, the core concepts of [ontologies](/docs/ontology) in one's research domain proves helpful. - -## Topics in this Section - -- [Identifiers](/docs/identifiers) -- [Data Formats](/docs/data_formats) -- [Data Description and Annotation](/docs/data_description_annotation) diff --git a/docs/60_topics/61_identifiers/00_identifiers.mdx b/docs/60_topics/61_identifiers/00_identifiers.mdx deleted file mode 100644 index d5562316..00000000 --- a/docs/60_topics/61_identifiers/00_identifiers.mdx +++ /dev/null @@ -1,24 +0,0 @@ ---- -title: "Identifiers" -slug: "/identifiers" -id: "identifiers" ---- - -Identifiers are unique strings aimed to identify resources. - -In research data management, identifiers can include [persistent identifiers (PIDs)](/docs/pid) such as digital object identifiers [DOIs](https://www.doi.org/), [ORCID iDs](https://www.orcid.org/) and the Research Organisation Registry ([ROR](https://www.ror.org/)) to persistently refer to published articles and research datasets or software in [repositories](/docs/repositories) and researchers with their affiliation. - -[Electronic Lab Notebooks (ELNs)](/docs/eln) and [archiving](/docs/data_storage) systems typically also use an identifier system. Specific to chemistry, [InChI](https://en.wikipedia.org/wiki/International_Chemical_Identifier) codes serve as a machine-readable identifier for chemical structures. A further example in chemistry is the [CAS Registry Number](https://www.cas.org/solutions/cas-custom-services/cas-registry-services), a proprietary unique identifier assigned to each chemical substance that is indexed in the proprietary [CAS database](https://www.cas.org/support/documentation/cas-databases). CAS numbers are widely used in chemical literature and databases, and they are recognized as an international standard. - -In terms of the [FAIR data principles](/docs/fair), identifiers should interlink scientific publications with their corresponding related dataset(s). For example, referring to the DOI of the associated published journal article in a datasets metadata via a related Identifier helps to describe and lend context to the data. Please see the [Best Practice article](/docs/best_practice) for further details. - -Symbols are close relatives to identifiers, but while identifiers require a dubbing process, such as a resolver for PIDs, symbols apply in a more general sense as a mark to represent another entity. - -## Sources and further information - -- German: [Forschungsdaten.info: Persistente Identifikatoren](https://forschungsdaten.info/themen/veroeffentlichen-und-archivieren/persistente-identifikatoren/) -- [The InChI Code](https://doi.org/10.1021/acs.jchemed.8b00090) - ---- - -Main author: [ORCID:0000-0003-4480-8661](https://orcid.org/0000-0003-4480-8661) diff --git a/docs/60_topics/61_identifiers/_category_.json b/docs/60_topics/61_identifiers/_category_.json deleted file mode 100644 index cb42ce10..00000000 --- a/docs/60_topics/61_identifiers/_category_.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "label": "Identifiers", - "link": { - "type": "doc", - "id": "identifiers" - } -} diff --git a/docs/60_topics/_category_.json b/docs/60_topics/_category_.json deleted file mode 100644 index 636cb6c2..00000000 --- a/docs/60_topics/_category_.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - 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- // Populate style object with all props except 'link' - - Object.keys(props).forEach((key) => { - if (key !== "link") { - style[key] = props[key]; - } +function FloatImage({ + url, + alt, + caption, + float, + noFloat, + shadow, + textAlign, + link, + id, + ...props +}) { + let containerClass = styles.FloatImage; + + containerClass = clsx(containerClass, { + [styles["FloatImage--noFloat"]]: float === "none" || noFloat, + [styles["FloatImage--floatLeft"]]: float === "left", }); - // Component for image - - const ThisImg = () => { - return ( - {alt} - ); - }; - - // If link prop is given, wrap image in link - - if (props.link && props.link.length > 0) { - return ( - - - - ); - } + const imgClass = clsx(styles.FloatImage, { + [styles["imgStyle--shadow"]]: shadow, + }); - return ; + const image = ( + {alt} + ); + + const linkedImage = link ? {image} : image; + + return ( +
+
+ {linkedImage} + {caption !== undefined && ( +

+ {caption} +

+ )} +
+
+ ); } export default FloatImage; diff --git a/src/css/FloatImage.module.css b/src/css/FloatImage.module.css index ce4163c8..ac0453a8 100644 --- a/src/css/FloatImage.module.css +++ b/src/css/FloatImage.module.css @@ -4,6 +4,32 @@ margin: 0 20px; } +.FloatImage--noFloat { + float: none; +} + +.FloatImage--floatLeft { + float: left; +} + +.imgGroup { + display: flex; + flex-direction: column; + align-items: center; +} + +.imgStyle--shadow { + box-shadow: 5px 5px 10px lightgrey; + margin-bottom: 1em; +} + +.captionStyle { + font-style: italic; + font-size: 0.8em; + text-align: left; + margin-bottom: 1em; +} + a > .FloatImage:hover { transform: scale(var(--n4c-hover-scale)); transition: transform var(--n4c-transform-time) ease-in-out; diff --git a/src/data/commonFeatures.js b/src/data/commonFeatures.js index e5604152..69e09e88 100644 --- a/src/data/commonFeatures.js +++ b/src/data/commonFeatures.js @@ -46,6 +46,16 @@ const commonFeatures = { imgUrl: "/img/nfdi4chem_Data_Documentation.svg", text: Data Documentation, }, + dataFormats: { + url: "/docs/data_formats", + imgUrl: "/img/nfdi4chem_Data_Storage_and_Archiving.svg", + text: Data Formats, + }, + dataAnnotation: { + url: "/docs/data_description_annotation", + imgUrl: "/img/nfdi4chem_Data_Documentation.svg", + text: Data Description and Annotation, + }, dataStorage: { url: "/docs/data_storage", imgUrl: "/img/nfdi4chem_Data_Storage_and_Archiving.svg", diff --git a/src/pages/index.js b/src/pages/index.js index 9890d80c..afe2deb5 100644 --- a/src/pages/index.js +++ b/src/pages/index.js @@ -32,7 +32,7 @@ const features = [ text: Electronic Lab Notebooks, imgUrl: "/img/nfdi4chem_SmartLab_white.svg", alt: "Electronic Lab Notebooks Icon", - url: "/docs/smartlab", + url: "/docs/eln", }, { text: How to Publish Your Data, diff --git a/static/img/4Chem.png b/static/img/4Chem.png deleted file mode 100644 index ccbd82cc..00000000 Binary files a/static/img/4Chem.png and /dev/null differ diff --git a/static/img/4Chem.svg b/static/img/4Chem.svg deleted file mode 100644 index 930cf4ed..00000000 --- a/static/img/4Chem.svg +++ /dev/null @@ -1,45 +0,0 @@ - - - - -Created by potrace 1.16, written by Peter Selinger 2001-2019 - - - - - - - - - - - - - diff --git a/static/img/ChemotionELN_Logo.png b/static/img/ChemotionELN_Logo.png deleted file mode 100644 index 2b15b5dc..00000000 Binary files a/static/img/ChemotionELN_Logo.png and /dev/null differ diff --git a/static/img/Constr_1bl.png b/static/img/Constr_1bl.png deleted file mode 100644 index 4db2ef0c..00000000 Binary files a/static/img/Constr_1bl.png and /dev/null differ diff --git a/static/img/Constr_1or.png b/static/img/Constr_1or.png deleted file mode 100644 index 9c6d96fc..00000000 Binary files a/static/img/Constr_1or.png and /dev/null differ diff --git a/static/img/Constr_2bl.png b/static/img/Constr_2bl.png deleted file mode 100644 index a1794829..00000000 Binary files a/static/img/Constr_2bl.png and /dev/null differ diff --git a/static/img/Constr_2or.png b/static/img/Constr_2or.png deleted file mode 100644 index c414eee7..00000000 Binary files a/static/img/Constr_2or.png and /dev/null differ diff --git a/static/img/Intro/LifeCycle.png b/static/img/Intro/LifeCycle.png deleted file mode 100644 index b54aa0db..00000000 Binary files a/static/img/Intro/LifeCycle.png and /dev/null differ diff --git a/static/img/Intro/N4C_DataLifecycle.svg b/static/img/Intro/N4C_DataLifecycle.svg deleted file mode 100644 index e2d16173..00000000 --- a/static/img/Intro/N4C_DataLifecycle.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/static/img/LabIMotion_logo.png b/static/img/LabIMotion_logo.png deleted file mode 100644 index 53180b09..00000000 Binary files a/static/img/LabIMotion_logo.png and /dev/null differ diff --git a/static/img/N4C_logo_hero.svg b/static/img/N4C_logo_hero.svg deleted file mode 100644 index 5eda615a..00000000 --- a/static/img/N4C_logo_hero.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/static/img/N4C_logo_navbar.svg b/static/img/N4C_logo_navbar.svg deleted file mode 100644 index 5cec8617..00000000 --- a/static/img/N4C_logo_navbar.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/static/img/comp.png b/static/img/comp.png deleted file mode 100644 index 80780b37..00000000 Binary files a/static/img/comp.png and /dev/null differ diff --git a/static/img/comp.svg b/static/img/comp.svg deleted file mode 100644 index 7adccb8a..00000000 --- a/static/img/comp.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/static/img/data/Constr_2bl.png b/static/img/data/Constr_2bl.png deleted file mode 100644 index a1794829..00000000 Binary files a/static/img/data/Constr_2bl.png and /dev/null differ diff --git a/static/img/data/chooserepo_petrol.svg b/static/img/data/chooserepo_petrol.svg deleted file mode 100644 index c1e808b7..00000000 --- a/static/img/data/chooserepo_petrol.svg +++ /dev/null @@ -1 +0,0 @@ - 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Was ist das Ziel des FDM? 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