1: a) 2D architectural elements: Layout files (GDSII format), designed using
KLayout, Raith 150 e-beam lithography software Version 5.0 (proprietary
format; will be exported to GDSII), LayoutEditor or L-edit software.

b) 3D architectural elements: we use Autodesk Inventor to prepare the 3D model
data which represents the error free junctions and potentially the linking
structures to the e-beam structures made by FhG ENAS. The 3D data from
Autodesk Inventor is then loaded into Rhinoceros3D (McNeel) where the
calculation of the hatching and contour vectors takes place. 3D model data is
always saved in either stl or stp file format which can be opened by several
open-source 3D viewers and 3D editors. Additionally, any 2D cross-section of
the generated data can be stored in DXF or GDSII formats, which can be opened
by open-source software, such as KLayout.

2: Layout files (GDSII format), designed using KLayout, Raith 150 e-beam
lithography software Version 5.0 (proprietary format; will be exported to
GDSII) and LayoutEditor or L-edit software.

Size: < 50GB

Utility: researchers within biocomputation, bio-nanotechnology and FET-sensing

**1.4 Microscopy Data**

Purpose 1: SEM images for quality control during fabrication of architectural
elements and biocomputation devices Purpose 2: Fluorescence microscopy images
for monitoring device operation

Types, formats and origin of data collected:

1: TIFF images, obtained with SEM microscopes.

2: TIFF images, Metamorph Stacks, Nikon ND2 files, obtained with Metamorph and
Nikon AR imaging softwares, Hamamtsu cxd files obtained using HCImage
software.

3\. OME-TIFF images obtained with Photometrics Prime CMOS camera

Size: 1-5 TB

Utility: researchers within Bio4Comp

**1.5 Processing and fabrication data**

Purpose 1/3/4: Process flow plans and parameter sets for fabrication of each
individual sample.

Types, formats and origin of data collected 1/3/4: For EBL control, the
following input data formats are permissible: GDSII, OASIS, DXF, CIF. Using an
appropriate design software such as LayoutEditor or L-edit, conversions
between different data formats are possible.

For galvo scanner control used in TPA, STL-files are used. These data are then
sliced and filled with vectors that are saved into a proprietary file format
(SLL). For direct fabrication with the 3D positioning system any motion and
laser triggering command will be given by a simple script language (G-Code;
industry standard). Viewers for these programs are Rhino3D, STL-Viewer,
EasyViewSTL). Additionally, any 2D cross-section of the generated 3D data can
be stored in DXF or GDSII format, that can be opened by open-source software,
such as KLayout (or commercial ones like Layout Editor) for further
modification at the collaboration partners. Further, text strings, floating
point numbers, vector sets are used. Reporting data can be done on formats
like .txt, .xls, or .doc, viewable with NotePad or standard Office Software.

Size: < 100 MB

Utility: researchers within Bio4Comp

#  FAIR DATA

**2.1 Making data findable, including provisions for metadata:**

  * **Outline the discoverability of data (metadata provision)**

  

  * **Outline the identifiability of data and refer to standard identification mechanism. Do you make use of persistent and unique identifiers such as Digital Object Identifiers?**

  

  * **Outline naming conventions used**

  

  * **Outline the approach towards search keyword**

  

  * **Outline the approach for clear versioning**

  

  * **Specify standards for metadata creation (if any). If there are no standards in your discipline describe what metadata will be created and how**

  

  1. Scientific documents (1.1) will be provided with keywords, a DOI and online searchability where applicable, as facilitated by the chosen institutional or subject repository. 

  

  2. Source code will be searchable through GitHub, use semantic versioning (  _http://semver.org/_ )  and commented. When possible, the source code on GitHub will be connected to other relevant resources, e.g. scientific documents, with DOIs. 

  

  3. Device layouts will be identified through a unique identifier which will also be used during device fabrication to identify individual devices. 

  

  4. Microscopy data will be provided with automatically generated metadata by the camera software (machine parameters like scale, camera brand, acquisition time, exposure time, light source, light intensity, and image mode (fluorescence or TIRF)) completed by manually generated metadata (Creator, 

  

  

Title, Subject, Description) readable by bioformats libraries

( _http://www.openmicroscopy.org/site/products/bio-formats_ )  wherever
possible.

  5. Fabrication data is usually generated in raw formats specific for the individual production facility (TPA, EBL) and will be locally saved in in the lab journals assigned to each facility and relating to the sample processed identified by their id. Data relevant for the processed samples will be copied to in the Bio4Comp project folders (institution-wide as well as TUD OwnCloud service) and translated in data formats accessible for the project partners and the public stakeholders (MS Office, TextEdit). 

  

  

In general, metadata creation will be in accordance with DataCite, the
following six fields being mandatory: Identifier, Creator, Title, Publisher,
PublicationYear, and ResourceType. We will encourage the NBC community to also
add the recommended fields: Subject, Contributor, Date, RelatedIdentifier, and
Description. For microscopy data, other metadata fields will also be required,
including the automatically generated metadata (see point 4 above). Before
uploading microscopy data to repositories, the researchers will curate the
metadata manually in order to make the files discoverable and reusable.

To facilitate discoverability, adding subject keywords (corresponding to
DataCite field Subject) to data and tools will be encouraged. As Bio4Comp is
contributing to development of a new research approach, there is not one
controlled vocabulary that exactly matches the scope of the project. Thesauri
that might cover parts of the subject scope of the project include IEEE and
INSPEC thesauri for the engineering aspects, and the ACM Computing
Classification System for the computing aspects. As a first step, subject
keywords will be chosen freely by the members of the NBC community. We will
also consult with subject librarians to develop an easy to use practice for
using a controlled vocabulary under these interdisciplinary circumstances.

We will follow the file and folder naming conventions as described by Stanford
Libraries “Best practices for file naming” guide (
_https://library.stanford.edu/research/data-management-services/data-best-
practices/bestpractices-file-naming_ )  . This includes creating a naming
scheme that informs the Bio4Comp researchers about e.g. the project name,
researcher name, date of experiment, and version number. To ensure consistency
among the researchers, a readme file will be available in common directories.

**2.2 Making data openly accessible:**

  * **Specify which data will be made openly available? If some data is kept closed provide rationale for doing so**

  

  * **Specify how the data will be made available**

  

  * **Specify what methods or software tools are needed to access the data? Is documentation about the software needed to access the data included? Is it possible to include the relevant software (e.g. in open source code)?**

  

  * **Specify where the data and associated metadata, documentation and code are deposited**

  

  * **Specify how access will be provided in case there are any restrictions**

  

**2.2.1 Data to be made openly accessible:**

  1. Scientific documents (1.1): Contributions to Open Innovation Awards; other documents concerning community building; and public reports for the Bio4Comp project will be published on Zenodo.org. Research publications will be stored (publicly searchable) each partner’s OpenAire approved institutional repository e.g. in Lund University’s research information system, LUCRIS, available at  _http://portal.research.lu.se/portal/_ f  or publications co-authored by researchers affiliated to Lund University; Qucosa, available at  _http://www.qucosa.de/startseite/_ f  or publications co-authored by researchers affiliated to TU Dresden; Fraunhofer ePrints, available at http://publica.fraunhofer.de/starweb/ep09/en/index.htm for publications co-authored by researchers affiliated to Fraunhofer Gesellschaft. 

  

  2. Source code (1.2) of software developed within the consortium, will be made publicly available under an open source license on GitHub, after IP protection and/or first scientific publication. 

  

  3. Fabrication data will be sufficiently outlined in the internal reporting as well as in scientific publications according to the scientific standards which allow a reproduction of the experimental execution by fellow researchers 

  

  

**Software tools** to access the data: pdf-reader, text editor, web browser,
image viewer (e.g. https://fiji.sc/)

**Associated metadata** and documentation will be deposited together with the
files on Zenodo.org

**2.2.2 Closed data:**

  1. Closed reports for the Bio4Comp project Reason: Relevant for IP protection. 

  

  2. Source code of unpublished programs. Reason: Quality management. Relevant for IP protection. 

  

  3. Device layouts (see 1.3). Reason: Highly relevant for IP protection. 

  

  4. Microscopy Data (see 1.4). Reason: Relevant for IP protection. 5) Fabrication Data (see 1.5): Reason: Relevant for IP protection. 

  

  

Closed data relevant to more than one partner will be shared through an
OwnCloud instance hosted by TUD.

**2.3 Making data interoperable:**

  * **Assess the interoperability of your data. Specify what data and metadata vocabularies, standards or methodologies you will follow to facilitate interoperability.**

  

  * **Specify whether you will be using standard vocabulary for all data types present in your data set, to allow inter-disciplinary interoperability? If not, will you provide mapping to more commonly used ontologies?**

  

  1. Research data (1.1) will be made available in PDF/A format to ensure the documents’ portability across systems in a long-term perspective. 

  

  2. Source code (1.2) will be provided as plain text files in well-documented programming languages such as matlab, java and c. 

  

  3. Data for internal Bio4Comp use (1.3 and 1.4) will be stored and shared within Bio4Comp in a defined folder hierarchy using an Owncloud instance hosted by TUD. Access will be granted only to Bio4Comp members. 

  

  4. The interoperability of fabrication data comprising techniques commercially not meant to interoperate one with another is a part of the research work done in WPs 2 and 4. 

  

  

See also Section 2.1 regarding metadata standard (DataCite) and controlled
vocabularies for describing the subject scope of the project’s resources. We
will consult with subject librarians to ensure interoperability with other
controlled vocabularies.

**2.4 Increase data re-use (through clarifying licenses):**

  * **Specify how the data will be licenced to permit the widest reuse possible**

  

  * **Specify when the data will be made available for re-use. If applicable, specify why and for what period a data embargo is needed**

  

  * **Specify whether the data produced and/or used in the project is useable by third parties, in particular after the end of the project? If the re-use of some data is restricted, explain why**

  

  * **Describe data quality assurance processes**

  

  * **Specify the length of time for which the data will remain re-usable**

  

  1. _Research data (1.1) generated by the Bio4Comp researchers_ will be licensed by the respective authors. 

  

  

Authors will be encouraged to use permissive licenses such as Creative Commons
wherever possible. Data connected to research publications (including device
layouts (1.3) and microscopy data (1.4) unless subject to IPR protection) will
be manually curated by the creating researchers before uploading to public
repositories. This will be done after the research publications have been
published in institutional repositories so that the publication can act as an
umbrella for finding und understanding the data. Metadata in the institutional
repositories will be curated by subject librarians to ensure sufficient
quality and findability. The research data that will be made available are
useful for other researchers who intend to generate their own biocomputation
designs or verify the correctness of our conclusions based on these data.
Research data that contributed to a PhD Thesis need to be stored for ten
years. The usefulness of our data for other researchers will probably have
expired by that time, as this research field, albeit new, is moving forward
very rapidly.

_Research data (1.1) generated by others and submitted to us in the frame of
the Open Innovation Awards_ will be made available directly after the decision
of the Innovation System Committee. Licenses are the responsibility of the
authors. IPR connected to these data that is not protected before submission
will become available under a Creative Commons license (CC-NC). Those data
will be useful for third parties that plan to start developing network-based
biocomputation units. As said above, the usefulness will probably expire five
to ten years after the end of the project as better network designs, better
agents as well as tracking and verification methods become available.

  2. Software (1.2) will be licensed under an open source license after IP protection and/or research publication. Distribution via a public repository on GitHub will ensure long-term re-usability. We expect this research field to grow even after the end of the project, therefore we expect many researchers to use the softwares resulting from this project. Design software to make new bio-computation networks and verification software to ensure the correctness of the achieved results. However, this field is rapidly growing; therefore we expect new versions and better programs by others to be available already 5 years after the end of this project. 

  

  3. Fabrication data iteratively proven functional and stored and retrieved locally at fabrication site will be used as standard method for upcoming fabrication runs. These data are not usable by third parties. The data published under 1) and 2) will be sufficient for others to set up their own fabrication protocols or replicate our experiments. 

  

  

#  ALLOCATION OF RESOURCES

**Explain the allocation of resources, addressing the following issues:**

  * **Estimate the costs for making your data FAIR. Describe how you intend to cover these costs**

  

  * **Clearly identify responsibilities for data management in your project** • **Describe costs and potential value of long term preservation**

  

  1. Gerda Rentschler will oversee data management in close collaboration with the respective copyright owners. (3 Person Months covered by Bio4Comp grant.) 

  

  2. Wherever possible, research will be made available via green and/or gold open access. Gold open access fees will be covered by Bio4Comp grant. 

  

  3. Wherever possible, existing infrastructure and/or public repositories will be used at no extra costs to the consortium. 

  

  4. Potential value of long term preservation: data that are included in a PhD thesis have to be stored for ten years after graduation. The Bio4Comp partner that graduates the PhD student is responsible for the storage of the data. As said above, the data generated by the Bio4Comp are probably not useful for third parties more than five to ten years after the end of the project due to newer data being more relevant. 

  

  

Therefore, we do not plan to ensure data preservation beyond that time.

  5. Responsibilities for reporting, storage and re-use of fabrication data are enacted with the device responsibility for microfabrication plants such as EBL (Fraunhofer ENAS) and TPA (Fraunhofer ISC). 

  

  

#  DATA SECURITY

**Address data recovery as well as secure storage and transfer of sensitive
data**

  1. Zenodo manages secure storage and data recovery; 

  

  2. Github research publications manages secure storage and data recovery; 

  

  3. TU Dresden manages owncloud secure storage and data recovery; 

  

  4. Additional data storage on servers of partner institutes with secure storage and data recovery. 

  

  

#  ETHICAL ASPECTS

**To be covered in the context of the ethics review, ethics section of DoA and
ethics deliverables. Include references and related technical aspects if not
covered by the former**

The considerations of ethical aspects, e.g. in connection with ethical
approval, in performing animal experiments increase the quality and thereby
the impact of resulting data. In addition to the animal experiments there are
no other ethical issues of the current project that concern research data.

#  OTHER

**Refer to other national/funder/sectorial/departmental procedures for data
management that you are using (if any)**

  1. Zenodo.org 

  

  2. Lund University’s research information system LUCRIS  _http://portal.research.lu.se/portal/_

  

  3. GitHub.org 

  

  4. TU Dresden Owncloud (  _https://cloudstore.zih.tu-dresden.de/_ ) 

  

  5. University libraries