Compliance
Attribution and licensing
This page is generated from the repository's own source registries, not written by hand. Every citation below is a licence condition, not a courtesy.
SC-WBD is built on publicly released atlases, receptor maps and
neuroimaging datasets. Several of them attach conditions — attribution,
non-commercial use, share-alike — and those conditions propagate into anything
derived from them.1Generated by site/gen_attribution.py, which
enumerates every card in scwbd/sources/cards/ and every entry in
scwbd/anatomy/sources.py and renders them through the same
scwbd.sources.attribution module the release path uses. Regenerate
with make site-attribution.
Licence is computed from the source registries and split into inheritance (what the sources impose) and policy (what the owner chose). The two are never summed into a single boolean, because only the second is the owner's to revoke.scwbd/release/licence.py
Effective licence union
The union below is the worst case over every source the repository holds, including sources no default code path currently loads. It is not a statement about any particular artifact.
non-commercial: yes; share-alike: yes; attribution: required; redistribution: none; SHARE-ALIKE IN FORCE: derivative works must be released under the same licence; 27 source(s) with UNKNOWN licence (adni, ds000113, hcp-young-adult, mne-sample, mne-spm-face, ram-intracranial, things-eeg2, tuh-eeg, ukbiobank-brain-imaging, buckner2011, conte69, desikan2006, destrieux2010, enigma_hcp_sc, fsaverage, glasser2016, goulas_autoradiography, hcps1200_maps, hill2010, julich_brain, margulies2016, markov2014, netneuro_lausanne_sc, neuromaps, raichle_metabolism, schaefer2018, sydnor2021) — unknown is not permissive
Read the trailing clause literally: unknown is not permissive.
A source whose licence text names no terms is carried as unresolved, never
rounded down to “fine”.2is_vacuous_licence_text exists because a
registry entry once read “See repository LICENSE (open, academic use)” for an
atlas whose actual licence imposes no academic-use limit at all — an invented
restriction, since corrected. The classifier now refuses to resolve text that
names no terms.
The three conditions that bind
Hansen receptor maps — CC-BY-NC-SA-4.0
Non-commercial and share-alike. Two questions have to be kept apart, and a page that merges them will misreport: does the object contain Hansen data, and does the default prior read it? These have different answers today.reports/licence_audit.md Where the terms attach, derivative works must be released under CC-BY-NC-SA-4.0.
Tian subcortical atlas — citation is the condition
The Melbourne Subcortex Atlas grants use without restriction subject to the
single condition that any publication using it cites Tian et al. (2020).
It is not a non-commercial licence. The citation below is how that condition is
met.3Verified against the vendored licence text at
assets/src/tian_subcortex/license.txt, not against the registry's
summary of it.
Schaefer 2018 — MIT, over GSP terms that name nothing
The parcellation labels are MIT (CBIG). Underneath sits Genomics Superstruct Project data “under its own terms”, and those terms are not named. The classifier resolves this to unknown rather than to MIT, and it is shown here as unresolved.
Unsettled, and deliberately not answered
Whether a model trained on CC-BY-NC-SA data is a derivative work of that data
is recorded in the release manifest as
unsettled -- no answer asserted.
This site does not assert an answer. The conservative reading — assume it does —
is the one that fails safe.scwbd/release/manifest.py
The repository has no LICENSE file, and pyproject.toml
declares license = { text = "Proprietary" }. If any
released artifact inherits CC-BY-NC-SA-4.0, ShareAlike requires derivatives be
released under that same licence, and “Proprietary” is not compatible with it.
This needs a human decision before anything is published, and it is a legal
question rather than an engineering one.
Also needed here: whether SC-WBD is being offered commercially, since that determines whether the NonCommercial term is a live constraint or a moot one.
Owner licence decision, on the record
The manifest carries the owner's decision and its history, because a superseded decision is evidence about how the current one was reached.scwbd/release/manifest.py The current decision accepts attribution; it records that the strongest supportable claim is “no established restriction remains” and explicitly not “commercially clear”.
Dataset sources
15 cards in scwbd/sources/cards/. Citations are reproduced verbatim; for the ODC-By datasets, attribution is the whole of the obligation.
| Key | Citation | Licence |
|---|---|---|
adni | Jack CR Jr et al. (2008). The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging 27:685-691. | ADNI Data Use Agreement (application + signature required) doi:10.1212/01.wnl.0000271090.28148.24 · source |
ds000113 | Hanke M, Baumgartner FJ, Ibe P, Kaule FR, Pollmann S, Speck O, Zinke W, Stadler J (2014). A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie. Scientific Data 1:140003, doi:10.1038/sdata.2014.3. Extension studies: Sengupta A et al. (2016), Sci Data 3:160092 (retinotopy); Hanke M et al. (2016), Sci Data 3:160092 (movie/eyegaze). OpenNeuro dataset ds000113 v1.3.0, doi:10.18112/openneuro.ds000113.v1.3.0. | unknown - verified absent from the distributed artifact. snapshot 1.3.0 ships no LICENSE file, dataset_description.json has NO "License" key (checked: the object has exactly BIDSVersion, Name, Authors and ReferencesAndLinks), and the 23,818-byte README contains no occurrence of "licen", "PDDL", "CC0", "public domain" or "Creative Commons". The studyforrest project's own website is documented elsew doi:10.18112/openneuro.ds000113.v1.3.0 · source |
ds000117 | Wakeman DG, Henson RN (2015). A multi-subject, multi-modal human neuroimaging dataset. Scientific Data 2:150001, doi:10.1038/sdata.2015.1. OpenNeuro dataset ds000117 v1.1.0, doi:10.18112/openneuro.ds000117.v1.1.0. | CC0 1.0 Universal (public domain dedication) doi:10.18112/openneuro.ds000117.v1.1.0 · source |
ds002336 | Lioi G, Cury C, Perronnet L, Mano M, Bannier E, Lecuyer A, Barillot C (2020). Simultaneous MRI-EEG during a motor imagery neurofeedback task: an open access brain imaging dataset for multi-modal data integration. Scientific Data 7:173, doi:10.1038/s41597-020-0498-3. OpenNeuro dataset ds002336 v2.0.2, doi:10.18112/openneuro.ds002336.v2.0.2. Paradigm: Perronnet L et al. (2017), Front Hum Neurosci 11:193. | CC0 1.0 Universal (public domain dedication) doi:10.18112/openneuro.ds002336.v2.0.2 · source |
ds004024 | Hernandez Pavon JC, Schneider Garces N, Begnoche JP, Miller LE, Raij T (2022). OpenNeuro dataset ds004024, doi:10.18112/openneuro.ds004024.v1.0.0. Cortico-cortical paired associative stimulation (ccPAS) with bi-focal MRI-navigated TMS-EEG of left and right M1. | CC0 1.0 Universal (public domain dedication) doi:10.18112/openneuro.ds004024.v1.0.0 · source |
eegmmidb | Schalk G, McFarland DJ, Hinterberger T, Birbaumer N, Wolpaw JR (2004). BCI2000: A General-Purpose Brain-Computer Interface (BCI) System. IEEE Trans Biomed Eng 51(6):1034-1043. Dataset: Schalk G (2009), EEG Motor Movement/Imagery Dataset (version 1.0.0), PhysioNet, RRID:SCR_007345, https://doi.org/10.13026/C28G6P | Open Data Commons Attribution License v1.0 (ODC-By 1.0) doi:10.13026/C28G6P · source |
hcp-young-adult | Van Essen DC et al. (2013). The WU-Minn Human Connectome Project: an overview. NeuroImage 80:62-79. | WU-Minn HCP Open Access Data Use Terms (click-through agreement) doi:10.1016/j.neuroimage.2013.05.041 · source |
mne-sample | Gramfort A et al. (2013). MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience 7:267. The sample dataset is distributed with MNE-Python as MNE-sample-data-processed.tar.gz. | unknown - the archive ships no LICENSE file and the MNE-Python documentation page for the sample dataset states no licence. It is distributed publicly as example data by the MNE-Python project. Because the licence is unresolved, this card sets may_release_examples false and redistribution 'unknown'; the data are used locally for calibration only. doi:unknown · source |
mne-somato | Parkkonen L (data author); BIDS conversion by Appelhoff S, Gramfort A and Jas M. Distributed with MNE-Python as MNE-somato-data.tar.gz. See https://mne.tools/stable/documentation/datasets.html#somatosensory | Open Data Commons Public Domain Dedication and License (PDDL) doi:unknown · source |
mne-spm-face | Henson RN, Goshen-Gottstein Y, Ganel T, Otten LJ, Quayle A, Rugg MD (2003) and the SPM multimodal face-processing example dataset; redistributed by the MNE-Python project as MNE-spm-face.tar.gz. See https://mne.tools/stable/documentation/datasets.html#spm-faces | unknown - the archive ships no LICENSE file and the MNE-Python documentation page states no licence for this dataset. The upstream SPM example data is distributed publicly by the Wellcome Centre for Human Neuroimaging. Because the licence is unresolved, redistribution is treated as not permitted and may_release_examples is false. doi:unknown · source |
ram-intracranial | Ezzyat Y et al. (2018). Closed-loop stimulation of temporal cortex rescues functional networks and improves memory. Nature Communications 9:365. | RAM public data use agreement (registration required) doi:10.1038/s41467-018-02753-0 · source |
sleep-edfx | Kemp B, Zwinderman AH, Tuk B, Kamphuisen HAC, Oberye JJL (2000). Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG. IEEE Trans Biomed Eng 47(9):1185-1194. Dataset: Kemp B, Zwinderman AH, Tuk B, Kamphuisen HAC, Oberye JJL. Sleep-EDF Database Expanded (version 1.0.0), PhysioNet, https://doi.org/10.13026/C2X676 | Open Data Commons Attribution License v1.0 (ODC-By 1.0) doi:10.13026/C2X676 · source |
things-eeg2 | Gifford AT, Dwivedi K, Roig G, Cichy RM (2022). A large and rich EEG dataset for modeling human visual object recognition. NeuroImage 264:119754. Data: OSF project 3jk45. | unknown - the OSF project 3jk45 declares no licence through the OSF API (the /license endpoint returns 404 and node_license carries an empty copyright holder). The associated paper is open access, but the data licence itself is not machine-readable, so the licence field cannot be populated and the source may not enter the mixture on an assumption. doi:10.1016/j.neuroimage.2022.119754 · source |
tuh-eeg | Obeid I, Picone J (2016). The Temple University Hospital EEG Data Corpus. Frontiers in Neuroscience 10:196. | TUH EEG Corpus Data Use Agreement (registration + signed DUA) doi:10.3389/fnins.2016.00196 · source |
ukbiobank-brain-imaging | Miller KL et al. (2016). Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nature Neuroscience 19:1523-1536. | UK Biobank Material Transfer Agreement (not an open licence) doi:10.1038/s41593-016-0073-1 · source |
Anatomy and atlas sources
27 entries in scwbd/anatomy/sources.py.
| Key | Citation | Licence |
|---|---|---|
bigbrain_layers | Amunts K. et al. (2013) Science 340:1472-1475; Wagstyl K. et al. (2020) PLoS Biol 18:e3000678. | CC-BY-4.0 (BigBrain derived data) source |
buckner2011 | Buckner R.L. et al. (2011) J Neurophysiol 106:2322-2345. | See repository (open, academic use, citation required) source |
conte69 | Van Essen D.C. et al. (2012) Cereb Cortex 22:2241-2262. | HCP open-access terms source |
desikan2006 | Desikan R.S. et al. (2006) NeuroImage 31:968-980. | FreeSurfer license (free for research use) source |
destrieux2010 | Destrieux C. et al. (2010) NeuroImage 53:1-15. | FreeSurfer license (free for research use) source |
diedrichsen2009 | Diedrichsen J. et al. (2009) NeuroImage 46:39-46. | Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0). NON-COMMERCIAL. Verbatim: 'The SUIT template, associated files and atlases are distributed under a Creative Commons Attribution-NonCommercial 3.0 Unported License, meaning that it can be freely used for non-commercial purposes, as long as proper attribution ... is given.' source |
enigma_hcp_sc | Lariviere S. et al. (2021) Nat Methods 18:698-700; Van Essen D.C. et al. (2013) NeuroImage 80:62-79 (HCP). | BSD-3-Clause code; HCP open-access data-use terms for the underlying scans source |
enigmatoolbox | Lariviere S. et al. (2021) Nat Methods 18:698-700. | BSD-3-Clause source |
fsaverage | Fischl B. et al. (1999) Hum Brain Mapp 8:272-284. | FreeSurfer license source |
glasser2016 | Glasser M.F. et al. (2016) Nature 536:171-178. | HCP open-access data-use terms; redistribution of derived labels permitted with citation source |
goulas_autoradiography | Zilles K., Palomero-Gallagher N. (2017) Front Neuroanat 11:78; Goulas A. et al. (2021) PNAS 118:e2020574118. | As released with the cited papers source |
hansen_lausanne_sc | Hansen J.Y. et al. (2022) Nat Neurosci 25:1569-1581. | CC-BY-NC-SA-4.0 source |
hansen_receptors | Hansen J.Y. et al. (2022) Nat Neurosci 25:1569-1581, plus the primary PET study for each tracer (see Table S3 of that paper). | CC-BY-NC-SA-4.0 source |
hansen_schaefer_sc | Hansen J.Y. et al. (2022) Nat Neurosci 25:1569-1581. | CC-BY-NC-SA-4.0 source |
harvardoxford | Makris N. et al. (2006) Schizophr Res 83:155-171; FSL/FMRIB. | FSL license (free for non-commercial research) source |
hcps1200_maps | Glasser M.F., Van Essen D.C. (2011) J Neurosci 31:11597-11616; Shafiei G. et al. (2022) PLoS Biol 20:e3001735 (MEG). | HCP open-access data-use terms source |
hill2010 | Hill J. et al. (2010) PNAS 107:13135-13140. | As distributed via neuromaps source |
julich_brain | Amunts K. et al. (2020) Science 369:988-992. | EBRAINS terms; account required for programmatic access source |
margulies2016 | Margulies D.S. et al. (2016) PNAS 113:12574-12579. | As distributed via neuromaps source |
markov2014 | Markov N.T. et al. (2014) Cereb Cortex 24:17-36; Ercsey-Ravasz M. et al. (2013) Neuron 80:184-197. | As released with the cited papers; redistributed by netneurolab source |
netneuro_lausanne_sc | Griffa A. et al. (2019) Zenodo; Betzel R.F., Bassett D.S. (2018) PNAS 115:E4880. | BSD-3-Clause (code); data as released with the cited papers source |
neuromaps | Markello R.D. et al. (2022) Nat Methods 19:1472-1479. | BSD-3-Clause (toolbox); per-annotation source terms source |
raichle_metabolism | Vaishnavi S.N. et al. (2010) PNAS 107:17757-17762. | As distributed via neuromaps source |
schaefer2018 | Schaefer A. et al. (2018) Cereb Cortex 28:3095-3114. | MIT (CBIG); underlying GSP data under its own terms source |
sydnor2021 | Sydnor V.J. et al. (2021) Neuron 109:2820-2846. | As distributed via neuromaps source |
tian2020 | Tian Y. et al. (2020) Nat Neurosci 23:1421-1432. | Melbourne Subcortex Atlas License: permission to use the atlas without restriction, including the rights to use, copy, modify, merge, publish and distribute, subject to the single condition that any publication using the atlas cites Tian Y. et al. (2020) Nat Neurosci 23:1421-1432. Attribution required. source |
voneconomo | von Economo C., Koskinas G.N. (1925); digitised by Scholtens L.H. et al. (2018) NeuroImage 170:412-423. | Digitisation released with netneurotools (BSD-3) source |
Redistribution
Several datasets carry redistribution_class: none — among them
HCP Young Adult, ADNI, UK Biobank and TUH-EEG. This site hosts no copy of
any of them and links to no derived data. Access goes through each
provider's own agreement.