1- # README
1+ # README
2+
3+ The README is usually the starting point for researchers using your data
4+ and serves as a guidepost for users of your data. A clear and informative
5+ README makes your data much more usable.
6+
7+ In general you can include information in the README that is not captured by some other
8+ files in the BIDS dataset (dataset_description.json, events.tsv, ...).
9+
10+ It can also be useful to also include information that might already be
11+ present in another file of the dataset but might be important for users to be aware of
12+ before preprocessing or analysing the data.
13+
14+ If the README gets too long you have the possibility to create a `/doc` folder
15+ and add it to the `.bidsignore` file to make sure it is ignored by the BIDS validator.
16+
17+ More info here: https://neurostars.org/t/where-in-a-bids-dataset-should-i-put-notes-about-individual-mri-acqusitions/17315/3
18+
19+ ## Details related to access to the data
20+
21+ - [ ] Data user agreement
22+
23+ If the dataset requires a data user agreement, link to the relevant information.
24+
25+ - [ ] Contact person
26+
27+ Indicate the name and contact details (email and ORCID) of the person responsible for additional information.
28+
29+ - [ ] Practical information to access the data
30+
31+ If there is any special information related to access rights or
32+ how to download the data make sure to include it.
33+ For example, if the dataset was curated using datalad,
34+ make sure to include the relevant section from the datalad handbook:
35+ http://handbook.datalad.org/en/latest/basics/101-180-FAQ.html#how-can-i-help-others-get-started-with-a-shared-dataset
36+
37+ ## Overview
38+
39+ - [ ] Project name (if relevant)
40+
41+ - [ ] Year(s) that the project ran
42+
43+ If no `scans.tsv` is included, this could at least cover when the data acquisition
44+ starter and ended. Local time of day is particularly relevant to subject state.
45+
46+ - [ ] Brief overview of the tasks in the experiment
47+
48+ A paragraph giving an overview of the experiment. This should include the
49+ goals or purpose and a discussion about how the experiment tries to achieve
50+ these goals.
51+
52+ - [ ] Description of the contents of the dataset
53+
54+ An easy thing to add is the output of the bids-validator that describes what type of
55+ data and the number of subject one can expect to find in the dataset.
56+
57+ - [ ] Independent variables
58+
59+ A brief discussion of condition variables (sometimes called contrasts
60+ or independent variables) that were varied across the experiment.
61+
62+ - [ ] Dependent variables
63+
64+ A brief discussion of the response variables (sometimes called the
65+ dependent variables) that were measured and or calculated to assess
66+ the effects of varying the condition variables. This might also include
67+ questionnaires administered to assess behavioral aspects of the experiment.
68+
69+ - [ ] Control variables
70+
71+ A brief discussion of the control variables --- that is what aspects
72+ were explicitly controlled in this experiment. The control variables might
73+ include subject pool, environmental conditions, set up, or other things
74+ that were explicitly controlled.
75+
76+ - [ ] Quality assessment of the data
77+
78+ Provide a short summary of the quality of the data ideally with descriptive statistics if relevant
79+ and with a link to more comprehensive description (like with MRIQC) if possible.
80+
81+ ## Methods
82+
83+ ### Subjects
84+
85+ A brief sentence about the subject pool in this experiment.
86+
87+ Remember that `Control` or `Patient` status should be defined in the `participants.tsv`
88+ using a group column.
89+
90+ - [ ] Information about the recruitment procedure
91+ - [ ] Subject inclusion criteria (if relevant)
92+ - [ ] Subject exclusion criteria (if relevant)
93+
94+ ### Apparatus
95+
96+ A summary of the equipment and environment setup for the
97+ experiment. For example, was the experiment performed in a shielded room
98+ with the subject seated in a fixed position.
99+
100+ ### Initial setup
101+
102+ A summary of what setup was performed when a subject arrived.
103+
104+ ### Task organization
105+
106+ How the tasks were organized for a session.
107+ This is particularly important because BIDS datasets usually have task data
108+ separated into different files.)
109+
110+ - [ ] Was task order counter-balanced?
111+ - [ ] What other activities were interspersed between tasks?
112+
113+ - [ ] In what order were the tasks and other activities performed?
114+
115+ ### Task details
116+
117+ As much detail as possible about the task and the events that were recorded.
118+
119+ ### Additional data acquired
120+
121+ A brief indication of data other than the
122+ imaging data that was acquired as part of this experiment. In addition
123+ to data from other modalities and behavioral data, this might include
124+ questionnaires and surveys, swabs, and clinical information. Indicate
125+ the availability of this data.
126+
127+ This is especially relevant if the data are not included in a `phenotype` folder.
128+ https://bids-specification.readthedocs.io/en/stable/03-modality-agnostic-files.html#phenotypic-and-assessment-data
129+
130+ ### Experimental location
131+
132+ This should include any additional information regarding the
133+ the geographical location and facility that cannot be included
134+ in the relevant json files.
135+
136+ ### Missing data
137+
138+ Mention something if some participants are missing some aspects of the data.
139+ This can take the form of a processing log and/or abnormalities about the dataset.
140+
141+ Some examples:
142+
143+ - A brain lesion or defect only present in one participant
144+ - Some experimental conditions missing on a given run for a participant because
145+ of some technical issue.
146+ - Any noticeable feature of the data for certain participants
147+ - Differences (even slight) in protocol for certain participants.
148+
149+ ### Notes
150+
151+ Any additional information or pointers to information that
152+ might be helpful to users of the dataset. Include qualitative information
153+ related to how the data acquisition went.
154+
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