A few minor typo fixes

dandi/tests/data/metadata/dandimeta_migration.new.json

@@ -3,7 +3,7 @@
   "schemaKey": "Dandiset",
   "schemaVersion": "0.4.0",
   "name": "A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task",
-  "description": "A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.",
+  "description": "A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy reuse of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.",
   "contributor": [
     {
       "schemaKey": "Person",

docs/design/python-api-1.md

@@ -118,7 +118,7 @@ Designs for an improved Python API
         * The basic methods simply upload/download everything, blocking until completion, and return either nothing or a summary of everything that was uploaded/downloaded
             * These methods have `show_progress=True` options for whether to display progress output using pyout or to remain silent
             * The upload methods return an `Asset` or collection of `Asset`s.  This can be implemented by having the final value yielded by the `iter_` upload function contain an `"asset"` field.
-        * Each method also has an iterator variant (named with an "`iter_`" preffix) that can be used to iterate over values containing progress information compatible with pyout
+        * Each method also has an iterator variant (named with an "`iter_`" prefix) that can be used to iterate over values containing progress information compatible with pyout
             * These methods do not output anything (aside perhaps from logging)
 
     * An `UploadProgressDict` is a `dict` containing some number of the following keys:

tools/update-assets-on-server

@@ -3,7 +3,7 @@
 
 Composed by Satra (with only little changes by yoh).
 Initially based on code in dandisets' backups2datalad.py code for updating
-as a part of that script but it was intefering with the updates to datalad thus
+as a part of that script but it was interfering with the updates to datalad thus
 extracted into a separate script.
 """