ReproNim · yarikoptic · Nov 10, 2017 · Nov 10, 2017 · Nov 10, 2017 · Nov 10, 2017
diff --git a/_episodes/01-Web-of-Data.md b/_episodes/01-Web-of-Data.md
@@ -81,7 +81,7 @@ The application of persistent identifiers in neuroimaging has been disdcussed in
 > ## Exercise: Identifier Resolution (click on the arrow to the right to open)
 > **Where can I resolve globally unique identifiers**
 >
-> The California Digital Library ([CDL](http://www.cdlib.org)) makes a number of tools available regarding persistent identifiers, including: registe4ring DOIs and ARKs and providing resolution services.  The N2T tool (Names to Things) is a resolving service that keeps names (identifiers) persistent, forwarding (resolving) them to the best known web addresses. For example, to resolve the PubMed identifier used in the above challenge - one would use the following call to N2T: [http://n2t.net/pubmed:26978244](http://n2t.net/pubmed:26978244)
+> The California Digital Library ([CDL](http://www.cdlib.org)) makes a number of tools available regarding persistent identifiers, including: registering DOIs and ARKs and providing resolution services.  The N2T tool (Names to Things) is a resolving service that keeps names (identifiers) persistent, forwarding (resolving) them to the best known web addresses. For example, to resolve the PubMed identifier used in the above challenge - one would use the following call to N2T: [http://n2t.net/pubmed:26978244](http://n2t.net/pubmed:26978244)
 >
 > The CDL is partnering with [identifiers.org](http://identifiers.org) to maintain a registry of resolvable prefixes. In this exercise, please explore the [registry at identifiers.org](https://www.ebi.ac.uk/miriam/main/collections) and choose a repository.  Browse the repository and extract some IDs and test the resolvers at N2T [http://n2t.net/](http://n2t.net/) and identifiers.org [http://identifiers.org](http://identifiers.org).
 >

diff --git a/_episodes/03-Ethics.md b/_episodes/03-Ethics.md
@@ -31,6 +31,9 @@ This  lesson links to externally available information to introduce the student
 >
 > **Abstract**: This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations-the interactions among hardware, software and data-rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments.This article is part of the themed issue 'The ethical impact of data science'.
 >
+>   - [Open Brain Consent](http://open-brain-consent.readthedocs.io)
+> project provides a collection of used consent forms which provision public sharing of collected data, and a suggested wording for an "ultimate" consent form which you could use in your studies.  Also points to the tools for data anonimization to prepare for public sharing.
+>
 > ### Relevant Organizations:
 >   - [Council for Big Data, Ethics, and Society](http://bdes.datasociety.net)
 >

diff --git a/_episodes/04-Data-Publishing.md b/_episodes/04-Data-Publishing.md
@@ -74,7 +74,7 @@ Here are some things to consider:
 
 #### DataLad
 
-DataLad builds on top of git-annex and extends it with an intuitive command-line interface. It enables users to operate on data using familiar concepts, such as files and directories, while transparently managing data access and authorization with underlying hosting providers.
+[DataLad](http://datalad.org) builds on top of [git-annex](http://git-annex.branchable.com/) and extends it with an intuitive command-line and Python interfaces. It enables users to operate on data using familiar concepts, such as files and directories, while transparently managing data access and authorization with underlying hosting providers.  Please see [Reproducible basics:VCS:DataLad](/module-reproducible-basics/02-vcs/#datalad) section for more information.
 
 #### Credit for publishing data
 

diff --git a/_episodes/05-Your-Laboratory-Datastore.md b/_episodes/05-Your-Laboratory-Datastore.md
@@ -1,5 +1,5 @@
 ---
-title: "Lesson 4: Your Labortory Datastore"
+title: "Lesson 4: Your Laboratory Datastore"
 teaching: Self Paced
 exercises: 0
 questions:
@@ -9,7 +9,7 @@ objectives:
 - "Learn about different databasing options if a custom solution is desired"
 keypoints:
 - There are a number of tools, developed by the research community and also by companies, to assist in stewardship of laboratory data.
-- There are a number of options for developiong your own custom database solution.
+- There are a number of options for developing your own custom database solution.
 
 ---
 
@@ -34,20 +34,28 @@ When managing data in your own laboratory, there are a number of options availab
 >
 > ##### LORIS:
 >
->  - [LORIS] (http://www.loris.ca)
->  - [LORIS GitHub] (https://github.com/aces/Loris)
+>  - [LORIS](http://www.loris.ca)
+>  - [LORIS GitHub](https://github.com/aces/Loris)
 >
 > **Overview**: The Longitudinal Online Research and Imaging System is a web-based data and project management software for neuroimaging research studies. It is an OPEN SOURCE framework for storing and processing behavioural, clinical, neuroimaging and genetic data. LORIS also makes it easy to manage large datasets acquired over time in a longitudinal study, or at different locations in a large multi-site study.
 >
 > **Documentation**: Documentation for LORIS can be found on their GitHub Wiki page (https://github.com/aces/Loris/wiki/Setup)
 >
 > ##### FlyWheel (Commercial):
 >
->  - [FlyWheel] (https://flywheel.io)
+>  - [FlyWheel](https://flywheel.io)
 >
 > **Overview**: Flywheel is a data management platform designed to ease the IT burden of the researcher by creating a collaborative environment for reproducible, computational science. Data can be uploaded directly from devices or can be manually uploaded into Flywheel. Once loaded, users can organize and search through data.
 >
-> **Documentation**: Documentation for FLyWheel can be found on their documentation page (https://docs.flywheel.io)
+> **Documentation**: Documentation for FlyWheel can be found on their documentation page (https://docs.flywheel.io)
+>
+> ##### DataLad:
+>
+>  - [DataLad](https://datalad.org)
+>
+> **Overview**: DataLad allows you to establish a collection of datasets while aggregating meta-data available in them, allowing for efficient search and management while keeping everything, including meta-data under git version control.  With [heudiconv](https://github.com/nipy/heudiconv) DataLad support, it becomes possible to establish automated conversion and complete version control of studies data and meta-data right from the fMRI scanner.
+>
+> **Documentation**: Documentation for DataLad can be found on their documentation page ([docs.datalad.org](https://docs.datalad.org)) with demos for establishing automated collection and conversion from [datalad.org/for/mri-data-management](http://datalad.org/for/mri-data-management).
 >
 {: .callout}
 
@@ -78,7 +86,7 @@ While it is recommended that one try and utilize (and potentially contribute to)
 > #### Lessons for Specific Database Platforms
 > ##### MariaDB:
 >
->   - [Learn MariaDB] (https://mariadb.org/learn/)
+>   - [Learn MariaDB](https://mariadb.org/learn/)
 >
 > ** Abstract**: MariaDB, the successor to MySQL, is an open-source relational database.  They provide a collection of online learning resources.
 >