In the previous task we've mentioned it a couple of times already. The data blog. Is it a bird? Is it a plane? No, it's a piece of text where you communicate in the best way possible what your dataset looks like and how and to what extent people can re-use it. 

What should a data blog contain?

• A summary of the collection that's represented by the dataset. What's this data about? Is it content and / or metadata? What kind of content does it represent? How was it digitized? etc.
• A description of the most important metadata fields. What do these fields contain, what type of information can people find in there, what format have you used to represent dates (e.g. yyyy/mm/dd or dd-mm-yyyy)?
• Why do you think this data can be interesting for re-use. If you have specific apllications in mind for your data you can list them here, maybe they will inspire someone to work on them. Be aware though, that a specific type of re-use can't be imposed, you can always make suggestions but there's no guarantee that other people like your propositions.
• An explanation, preferably with a link, where the data can be found and obtained and in what format you offer the data (xml, csv, etc.) 
• Are there additional things that have to be taken into consideration? Here you can describe the code you use by giving examples. 
• What is the rights status of the dataset and what does this mean for the re-user? Explain in detail what kind of re-use is allowed and what not.  If you make use of Creative Commons licenses, be sure to include a hyperlink to the official license pages on creativecommons.org. This way everyone can find as much information as they want. It's a good idea to still include a small summary in your own words though. Use Creative Commons's license chooser to add more data to your license like the way you want to be attributed.
• If people want to make use of your data, chances are they still have some questions or they just want your input on their project. Therefore it is recommended that you provide them with contact information. Preferably someone who is really involved in setting up the open data policy of your institution rather than some general info@institution.com address.
• Also, be prepared to spend some time on following up questions and reactions. The more you can take part in an active dialogue, the more you can potentially gain from opening up your data.

Now it's up to you to put this theory into practice. You've selected one or more datasets, you've chosen an open licensing standard and applied it to the data. Now it's time to summarise all your hard work into a datablog. Write a dedicated datablog for each collection or dataset you offer. You can post the links to the blogs in the comment section below.