There are various enhancements to HDX that we can consider to improve the user experience, simplify the quality assurance work of Data Partnerships and support the development of dashboards and other visualisations. I want to document these enhancements here as we consider if they fit into our plans and where.

Problems

Issues that were already identified 

The following issues have been identified:

• archiving of "old" datasets (where data is from a long time ago, but is as up to date as it can be eg. ebola 2013) - this is done

• tag cleanup - dataset tags should not be freeform, they should be from a fixed list with the facility to request to add more - some of this is done

• fixing data URLs so that charts, reports etc. don't break - USAID have asked for this and there is a Jira Epic for it (the Fixed Data URLs Idea goes further than what USAID have asked for)

• a workflow that tries to alert a contributor when an update to a resource they are making has unexpected field names, data type changes, etc. - USAID have asked for this and there is a Jira Epic for it

• a system whereby automated users (and maybe normal users as well) can register to receive important information about a dataset they are using eg. a breaking change to the format, no longer being updated etc. - USAID have asked for this and there is a Jira Epic for it

• we need to be able to distinguish data resources from auxiliary ones - helpful to DP's work on QAing datasets

• distinguishing API resources from others

• resources can't keep growing indefinitely - we need a way to split a resource once it grows beyond a certain size

• keeping a history of data (versioning) - newly added data may contain errors so it may be helpful to be able to fall back to a previous version of the data eg. if a dashboard cannot load latest/xxx.csv, it could try 1/xxx.csv

• a service whereby if a contributor uploads data in a particular format/structure that we specify, then the data is served out disaggregated in multiple ways

• finding data by API needs to be simpler. Currently the limitation there is the capabilities of the CKAN API search. It can be helped by adding more metadata into the dataset for example the list of fields and HXL tags in the data

• more generally a search tailored to what users want to search for eg. if a user types "wheat price kandahar" they would like to get back that price.

How data is currently structured

In order to determine the best way to structure data going forwards, it is important to look at how data is currently structured. This is typically dependent upon how the organisation chooses to disaggregate its data.

1. Dataset containing data in xlsx and csv formats as separate resources eg. https://data.humdata.org/dataset/afghan-voluntary-repatriation

2. Dataset with rolling updates of resource (ie. dataset end date should be DATE) eg. https://data.humdata.org/dataset/inso-key-data-dashboard, https://data.humdata.org/dataset/indonesia-monthly-humanitarian-update

3. Dataset with metadata in resource eg. https://data.humdata.org/dataset/global-airports, https://data.humdata.org/dataset/drc-health-data (jpeg has graphical metadata)

4. Dataset with tiff in a zip: https://data.humdata.org/dataset/malawi_national_vulnerability_index_2015 (note the 2015 in the url is incorrect as it is current)

5. Dataset with pdfs, zips (on OneDrive and filestore), mbtiles, tiff : https://data.humdata.org/dataset/iom-npm-cox-bazar-uav-imagery

6. Dataset with JSON feed, HXLated JSON feed and xlsx (from automated output): https://data.humdata.org/dataset/migrant-deaths-by-month

7. Disaggregate by country into datasets and by indicator into resources eg. https://data.humdata.org/dataset/who-data-for-barbados

8. Disaggregate by date into datasets  eg. https://data.humdata.org/dataset/syria-idp-flow-and-returnee-data-october-2018, https://data.humdata.org/dataset/syria-idp-flow-and-returnee-data-september-2018

9. Disaggregate by date into resources within one dataset eg. https://data.humdata.org/dataset/nigeria-humanitarian-needs-overview

10. Disaggregate by indicator into datasets eg. https://data.humdata.org/dataset/gender-development-index-female-to-male-ratio-of-hdi, https://data.humdata.org/dataset/population-in-severe-poverty-headcount

11. Disaggregate by country into datasets and by date and region into resources eg. https://data.humdata.org/dataset/drc-displacement-data-baseline-assessment-iom-dtm

12. Disaggregate by country into datasets and by round into resources eg. https://data.humdata.org/dataset/nigeria-baseline-data-iom-dtm

13. Disaggregate by country and emergency into datasets and by round into resources eg. https://data.humdata.org/dataset/indonesia-displacement-data-sulawesi-earthquake-site-assessment-iom-dtm

14. Map data for a country at different admin levels for various dates eg. https://data.humdata.org/dataset/administrative-boundaries-of-bangladesh-as-of-2015 (note the 2015 in the url is incorrect as it is current)

15. Map and population data for a country with varying file formats and metadata in a pdf eg. https://data.humdata.org/dataset/bhutan-administrative-level-0-1-population-statistics

Simon is looking at how to identify data series.

Are we approaching the stage where we need to break down data by admin 1 rather than country to enable users of HDX to be able to search for data in the UI at that level? How do we make data available in many forms eg. by country, by indicator, by admin 1?

Ideas for HDX

The solutions presented below were created with consideration for what is feasible given the restrictions of CKAN. The intention was to avoid complex solutions that might require forking CKAN to make fundamental changes to its architecture and instead to try to come up with something relatively simple to implement given limited development capacity.

Tags metadata

• Tag mappings from existing tags to desired ones and deletions of extraneous tags have been previously defined in the Google spreadsheet here

• That Google spreadsheet is already used by HDX Python API library

• There is already a ticket so that any edits made as a result of tag cleanup do not "touch" the datasets  HDX-6404 - Getting issue details... STATUS

• The locked down list of tags from the Google spreadsheet should be integrated into CKAN

• The list of allowed tags should be put into a CKAN vocabulary eg. using the CKAN API call: vocabulary_create

  • Now might be a good time to categorise tags into multiple vocabularies?

• The way to use the tag vocabulary with the metadata field is described in the CKAN documentation for schemas (I think)

• On the dataset edit page, when a contributor starts to type a tag, tag suggestions from the defined vocabulary(ies) should pop up

  • This might work using the CKAN call tag_autocomplete

  • Or maybe comes directly from setting the metadata field to use a specific vocabulary(ies)

  • An example to look at for UI is stackoverflow

• Establish a synonym schema so that if a user types "idp" in the tag search, the "internally displaced persons" tag will come up even though there are no matching strings.

• Create a process for suggesting new tags - if a contributor types a tag name that is not in the vocabulary, then:

  • The contributor should be alerted that the tag is not in the existing list

  • The contributor should be shown the full list of tags and advised to check if there is an existing tag that matches

  • If we have categorised tags into multiple vocabularies, that would be quite helpful for the contributor to narrow down their search

  • If there is none that matches the contributor should be able to click a button to apply for a new tag

  • If categories are being used, they will need to specify the category?

  • Should we allow the tag (ie. auto add it) with DP having the option to reject it?

  • or should the dataset be created minus the tag with DP having to add it later if they approve it?

  • In either case, the contributor should be allowed to continue creating the dataset

  • On submit (when all the information about the dataset will be available), DP should receive a mail containing the:

    • organisation name

    • contributor username and email

    • dataset title

    • tags and proposed tag(s)

• Provide a way for DP to add, edit and delete tags

  • Initially this can be by script

  • In the long run if it happens often that new tags are needed, then there may be some value in either:

    • making a UI

    • updating the CKAN tags and vocabulary(ies) from a Google Spreadsheet (which may already have been done in one of the earlier steps to create the locked down list)

• The CKAN calls package_create or package_update should fail with an appropriate error message if tags are specified that aren't in the vocabulary(ies) - again this might be a byproduct of defining a vocabulary(ies) on a metadata field

• Once this is in place, there needs to be a check to see if any new tags have appeared since the tag cleanup spreadsheet was last worked on

• Demo should get the current prod database

• The tag cleanup script should be updated to use whatever parameter (or username or whatever) was created so that it does not touch datasets

• The tag cleanup script should be run against demo

• If all goes well, the tag cleanup should be run against prod

Detecting Breaking Changes to Resources

• For USAID, this is being looked at for filestore resources: HDX-8280 - Getting issue details... STATUS

Users Registering Interest in Datasets

• While it is possible to “Follow” datasets in the UI, that option should also be available through API

• They should be able to select what updates they are interested in:

  • Metadata changes

  • Tabular or Map Data changes (assuming the later data categorisation idea is implemented)

  • Dataset being "Reviewed"

  • Breaking changes (USAID: HDX-8281 - Getting issue details... STATUS )

• They should perhaps be able to select whether to get emails and the frequency of emails (but this will complicate the logic)

  • Whenever the dataset is updated and the update corresponds to what they registered for, they should get an email immediately or the change should be recorded for sending in a periodic email

Keeping a History of Data

• This is about versioning of files on HDX

• Assuming we limit it to the filestore, it may be easiest to leverage AWS versioning

• If AWS isn’t an option, a solution could be as follows:

  • For filestore resources, backup when contributor uses dataset edit dialog to update a resource

  • For external urls, backup according to the expected update frequency into the filestore

  • Do we ask if contributor wishes to keep a backup? No backup means just do as now (ie. overwrite the resource)

  • Backups are created in new resource groups

  • Once there are too many resources, archive the old ones

  • This will require a lot of storage

  • Some resources may be too big to keep backing up so regularly

Improving Search

• The metadata field that HDX Connect uses should be added to all datasets (field_names)

• A new metadata field should be added to all datasets: hxl_hashtags

• In the dataset edit dialog when a contributor adds a resource:

  • Its headers and any HXL tags should be scanned

  • The headers should prepopulate the Field Names text field

  • The contributor can edit the text field

  • The HXL Hashtags should prepopulate the HXL Hashtags (uneditable?) text field

• CKAN search should be made to use the field_names and hxl_hashtags dataset fields by default

• The resource_groups field in the dataset should also be included in CKAN search

• See also “Idea for a Data Cube” later in this page

Stndardising and Categorising Resources

• We could categorise resources into Data and Auxiliary resources and then further subdivide into say “tabular data” and “geodata” in the UI

  • The "Data and Resources" tab should be divided into the categories

  • We need to define a list of file extensions that we regard as "tabular data" eg. csv, xls, xlsx etc.

  • We need to define a list of file extensions that we regard as "geodata" eg. geojson, zipped shapefile etc.

• In the dataset edit UI, the resource name field should be relabelled "Title of Resource"

  • It should not be prepopulated from the filename (as it is currently) because we want contributors to write a descriptive resource title

• If there is a file extension, it should be used to prepopulate the "File type" field

  • The "File type" should not be allowed to be different to any provided file extension

  • If a file extension is not provided, the resource could be sniffed to try to guess the file type to prepopulate the field eg. using https://github.com/ahupp/python-magic

  • When adding a resource, the "File type" field needs to be locked down to a list of possible formats for the contributor to pick from

• Consider adding an option to suggest a new format not in the list

• For one resource, there should be an option to add more file types (ie. upload same data in different formats like csv, xls etc.)

  • One resource with multiple file types would likely translate into separate resources in dataset metadata

  • The "Download" button should be replaced with the "File type" with a small download symbol

  • If more than one resource has the same "Title of Resource", but different "File types" (within the same category), they can be shown as one resource with more than one file type download buttons

  • Example: Missing Migrants     ↓csv  ↓xls

• Categorisation in the dataset edit UI:

  • The resource metadata should have a new field containing the categorisation eg. category which could be "tabular", "map" or "auxiliary"

  • Once the "File type" is selected, the dataset edit UI should show how the resource was categorised:

    • "Tabular data"

    • "Map data"

    • "Auxiliary data"

  • The contributor should have the option to recategorise "Tabular data" or "Map data" to "Auxiliary data"

• Showcases should just point to websites and visualisations with pdfs being auxiliary resources?

• The contributor should have the option to flag to us that "Auxiliary data" has been incorrectly categorised - this will alert us to new tabular or map file formats to add to our lists

Handling Different Structures of data 

We want to move contributors away from a completely freeform experience of structuring data without discouraging them. I need to see how this fits with SImon’s ongoign work on data series:

• We need to introduce the concept of "Resource Groups"

• Resource groups allow resources to be grouped in multiple ways, for example:

  • By date

  • By round

• The logic for resource groups should enable versioning

• Resource groups can have the categories tabular, map and auxiliary within them

• There should be a resource metadata field "group"

• There should be a dataset metadata field "latest_resource_group"

• All resource groups should be maintained at the dataset level in a field eg. "resource_groups" which could be a comma separated list for example

• In the dataset view UI, if there is only one group then the "Data and Resources" tab should be displayed as now

• If there are multiple resource groups, then the "Data and Resources" tab should have within it either tabs:

  • Sub-tabs for each group "Resources - groupname" in the order in the dataset's "resource_groups" field

  • The default one shown should be the one specified in the dataset "latest_resource_group"

• Or an alternative to tabs within tabs are folders/shortcuts which may be more intuitive:

  • The resources of the default group (as specified in the dataset "latest_resource_group") should be shown

  • Below these should be folder icons for each group "Resources - groupname" in the order in the dataset's "resource_groups" field (excluding the "latest_resource_group")

  • Double clicking a folder will change the resources shown to those in the resource group corresponding to the folder

• In the dataset edit UI, there should either be tabs:

  • Tabs at the top showing any resource groups that already exist in the order in the dataset's "resource_groups" field

  • The first and default tab should be what is in latest_resource_group

  • The resources shown should be whatever are in the resource group specified in latest_resource_group

  • A "+" tab should allow the creation of a new resource group

  • Double clicking in an existing tab should allow renaming a resource group

  • Clicking a not selected resource group tab should cause the resources shown to change to whatever are in that resource group

  • The tabs should be draggable to change their order which will cause the dataset's "resource_groups" field to update

• Or folders/shortcuts:

  • The resources shown should be whatever are in the resource group specified in latest_resource_group

  • Below these should be folder icons for any resource groups that already exist in the order in the dataset's "resource_groups" field

  • A folder with "+" in the icon should allow the creation of a new resource group

  • Single clicking on a existing folder should allow renaming a resource group

  • Double clicking a resource group folder should cause the resources shown to change to whatever are in that resource group

  • The folders should be draggable to change their order which will cause the dataset's "resource_groups" field to update

• Each resource should have an option (button with dropdown?) to move it to another resource group

• There needs to be an explanation of what a "Resource Group" is and what it is used for on the left

• There should be a field "Latest Resource Group" with a dropdown to select from all the created groups

• See also Proposed Solution for Improving Search below

Fixing URLs

• A version of this is being done for USAID whereby there are URLs for resource positions in the dataset.

• Based upon the groups and categories outlined in ideas above, the resources should be made available under the urls:
  https://data.humdata.org/dataset/mydataset/groupname/tabular/
  https://data.humdata.org/dataset/mydataset/groupname/map/
  https://data.humdata.org/dataset/mydataset/groupname/auxiliary/

• The descriptive resource title should be slugified and used as the resource filename

• The extension should be taken from the "File type" field

• Example: "Title of Resource" = "Missing Migrants", "File type" = "xlsx", group = "2018" → https://data.humdata.org/dataset/mydataset/2018/tabular/missing-migrants.xlsx

• If "2018" were set as the latest group, the same file would be accessible from this url → https://data.humdata.org/dataset/mydataset/latest/tabular/missing-migrants.xlsx

Archiving Resources

• We should determine a sensible maximum number of resources in the UI

• When a dataset grows to have that maximum and the contributor tries to add more, they should be prompted to archive or delete resources

• Archived resources are not shown by default in the dataset view

• Depending upon performance for datasets with many resources:

  • Each resource should have a new metadata field "archived" 

  • The dataset edit UI should have an archive resource button (or if we have resource groups, on each resource group)

  • This should prompt the contributor to select the resource(s) (or resource group(s)) to be archived

  • For each resource (in the resource group(s)), the archived flag is set to True

• If performance is an issue:

  • The dataset edit UI should have an archive resource group button

  • This should prompt the contributor to select the resource group(s) to be archived

  • On clicking next, a new dataset should be created with only the resource group(s) that were selected

  • The metadata for the dataset should be copied from the original

  • The archived metadata field should be set to True

  • The dataset title should have "(archived on ISODATETIME)"

  • The original dataset should have the resource groups (and underlying resources) removed from it

Excessively Large Resources

• We need to define how big is reasonable (can we?)

• When a filestore resource reaches that size:

  • In the dataset edit UI, the contributor should be prompted

  • The prompt should contain information or link to info on ways to disaggregate data into Resource Groups

  • The contributor can either go back to the edit UI (file will not be added as resource)

  • Or ignore and continue (file will be included as resource)

• We could look at http header content length for remote resources and do the same?

Centre Curated Resources

The Centre may wish to create new curated version(s) of an existing resource(s) in a dataset:

• HDX create a new resource group within the dataset eg. "curated"

• HDX add curated resource(s) under that group

• URL would be something like: https://data.humdata.org/dataset/mydataset/curated/tabular/missing-migrants.csv

• The curated resource is appropriately highlighted in the UI

Discouraging Dated datasets

We want to discourage dated datasets as this leads to new datasets being created for each new update and inconsistent urls

• We should have a check in the dataset create dialog for a date (eg. a year) being put into a title

• Some sort of dialog should appear that guides the user away from doing this (by informing them about Resource Groups within datasets)

Blue Sky Ideas

Idea for a Meta Service/API that links to other APIs

The idea is to have a meta service/API that would link to other services/APIs and allow the easy download of data given a standard set of input parameters. On top of such a meta service/API would be a user interface which would allow setting of those parameters and download by non technical users. Using the "wheat price kandahar" example, I could imagine a meta service/API user choosing parameters like "service": "prices", "type": "commodities", "provider": "WFP", "country": "Afghanistan", "adm1": "Kandahar", "Commodity": "wheat", "date": "08/03/2022".

Could this power the HDX UI allowing searches like "wheat price kandahar" to produce helpful results?

Add meta service/API resources as “queryable” resources in HDX - ones where you can add some parameters to filter or transform the returned file:

• Resources should have a field "is_queryable" which can be True or False

• Resources should have a field "queryable_desc_url" which is a link to a webpage that describes the parameters a user can to the URL to filter or transform the data

• There should be an explanation of what queryable means in the dataset edit dialog

• There should be a checkbox in the dataset edit dialog to mark a resource as queryable

• There should be a url field for adding a link to a webpage that describes the parameters a user can to the URL to filter or transform the data

• Queryable resources should be flagged in the dataset view and search UIs (work has been done on this)

• The link to a webpage describing the parameters should be next to or below the queryable resource

Idea for a Data Cube

Typically we make data available in different forms like by indicator or by country by making separate datasets with their own data. This makes accessing the data fast but complicates scrapers which must do the breakdowns so mostly data is just broken down by country on HDX. A data cube enables data to be modelled and viewed in multiple dimensions. Is there a way that data could be stored in some sort of data cube so that it can be viewed in different ways like by country, admin 1 or indicator without keeping multiple copies of the data?

• The data cube should be available from the HDX add dataset dialog, perhaps as a third type?

• Aggregated data should be provided in standardised form with HXL hashtags (to be defined) 

• The service potentially generates multiple datasets on HDX

• General metadata that will be used for all generated datasets should be added using a UI similar to the add public dataset UI on HDX

• The contributor can select to have the full aggregated dataset put into HDX?

• The service looks at the HXL hashtags

• It determines the columns which are suitable for disaggregation by looking at the HXL hashtags

• It offers them as suggestions to the contributor?

• If the contributor selects #country or we just disaggregate along every suitable column we detect, we can:

  • It splits the dataset by country, creating a dataset per country in HDX pointing back to the cube data

  • The metadata for each dataset is based on the general metadata

  • It will need to add country information into the dataset title etc.

• A similar process can be applied for #indicator etc.