Pproducers and consumers of data want to have data presented in tables and graphs -- "views" on the data. They want this for a range of reasons, from simple eyeballing to drawing out key insights.

graph LR data[Your Data] --> table[Table] data --> grap[Graph] data --> geo[Map]

To achieve this we need to provide:

  • A tool-chain to create these views from the data.
  • A descriptive language for specifying views such as tables, graphs, map.

These requirements are addressed through the introduction of Data Package "Views" and associated tooling.

graph LR subgraph Data Package resource[Resource] view[View] resource -.-> view end view --> toolchain toolchain --> svg["Rendered Graph (SVG)"] toolchain --> table[Table] toolchain --> map[Map]

This section describes the details of how we support Data Package Views in the DataHub.

It consists of two parts, the first describes the general tool chain we have. The second part describes how we use that to generate graphs in the showcase page.

Quick Links

Table of Contents

The Tool Chain

Figure 1: From Data Package View Spec to Rendered output

graph TD pre[Pre-cursor views e.g. Recline] --bespoke conversions--> dpv[Data Package Views] dpv --"normalize (correct any variations and ensure key fields are present)"--> dpvn["Data Package Views
(Normalized)"] dpvn --"compile in resource & data ([future] do transforms)"--> dpvnd["Self-Contained View
(All data and schema inline)"] dpvnd --compile to native spec--> plotly[Plotly Spec] dpvnd --compile to native spec--> vega[Vega Spec] plotly --render--> html[svg/png/etc] vega --render--> html

IMPORTANT: an important "convention" we adopt for the "compiling-in" of data is that resource data should be inlined into an _values attribute. If the data is tabular this attribute should be an array of arrays (not objects).


Figure 2: Conversion paths

graph LR inplotly["Plotly DP Spec"] --> plotly[Plotly JSON] simple[Simple Spec] --> plotly simple .-> vega[Vega JSON] invega[Vega DP Spec] --> vega vegalite[Vega Lite DP Spec] --> vega recline[Recline] .-> simple plotly --plotly lib--> svg[SVG / PNG] vega --vega lib--> svg classDef implemented fill:lightblue,stroke:#333,stroke-width:4px; class recline,simple,plotly,svg,inplotly,invega,vega implemented;


  • Implemented paths are shown in lightblue - code for this is in datapackage-render-js
  • Left-most column (Recline): pre-specs that we can convert to our standard specs
  • Second-from-left column: DP View spec types.
  • Second-from-right column: the graphing libraries we can use (which all output to SVG)

Geo support

Note: support for customizing map is limited to JS atm - there is no real map "spec" in JSON yet beyond the trivial version.

Note: vega has some geo support but geo here means full geojson style mapping.

graph LR geo[Geo Resource] --> map map[Map Spec] --> leaflet[Leaflet] classDef implemented fill:lightblue,stroke:#333,stroke-width:4px; class geo,map,leaflet implemented;

Table support

graph LR resource[Tabular Resource] --> table table[Table Spec] --> handsontable[HandsOnTable] table --> html[Simple HTML Table] classDef implemented fill:lightblue,stroke:#333,stroke-width:4px; class resource,table,handsontable implemented;


Figure 3: From Data Package View to Rendered output flow (richer version of diagram 1)

Views in the Showcase

To render Data Packages in browsers we use DataHub views written in JavaScript. The module implemented in ReactJS framework and it can render tables, maps and various graphs using third-party libraries.

Implementing code can be found in:

graph TD url["metadata URL passed from back-end"] dp-js[datapackage-js] dprender[datapackage-render-js] table["table view"] chart["graph view"] hot[HandsOnTable] map[LeafletMap] vega[Vega] plotly[Plotly] browser[Browser] url --> dp-js dp-js --fetched dp--> dprender dprender --spec--> table table --1..n--> hot dprender --geojson--> map dprender --spec--> chart chart --0..n--> vega chart --0..n--> plotly hot --table--> browser map --map--> browser vega --graph--> browser plotly --graph--> browser

Notice that DataHub views render a table view per tabular resource. If GeoJSON resource is given, it renders a map. Graph views should be specified in views property of a Data Package.


There is a separate page with additional research material regarding views specification and tooling.