5.2 KiB
Views
Producers 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
- Data Package Views introduction and spec
- datapackage-render-js - this is the library that implements conversion from the data package views spec to vega/plotly and then svg or png
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<br />(Normalized)"]
dpvn --"compile in resource & data ([future] do transforms)"--> dpvnd["Self-Contained View<br />(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).
Graphs
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;
Notes:
- 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;
Summary
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:
- dpr-js repo - which in turn depends on datapackage-render-js
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.
Appendix
There is a separate page with additional research material regarding views specification and tooling.