Re: Time-series spatial data [was: Re: TCGA / Microscopy Imaging Use Case] [SEC=UNCLASSIFIED]

Dear all, 

Regrets for the f2f. I feel obliged to add my two cents; have thought about and written about the trans-disciplinary (and temporal) nature of space and spatiality a lot (most recently Space in Mind [1]) . 

My take: we seek to model natural phenomena, which have co-equal spatial and temporal descriptors...whether a particular study examines (or has data for) both dimensions, both exist. Our models should be designed to capture (and permit computing over) the essential qualities of their subjects, and that includes space and time for all natural phenomena. 

In recent discussions about adding time to GeoJSON, which models geographic features, we considered that there are "event-like features" and sought to add a {"when": ""} object to a feature description (the already existing {"geometry": ""} is the "where." The contents of a "when" object would be expressions for instants and intervals as described by existing ontologies, like Owl:Time, and might be extended by references to calendars and ways of addressing "fuzzy" temporal bounds. 

Sadly, the discussion bogged down - or perhaps simply got upstaged by a more fruitful work on GeoJSON-LD that arose at the same time; some discussion appears in "closed issues" [2]. I have not dropped it and will be proposing something further within the next few months. 

Somewhat related: in historical and archaeological studies, there are some entities that demonstrate the ways that place and period are intertwined, for example "Iron Age Britain" and "Middle Bronze Age Southern Levant." 

One last data point I'll mention I haven't heard raised here is the current version of CIDOC-CRM, which has added E92-SpaceTime Volume [3] and associated classes and properties. 


[1] Montello, D.R., Grossner, K., Janelle, D.G (Eds.) (2014). Space in Mind: Concepts for Spatial Learning and Education . Cambridge, MA: MIT Press 

Karl Grossner, PhD 
Center for Interdisciplinary Digital Research (CIDR) 
Stanford University Libraries 
Stanford,CA US 

----- Original Message -----

> > "From my perspective in managing climate data, all of our data is
> > time-series
> > spatial data. It is very important to understand the ‘when’ as well as
> > there
> > ‘where’ with respect to the data (together with the data provenance etc)."
> Bruce's use case is certainly an important one and we need to make sure we
> can handle it. But I think it is still possible to separate out time and
> location concerns in the sense of vocabularies and data representation
> patterns. For a particular data point (or event or whatever), an approach
> like RDF Data Cube, or similar n-ary relationship, can link the data point
> to the appropriate location and time.

> So (as I see it) the location specification itself does not need to
> incorporate a concept of time in this case, but rather each data point needs
> to connect both to a location and a time period. Let me know Bruce if I am
> missing something important here!

> (A separate issue is where a location named by an identifier might change
> it's definition over time - eg 'London' is bigger now than it was a hundred
> years ago).

> Cheers

> Bill

Received on Wednesday, 11 March 2015 04:58:00 UTC