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[UPDATE: Fixed some formatting]

Creative Commons Licence
Round table on vocabularies for describing research data: where’s my semantic web? by Peter Sefton is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.

Summary: in this post I talk about an experimental semantic website for describing what I’m calling ‘research context’, wondering if such as site can be used as a ‘source of truth’ for metadata entry, for example when someone is uploading a file into a research data repository. The post assumes some knowledge of linked data and RDF and/or an interest in eResearch software architecture.

Thanks to twitter correspondents Jodi Schneider, Kristi Holmes and Christopher Gutteridge.

On Friday 7th September I attended a meeting at Intersect about metadata vocabularies for managing research data, in the context of projects sponsored by the Australian National Data Service (ANDS). Ingrid Mason asked me to talk about my experiences describing research data. I approached this by starting with a run-through of the talk Peter Bugeia and I put together for Open Repositories with an emphasis on our attempts to use Linked Data principles for metadata. In this work we encountered two big problems, which I brought to the round-table session as questions.

  1. It’s really hard to work out which ontology, or set of vocabulary terms to use to describe research context. Take ‘experiment’ what is a good linked data term for that?

    Q. What to use as a URI for an experiment?

  2. In trying to build linked-data systems I have not found any easy to use tools. (I got lots of useful leads from Kristy Holmes and Jodi Schneider on Twitter, more on that below).

    Q. Where’s my semantic web!

Answers at the end of the post, but you have to read the whole thing anyway.

The problem I’m working on at the moment with colleagues at the University of Western Sydney is how we can provide a framework for metadata about research data. We’re after efficient interfaces for researchers to contextualise research data sets, across lots of different research domains where the research context looks quite different.

For example, take the HIEv system at the Hawkesbury Intitute for the Environment (HIE). HIEv is basically a file-repository for research data files. It has information about each file (size, type, date range etc) and contextual metadata about the research context, in this case using a two-part hierarchy: Facility / Experiment where facilities are associated with multiple experiments and files are associated with experiments. Associating a data file with research context is easy in HIEv because it’s built in to the system. A human or machine uploading a data file associates it with an experiment using a form, or a JSON data structure respectively. The framework for describing research context is built-in to the application, and the data lives in its internal database.

This approach works well, until:

  1. We try to re-use the software behind HIEv in another context, maybe one where the research domain does not centre on facilities, or experiment is not quite the right concept, or the model needs to be further elaborated.

    Example: In the MyTardis project, a development team added an extra element to that package’s research hierarchy – porting the application to new domains means substantial rework. See this message on their mailing list.

  2. We want to re-use the same contextual descriptions to describe research data in another system where we are faced with either programming a whole new framework for the same context, or adding a new interface for our new system to talk to the research context framework in the old one.

    Example: At HIE, with the help of some computing students, Gerry Devine and I are exploring the use of OwnCloud (the dropbox-like Share/Sync/See application) to manage working files, with a simple forms interface to add them to HIEV. As it stands the students have to replicate the Facility/Experiment data in their system, meaning they are hard-coding facility / Experiment hierarchies into HTML forms.


Gerry Devine and I have been sketching an architecture designed to help out in both of these situations. The idea is to break-out the description of the research-context into a well-structured application. This temporary site of Gerry’s, shows what it might look like in one aspect, a web site which describes stuff at HIE; facilities, and their location, experiments taking place at those facilities, and projects. The question we’re exploring is: can we maintain a description of the HIE research context in one place, such as an institute research site or wiki, and have our various data-management applications use that context, rather than having to build the same research-context framework into each app and populate with lists of values? Using a human-readable website as the core home for research context information is appealing because it solves another problem, getting some much needed documentation on the research happening at our organisation online.

Here’s an interaction diagram showing what might transpire when a researcher wants to use a file management application, such as ownCloud (app) to upload some data to HIEv, the working data repository at the institute:


We don’t have much of this implemented, but last week I had a play with the research context website part of the picture (the system labelled ‘web’, in the above diagram). I wanted to see if I could create a web site like the one Gerry made, but with added semantics, so that when an application, like an ownCloud plugin asked ‘gimme research context’ it could return a list of facilities, experiments and projects in machine readable form.

For a real institute or organisation-wide research context management app, you’d want to have an easy to use point and click interface, but for the purposes of this experiment I decided to go with one of the many markdown-to-html tools. See this page which summarises why you’d want to useone andlists an A-Z of alternatives.This is the way many of the cool kids make their sites theses days – they maintain pages as markdown text files, kept under version control and run a script to spit out a static website. Probably the best-known of these is Jekyl, which is built in to GitHub. I chose Poole because it’s Python, a language in which I can get by, and it is super-simple, and this is after-all just an experiment.

So, here’s what a page looks like in Markdown. The top part of the file, up to ‘—–’ is metadata which can be used to lay out the page in a consistent way. Below the line, is structured markup. # Means “Heading level 1” (h1), ## is ‘h2’ and so on.

title: Glasshouse S30
long: 150.7465
lat:  -33.6112
typeOf: @facility
full_name: Glasshouse facility at UWS Hawkesbury building S30
code: GHS30
description: Glasshouse in the S-precinct of the University of Western Sydney, Hawkesbury Campus, containing eight naturally lit and temperature-controlled compartments (3 x 5 x 3.5m, width x length x height). This glasshouse is widely used for short-term projects, often with a duration of 2-3 months. Air temperature is measured and controlled by an automated system at user-defined targets (+/- 4 degrees C) within each compartment. The concentration of atmospheric carbon dioxide is controlled within each compartment using a system of infrared gas analyzers and carbon dioxide injectors. Supplementary lighting will be installed in 2013.
---

Contact: Renee Smith (technician, R.Smith@uws.edu.au), John Drake (Post-doc, je.drake@uws.edu.au), Mike Aspinwall (Post-doc, m.aspinwall@uws.edu.au).

# References: 

Smith, R. A., J. D. Lewis, O. Ghannoum, and D. T. Tissue. 2012. Leaf structural responses to pre-industrial, current and elevated atmospheric CO2 and temperature affect leaf function in Eucalyptus sideroxylon. Functional Plant Biology 39:285-296.

Ghannoum, O., N. G. Phillips, J. P. Conroy, R. A. Smith, R. D. Attard, R. Woodfield, B. A. Logan, J. D. Lewis, and D. T. Tissue. 2010. Exposure to preindustrial, current and future atmospheric CO2 and temperature differentially affects growth and photosynthesis in Eucalyptus. Global Change Biology 16:303-319.



# Data organisation overview

There have been a large number of relatively short-duration experiments in the Glasshouse S30 facility, often with multiple nested projects within each experiment.  The file naming convention captures this hierarchy.



# File Naming Convention

Convention: GHS30_<EXPERIMENT>_<PROJECT>_<VARIABLE COLLECTION CODE>_<DATA PROCESSING>_<DATE or DATERANGE>[_<VERSION>].<filetype>

The resulting HTML looks like this:

But wait, there’s more! Inside the human-readable HTML page is some machine-readable code to say what this page is about using linked-data principles. The best way I have been able to work out how to describe a facility is using the Eagle-I ontology, where I think the appropriate term for what HIE calls a facility is ‘core-laboratory’. You can browse the ontology and tell me if I’m right. This says that the glasshouse facilty is a type of core-laboratory.

<section
resource="http://uws.edu.au/facilities/glasshouse-s30.html"
typeof="http://vivoweb.org/ontology/core#CoreLaboratory">
<h1 property="dc:title">Glasshouse facility at UWS
Hawkesbury building S30</h1>

(I’m not an RDF expert so if I have this wrong somebody please tell me! And yes, I know there are issues to consider here What URIs should we use for naming facilities and other contextual things? Should we use Handles? PURLS? Plain old URLs like the one above?)


The code that produced this snippet is really simple, but I did have to code it:

def hook_postconvert_semantics():
    for p in pages:
        if p.typeOf <> None:
            p.html = "\n\n<section resource='http://hie.uws.edu.au/research-context/%s' \
                typeof='%s'>\n\n%s\n\n<section>\n\n" % (p.url, types[p.typeOf], p.html)

Now, the part that I’m quite excited about is that if you point an RDFa distiller at this you get the following. This is JSON-LD format which is (sort of) RDF wrapped up in JSON. Part time programmers like me often find RDF difficult to deal with, but everyone loves JSON, you can slurp it up into a variable in your language of choice and access the data using native idioms.

{
    "@context": {
        "dcterms": "http://purl.org/dc/terms/"
    }, 
    "@graph": [
      
        {
            "@id": "facilities/glasshouse-s30.html", 
            "@type": "http://vivoweb.org/ontology/core#CoreLaboratory", 
            "http://www.w3.org/2003/01/geo/wgs84_pos#long": {
                "@value": "150.7465", 
                "@language": "en"
            }, 
            "dcterms:title": {
                "@value": "Glasshouse facility at UWS Hawkesbury building S30", 
                "@language": "en"
            }, 
            "http://www.w3.org/2003/01/geo/wgs84_pos#lat": {
                "@value": "-33.6112", 
                "@language": "en"
            }
        }
    ]

That might look horrible to some, but should be easy for our third-year comp-sci students to deal with. Iterate over the items in the @graph array, find those where @type is equal to “http://vivoweb.org/ontology/core#CoreLaboratory”, get the title, and build a drop-down list for the user, to associate their data file with this facility (using the ID). This potentially lets us de-couple our file management app from our HIEv repository, from our Research Data repository, and let them all share the same ‘source of truth’ about research context. In library terms, my hacked-up version of Gerry’s website is acting as a name-authority for entities in the HIE space.

There is a lot more to cover here, including how experiments are associated with facilities, and how, when a user publishes a data set from HIEv a file can be linked to a facility/experiment combination using a relation “wasGeneratedBy” from the World Wide Web Consortium’s PROV (provenance) ontology.

As I noted above, the markdown based approach is not going to work for some user communities. What is needed to support this general design pattern, assuming that one would want to, is some kind of combination of a research-context database application and a web content management system (CMS). A few people, including Jodi Schneider suggested I look at Drupal, the open source CMS. Drupal does ‘do’ RDF, but not without some serious configuration.

Jodi also pointed me to VIVO, which is used for describing research networks, usually focussing on people more than on infrastructure or context. I remember from a few years ago a presentation from one of the VIVO people that said very explicitly that VIVO was not designed to be a source of primary data so I wondered if it was appropriate to even consider it as a place to enter, rather than index and display data. The VIVO wiki says it is possible, but building a site with the same kind of content as Gerry’s would be a lot of work just as it would be in Drupal.

Oh, and those answers? Well thanks to Arif Shaonn from the University of New South Wales, I know that http://www.w3.org/ns/prov#Activity is probably a good general type for experiments (no, I’m going to define an ontology of my own, I already have enough pets).

And where’s my semantic web? Well, I think we may need to build a little more proof-of-concept infrastructure to see if the idea of a research-context CMS acting as a source of truth for metadata makes sense, and if so, make the case for building it as part of future eResearch data-management apps.

My dodgy code including the input and output files for a small part of Gerry’s website is on github, to run it you’ll need to install Poole first.


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