Linking research & learning technologies through standards

As in other sectors, schools have long been burdened with the incompatibility of the multiple IT systems used to run their business. The Learning Management Systems, the Student Enrolment Systems, the systems dealing with assessment, pastoral care, attendance, staffing, timetabling—all of these store data about the same students in different ways, and each exports data in its own way. To get the systems to share data between each other has often meant costly custom porting for each pair—where it has not involved printing the data out, and rekeying it from scratch. Waving printouts at a keyboard is not, of course, fulfilling the promise of the paperless office, and it hardly translates to data at one’s fingertips.

The school sector realised quite early (1998) that something could be done about this, and the Systems Interoperability Framework (SIF) was developed Stateside in response to it. SIF was developed several years before Service-Oriented Architecture started to address similar issues of data incompatibility in industry, but it takes an approach similar enough that it can be stated in SOA terms. Data is exchanged between systems across a common trust environment, using common data structures in XML—just like the Enterprise Service Bus and SOAP of SOA. Systems are able to exchange data because agents translate their native data to the common formats and back again. Data can be pulled in, in a request–response pattern, or pushed out, in a subscription pattern. Unlike SOA, the protocols and common data models are standardised and fixed ahead of time for the school domain, and do not require the systems to be reengineered to fit the system protocols better; so SIF can be layered over existing systems relatively straightforwardly.

The recent trend in the Australian government school sector, and to a growing extent in the Catholic sector, has been to host school systems centrally; this leads to greater efficiencies and security in how data is handled and exchanged, and relieves schools from the burden of having to run systems themselves. However, jurisdictions still have to deal with multiple systems internally, some more centralised than others. They also have occasion to exchange data with other jurisdictions and schools, especially when students move interstate, or in dealing with national testing and benchmarking. Dealing with these issues has made SIF an attractive proposition for the Australian school sector, whether to support the integration of all their internal systems, as is taking place in Victoria, or to provide a consistent outward interface to the data they are authorised to share. This has led to the SIF Association AU initiative, led by representatives from all Australian school systems.

As a relatively lightweight technical architecture, SIF does not particularly depend on where it is deployed, and there have already been several successful deployments of SIF in the UK, in addition to the pilots now underway in Australia. What does need to change from place to place is the model underlying the common data format that the system uses. The original SIF data model deals with the realities of the American school system, so it represents data that makes sense for that context. Because students are provided lunch at school, the logistics of school canteens are a major concern of SIF data modelling, and there are obvious dollar and cent efficiencies in getting the canteen system to talk to the student attendance system. When Australian school systems exchange information, canteen logistics are not a major concern; but getting timetabling right is.

Likewise, the data fields and values captured in SIF reflect American conventions and requirements: they deal in quarters and quinmesters, charter schools, and demographics driven by the American Census and the NCES. The data collected and exchanged in Australian schools needs to reflect Australian requirements, and to conform to Australian norms and conventions. So data is about ESL, not English Proficiency, and the codes for countries and languages are the Australian Bureau of Statistics’. Dealing with these codes in turn means addressing questions such as how many different shades of “Not Applicable” to allow for Yes/No fields, or whether to include both the nodes and the leaves in a hierarchical vocabulary (e.g. whether to allow Netherlandic as a language choice, or only its child nodes, Dutch and Frisian).

Link Affiliates and the ABS, along with members of the SIF-AU data working group, gave feedback on how best to specify the data objects and vocabularies to be used. The SIF-AU draft standard is now being vetted by SIF; meanwhile, pilot projects are underway in several jurisdictions, with an aim to finalise work by the end of the year.