Business information systems; Knowledge graph engineering; Knowledge management; Ontology engineering; Linked data; Graph learning; Semantic web; Internet-of-things.
Armin Haller is an Associate Professor of Business Information Systems. His research interests include knowledge graph engineering, ontology engineering, linked data, the Internet-of-Things and the semantic Web in general. Armin has received funding from organisations including: the Department of Finance, to develop an ontology framework for government information and an open-source software that allows domain experts to maintain knowledge graphs called Schímatos; and from the Australian Research Council’s Linkage Program, for a project with Sydney Trains. He has published in the most prominent academic journals and conferences in his field, including Journal of Web Semantics, Semantic Web Journal, Applied Ontology, World Wide Web Conference and the International Semantic Web Conference. Armin engages with the Australian ICT industry through his managing of the W3C Office Australia. He is also active in several W3C working groups, where he chaired the Semantic Sensor Network Ontology working group. This work has resulted in an international standard for the description of sensors and actuators on the Internet-of-Things and has been published in two journal articles. Armin is a passionate evangelist of Open Government Data and, to this end, has chaired Australian Government Linked Data Working Group for the last 7 years.
Haller, A & Polleres, A 2020, 'Are we better off with just one ontology on the Web?', Semantic Web, vol. 11, no. 1, pp. 87-99.
Oliveira, D, Butt, A, Haller, A et al 2019, 'Where to search top-K biomedical ontologies?', Briefings in Bioinformatics, vol. 20, no. 4, pp. 1475-1491.
Janowicz, K, Haller, A, Cox, S et al 2019, 'SOSA: A lightweight ontology for sensors, observations, samples, and actuators', Journal of Web Semantics, vol. 56, pp. 1-10.
van den Brink, L, Barnaghi, P, Tandy, J et al 2019, 'Best Practices for Publishing, Retrieving, and Using Spatial Data on the Web', Semantic Web, vol. 10, no. 1, pp. 95-114.
Haller, A, Janowicz, K, Cox, S et al 2018, 'The Modular SSN Ontology: A Joint W3C and OGC Standard Specifying the Semantics of Sensors, Observations, Sampling, and Actuation', Semantic Web, vol. 10, no. 3, pp. 1-23pp.
Ranjan, R, Thakker, D, Haller, A et al 2017, 'A note on exploration of IoT generated big data using semantics', Future Generation Computer Systems, vol. 76, pp. 495-498pp.
Lefort, L, Haller, A, Taylor, K et al 2017, 'The ACORN-SAT Linked Climate Dataset', Semantic Web, vol. 8, no. 6, pp. 959-967pp.
Butt, A, Haller, A & Xie, L 2016, 'RecOn: Ontology recommendation for structureless queries', Applied Ontology, vol. 11, no. 4, pp. 301-324pp.
Butt, A, Haller, A & Xie, L 2016, 'DWRank: Learning concept ranking for ontology search', Semantic Web, vol. 7, no. 4, pp. 447-461.
Butt, A, Haller, A & Xie, L 2015, 'A Taxonomy of Semantic Web Data Retrieval Techniques', 8th International Conference on Knowledge Capture K-CAP 2015, Association for Computing Machinery (ACM), New York,USA, pp. 1-9.
Speiser, S, Junghans, M & Haller, A 2014, 'Linked Data Services', in Andreas Harth, Katja Hose, and Ralf Schenkel (ed.), Linked Data Management, Taylor & Francis Group, Boca Raton, Florida, pp. 439-457pp.
Department of Finance, An ontology framework for government information, 2018. (Sole CI)
ARC Linkage Grant, LP160100910, Preventing railway suicide: An open-systems perspective,with Sydney Trains, 2016.
Editorial Board for Semantic Web Journal
Special Issue Editor for Journal of Web Semantics
MBA Director at RSM from 2017 to 2019
Deputy Director of Engagement and Outreach from 2018 to 2019
Armin has been teaching postgraduate and PhD courses, and is currently convening Digital Transformation at RSM and Introduction to Programming for Data Scientists at RSCS. He supervises students at Honours, Masters and PhD levels in both Schools. Armin has received the College of Engineering and Computer Science Dean's Award for Excellence in Teaching in the Outstanding Contribution to Student Learning Category in 2016.
COMP7230 Introduction to Programming for Data Scientists,
INFS7040 Digital Transformation
COMP7230 Introduction to Programming for Data Scientists
INFS7040 e-Commerce for Managers