An ontological characterization of time-series and state-sequences for data mining

Time-series and sequences are important patterns in data mining. Based on an ontology of time-elements, this paper presents a formal characterization of time-series and state-sequences, where a state denotes a collection of data whose validation is dependent on time. While a time-series is formalized as a vector of time-elements temporally ordered one after another, a state-sequence is denoted as a list of states correspondingly ordered by a time-series. In general, a time-series and a state-sequence can be incomplete in various ways. This leads to the distinction between complete and incomplete time-series, and between complete and incomplete state-sequences, which allows the expression of both absolute and relative temporal knowledge in data mining.

The illusions of competition in the water sector: a response to the OFWAT/Cave consultations on introducing competition in the water sector in England and Wales

The paper provides a critical review of the role of liberalisation and competition in the water sector, based on empirical evidence from the UK and internationally. The paper is submitted as evidence to the official reviews of competition in water sector in England and Wales.