Despite recent progresses in methods for processing data about the movement of objects in the geographic space, some fundamental issues remain unresolved. One of them is how to describe movement segments (e.g., semantic trajectories, episodes like stops and moves) and diverse movement patterns (e.g., moving clusters, hotel-restaurant-shop-hotel), with formal semantic descriptions. Another issue is how to arrange descriptive data and measures in a Movement Data Warehouse (MDW) for powerful information analyses and reasonable performance. This paper introduces general definitions for movement segments, movement patterns, their categories and hierarchies. The proposed constructs are semantically enriched with references to concepts (categories) and/or instances of these concepts (objects) arranged in distinct hierarchies. Based on these constructs, we propose a semantic multidimensional model for MDW. A case study illustrates the expressiveness of the proposal for analyzing movement data collected via social media and semantically enriched with Linked Open Data (LOD).

Technological advances in sensing technologies and wireless telecommunication devices enable novel research fields related to the management of trajectory data. As it usually happens in the data management world, the challenge after storing the data is the implementation of appropriate analytics for extracting useful knowledge. However, traditional data warehousing systems and techniques were not designed for analyzing trajectory data. Thus, in this work, we demonstrate a framework that transforms the traditional data cube model into a trajectory warehouse. As a proof-of-concept, we implemented T-WAREHOUSE, a system that incorporates all the required steps for Visual Trajectory Data Warehousing, from trajectory reconstruction and ETL processing to Visual OLAP analysis on mobility data.

Studies on the relationship between label consistency, computability, and complexity assume the existence of local orientation; this assumption is in fact at the basis of the point-to-point model and is realistic for systems where a communication link can connect only two entities. However, in systems which use more advanced communication and interconnection technology, such as buses, optical networks, and wireless communication media, and more importantly, in heterogeneous systems (such as the Internet) which include any combination of the above, local orientation cannot be assumed. This implies that the entire established body of results on the relationship between label consistency (e.g., sense of direction}) and computability and complexity does not hold for systems with advanced communication technology. In this paper we consider a new type of consistency which we shall call backward consistency and which, unlike sense of direction, can exist even without local orientation. Thus, unlike all previous forms of consistency, it can be found (or designed) in advanced distributed systems. We study backward consistency both in terms of its relationship with the traditional properties of local orientation and (weak) sense of direction, and with respect to symmetries of the edge labelings and of the naming functions. We show that backward consistency is computationally equivalent to sense of direction; in other words, it is possible to take advantage of the computational power of sense of direction even in the absence of local orientation.

The studies on the relationship between label consistency, computability and complexity assume the existence of local orientation; this assumption is in fact at the basis of the point-to-point model and is realistic for systems where a communication link can connect only two entities.However, in systems which use more advanced communication and interconnection technology such as buses, optical networks, wireless communication media, etc., and more importantly, heterogeneous systems (such as internet) which include any combination of the above, local orientation can not be assumed.In this paper we consider a new type of consistency which we shall call backward consistency and which, unlike sense of direction, can exist even without local orientation.Thus, unlike all previous forms of consistency, it can be found (or designed) in advanced distributed systems.We study backward consistency both in terms of its relationship with the traditional properties of local orientation and (weak) sense of direction, and with respect to symmetries of the edge labelings and of the naming functions.We prove that backward consistency is computationally equivalent to sense of direction; in other words, it is possible to take advantage of the computational power of sense of direction even in absence of local orientation.'Research supported in part by F.C.A.R and N3.E.R.C permission to make digital or hard copies of all