Riccardo Martoglia

Bio: Riccardo Martoglia is an academic researcher from University of Modena and Reggio Emilia. The author has contributed to research in topics: XML & Semantic Web. The author has an hindex of 16, co-authored 112 publications receiving 866 citations.

Standards, Security and Business Models: Key Challenges for the IoT Scenario

Abstract: The number of physical objects connected to the Internet constantly grows and a common thought says the IoT scenario will change the way we live and work. Since IoT technologies have the potential to be pervasive in almost every aspect of a human life, in this paper, we deeply analyze the IoT scenario. First, we describe IoT in simple terms and then we investigate what current technologies can achieve. Our analysis shows four major issues that may limit the use of IoT (i.e., interoperability, security, privacy, and business models) and it highlights possible solutions to solve these problems. Finally, we provide a simulation analysis that emphasizes issues and suggests practical research directions.

Semantic peer, here are the neighbors you want!

Abstract: Peer Data Management Systems (PDMSs) have been introduced as a solution to the problem of large-scale sharing of semantically rich data. A PDMS consists of semantic peers connected through semantic mappings. Querying a PDMS may lead to very poor results, because of the semantic degradation due to the approximations given by the traversal of the semantic mappings, thus leading to the problem of how to boost a network of mappings in a PDMS.In this paper we propose a strategy for the incremental maintenance of a flexible network organization that clusters together peers which are semantically related in Semantic Overlay Networks (SONs), while maintaining a high degree of node autonomy. Semantic features, a summarized representation of clusters, are stored in a "light" structure which effectively assists a newly entering peer when choosing its semantically closest overlay networks. Then, each peer is supported in the selection of its own neighbors within each overlay network according to two policies: Range-based selection and k-NN selection. For both policies, we introduce specific algorithms which exploit a distributed indexing mechanism for efficient network navigation. The proposed approach has been implemented in a prototype where its effectiveness and efficiency have been extensively tested.

Flexible query answering on graph-modeled data

Abstract: The largeness and the heterogeneity of most graph-modeled datasets in several database application areas make the query process a real challenge because of the lack of a complete knowledge of the vocabulary used, as well as of the information about the structural relationships between the data.To overcome these problems, flexible query answering capabilities are an essential need. In this paper we present a general model for supporting approximate queries on graph-modeled data. Approximation is both on the vocabularies and the structure. The model is general in that it is not bound to a specific graph data model, rather it gracefully accommodates labeled directed/undirected data graphs with labeled/unlabeled edges. The query answering principles underlying the model are not compelled to a specific data graph, instead they are founded on properties inferable from the data model the data graph conforms to. We complement the work with a ranking model to deal with data approximations and with an efficient top-k retrieval algorithm which smartly accesses ad-hoc data structures and generates the most promising answers in an order correlated with the ranking measures. Experimental results prove the good effectiveness and efficiency of our proposal on different real world datasets.

SRI: exploiting semantic information for effective query routing in a PDMS

Abstract: The huge amount of data available from Internet information sources has focused much attention on the sharing of distributed information through Peer Data Management Systems (PDMSs). In a PDMS, peers have a schema on their local data, and they are related each other through semantic mappings that can be defined between their own schemas.Querying a PDMS means either flooding the network with messages to all peers or take advantage of a routing mechanism to reformulate a query only on the best peers selected according to some given criteria. As reformulations may lead to semantic approximations, we deem that such approximations can be exploited for locating the semantically best directions to forward a query to.In this paper, we propose a distributed index mechanism where each peer is provided with a Semantic Routing Index (SRI) for routing queries effectively. A fuzzy-oriented model for SRI is presented where operations for creating and maintaining SRIs are well-founded. In addition, we show how SRIs can be employed in the query processing phase with the aim of reducing the space of reformulations. Finally, we conduct a series of meaningful experiments showing the effectiveness of the proposed approach.

Communications of the ACM

Abstract: Communications of the ACM (CACM for short, not the best sounding acronym around) is the ACM’s flagship magazine. Started in 1957, CACM is handy for keeping up to date on current research being carried out across all topics of computer science and realworld applications. CACM has had an illustrious past with many influential pieces of work and debates started within its pages. These include Hoare’s presentation of the Quicksort algorithm; Rivest, Shamir and Adleman’s description of the first publickey cryptosystem RSA; and Dijkstra’s famous letter against the use of GOTO. In addition to the print edition, which is released monthly, there is a fantastic website (http://cacm.acm. org/) that showcases not only the most recent edition but all previous CACM articles as well, readable online as well as downloadable as a PDF. In addition, the website lets you browse for articles by subject, a handy feature if you want to focus on a particular topic. CACM is really essential reading. Pretty much guaranteed to contain content that is interesting to anyone, it keeps tabs on the latest in computer science. It is a valuable asset for us students, who tend to delve deep into a particular area of CS and forget everything that is happening around us. — Daniel Gooch U ndergraduate research is like a box of chocolates: You never know what kind of project you will get. That being said, there are still a few things you should know to get the most out of the experience.

Query languages for graph databases

Abstract: Query languages for graph databases started to be investigated some 25 years ago. With much current data, such as linked data on the Web and social network data, being graph-structured, there has been a recent resurgence in interest in graph query languages. We provide a brief survey of many of the graph query languages that have been proposed, focussing on the core functionality provided in these languages. We also consider issues such as expressive power and the computational complexity of query evaluation.

PARIS: Probabilistic Alignment of Relations, Instances, and Schema

Abstract: One of the main challenges that the Semantic Web faces is the integration of a growing number of independently designed ontologies. In this work, we present PARIS, an approach for the automatic alignment of ontologies. PARIS aligns not only instances, but also relations and classes. Alignments at the instance level cross-fertilize with alignments at the schema level. Thereby, our system provides a truly holistic solution to the problem of ontology alignment. The heart of the approach is probabilistic, i.e., we measure degrees of matchings based on probability estimates. This allows PARIS to run without any parameter tuning. We demonstrate the efficiency of the algorithm and its precision through extensive experiments. In particular, we obtain a precision of around 90% in experiments with some of the world's largest ontologies.