Emanuele Storti

Ontology-Driven KDD Process Composition

One of the most interesting challenges in Knowledge Discovery in Databases (KDD) field is giving support to users in the composition of tools for forming a valid and useful KDD process. Such an activity implies that users have both to choose tools suitable to their knowledge discovery problem, and to compose them for designing the KDD process. To this end, they need expertise and knowledge about functionalities and properties of all KDD algorithms implemented in available tools. In order to support users in this heavy activity, in this paper we introduce a goal-driven procedure for automatically compose algorithms. The proposed procedure is based on the exploitation of KDDONTO, an ontology formalizing the domain of KDD algorithms, allowing us to generate valid and non-trivial processes.

A Logic-Based Formalization of KPIs for Virtual Enterprises

Open innovation is gaining increasing interest as a model to foster innovation through collaboration and knowledge sharing among organizations, especially in the context of Virtual Enterprises (VE). One of the main issues to overcome in such distributed settings is the integration of heterogeneous data, and the need to evaluate common Key Performance Indicators (KPI) capable to measure overall performances of the VE. In this paper we propose a conceptualization of KPIs into an ontology, to provide a common vocabulary to semantically annotate data belonging to different organizations. KPIs are described in terms of dimensions and a mathematical formula. In order to support reasoning services over KPIs formulas we refer to a logic-based formalization in Prolog, where formulas are translated as facts, and several predicates are included to support both mathematical functionalities for formula manipulation and higher-level functions especially suited for VE setup.

Mining usage patterns from a repository of scientific workflows

In many experimental domains, especially e-Science, workflow management systems are gaining increasing attention to design and execute in-silico experiments involving data analysis tools. As a by-product, a repository of workflows is generated, that formally describes experimental protocols and the way different tools are combined inside experiments. In this paper we describe the use of the SUBDUE graph clustering algorithm to discover sub-workflows from a repository. Since sub-workflows represent significant usage patterns of tools, the discovered knowledge can be exploited by scientists to learn by-example about design practices, or to retrieve and reuse workflows. Such a knowledge, ultimately, leverages the potential of scientific workflow repositories to become a knowledge-asset. A set of experiments is conducted on the my Experiment repository to assess the effectiveness of the approach.

A Semantic Framework for Knowledge Management in Virtual Innovation Factories

Knowledge management is a crucial aspect for enterprises that want to effectively cope with business innovation. However, the full control of the knowledge asset is often missing due to the lack of precise organizational models, policies, and proper technologies, especially in Virtual Enterprises VEs, which are characterized by heterogeneous partners with different policies, skills and know-how. For such reasons, the need for technologies that enable knowledge sharing, efficient access to knowledge resources, and interoperability is felt as primary. This work proposes a semantics-based infrastructure aimed at supporting effective knowledge management for business innovation in VEs. Knowledge resources are formally represented and stored in a semantic layer, which is exploited by a set of semantic services for enabling efficient retrieval and reasoning capabilities to derive additional knowledge.

SemPI: A semantic framework for the collaborative construction and maintenance of a shared dictionary of performance indicators

Abstract Collaboration at strategic level entails the sharing of Performance Indicators (PIs) to measure the achievement of common objectives and evaluate performances. PIs are synthetic measures calculated starting from transactional data. Given their compound nature, it is difficult to achieve an agreement on their definitions and heterogeneities arise that make sharing and exchange a difficult task. Semantic techniques can help to address these challenges by providing a common layer of formal definitions and automatic reasoning tools to maintain its consistency. In this paper, we present a novel semantic framework for representing Performance Indicators that supports the construction and maintenance of a minimal and consistent dictionary. The distinctive feature of the approach is the logical representation of formulas defining PIs, allowing to make algebraic relationships among indicators explicit, and to reason over these relationships to derive PI identity and equivalence and to enforce the overall consistency of the dictionary. We also present a web application implementing the framework for collaborative construction and maintenance of the dictionary. We provide experimental evidence of the efficiency and effectiveness of the approach on synthetic and real data.

Extended drill-down operator: Digging into the structure of performance indicators

Performance measurement is the subject of interdisciplinary research on information systems, organizational modeling and decision support systems. The data cube model is usually adopted to represent performance indicators (PI) and enable flexible analysis, visualization and reporting. However, the major obstacles against effective design and management of PI monitoring systems are related to the facts that PIs are complex objects with an aggregate/compound nature. This often leads to unawareness of indicator semantics as well as of dependencies among indicators. In this work, we propose to enrich the data cube model with the formal description of the structure of an indicator given in terms of its algebraic formula and aggregation function. Such a model enables the definition of a novel operator, namely indicator drill‐down, which relies on formula manipulation functionalities and reasoning. Like the usual drill‐down, this operator increases the detail of a measure of the data cube by expanding an indicator into its components. Thus, the two notions of drill‐down are integrated, allowing a novel way of data exploration. As a proof‐of‐concept, an implementation of the approach is presented. The evaluation of the implementation on real and synthetic scenarios enlightens the effectiveness and the efficiency of the approach. Copyright

Collaborative Building of an Ontology of Key Performance Indicators

In the present paper we propose a logic model for the representation of Key Performance Indicators (KPIs) that supports the construction of a valid reference model (or KPI ontology) by enabling the integration of definitions proposed by different engineers in a minimal and consistent system. In detail, the contribution of the paper is as follows: (i) we combine the descriptive semantics of KPIs with a logical representation of the formula used to calculate a KPI, allowing to make the algebraic relationships among indicators explicit; (ii) we discuss how this representation enables reasoning over KPI formulas to check equivalence of KPIs and overall consistency of the set of indicators, and present an empirical study on the efficiency of the reasoning; (iii) we present a prototype implementing the approach to collaboratively manage a shared ontology of KPI definitions.

A virtual mart for knowledge discovery in databases

The Web has profoundly reshaped our vision of information management and processing, enlightening the power of a collaborative model of information production and consumption. This new vision influences the Knowledge Discovery in Databases domain as well. In this paper we propose a service-oriented, semantic-supported approach to the development of a platform for sharing and reuse of resources (data processing and mining techniques), enabling the management of different implementations of the same technique and characterized by a community-centered attitude, with functionalities for both resource production and consumption, facilitating end-users with different skills as well as resource providers with different technical and domain specific capabilities. We first describe the semantic framework underlying the approach, then we demonstrate how this framework is exploited to give different functionalities to users through the presentation of the platform functionalities.

Data Mart Reconciliation in Virtual Innovation Factories

The present paper deals with the problem of collaboration at strategic level in innovation-oriented Virtual Enterprises. The problem is taken from the perspective of sharing a special kind of data, Key Performance Indicators, that are measures adopted to monitor the achievement of certain strategic goals. We discuss the main conflicts that can arise in measures coming from autonomous enterprises, adopting the conceptual multidimensional cube model. Then we propose a novel semantic model to deal with conflicts related to the structure of a measure, that arise when the “same” KPI is calculated in different ways by different enterprises. Finally, conflict reconciliation strategies enabled by the semantic model are discussed.

Extending Drill-Down through Semantic Reasoning on Indicator Formulas

Performance indicators are calculated by composition of more basic pieces of information, and/or aggregated along a number of different dimensions. The multidimensional model is not able to take into account the compound nature of an indicator. In this work, we propose a semantic multidimensional model in which indicators are formally described together with the mathematical formulas needed for their computation. By exploiting the formal representation of formulas an extended drill-down operator is defined, which is capable to expand an indicator into its components, enabling a novel mode of data exploration. Effectiveness and efficiency are briefly discussed on a prototype introduced as a proof-of concept.