SAMOS - A framework for model analytics and management

The increased popularity and adoption of model-* engineering paradigms, such as model-driven and model-based engineering, leads to an increase in the number of models, metamodels, model transformations and other related artifacts. This calls for automated techniques to analyze large collections of those artifacts to manage model-* ecosystems. SAMOS is a framework to address this challenge: it treats model-* artifacts as data, and applies various techniques—ranging from information retrieval to machine learning—to analyze those artifacts in a holistic, scalable and efficient way. Such analyses can help to understand and manage those ecosystems

Using ATL transformation services in the MDEForge collaborative modeling platform

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-42064-6_5In the last years, the increasing complexity of Model-Driven Engineering (MDE) tools and techniques has led to higher demands in terms of computation, interoperability, and configuration management. Harnessing the softwareas- a-service (SaaS) paradigm and shifting applications from local, mono-core implementations to cloud-based architectures is key to enhance scalability and flexibility. To this end, we propose MDEForge: an extensible, collaborative modeling platform that provides remote model management facilities and prevents the user from focussing on time-consuming, and less creative procedures. This demo paper illustrates the extensibility of MDEForge by integrating ATL services for the remote execution, automated testing, and static analysis of ATL transformations. The usefulness of their employment under the SaaS paradigm is demonstrated with a case-study showing a wide range of new application possibilities.Work supported by the Spanish MINECO (TIN2014-52129-R), the Madrid Region (S2013/ICE-3006), and the EU commission (#611125

P ORTOLAN: a Model-Driven Cartography Framework

Processing large amounts of data to extract useful information is an essential task within companies. To help in this task, visualization techniques have been commonly used due to their capacity to present data in synthesized views, easier to understand and manage. However, achieving the right visualization display for a data set is a complex cartography process that involves several transformation steps to adapt the (domain) data to the (visualization) data format expected by visualization tools. To maximize the benefits of visualization we propose Portolan, a generic model-driven cartography framework that facilitates the discovery of the data to visualize, the specification of view definitions for that data and the transformations to bridge the gap with the visualization tools. Our approach has been implemented on top of the Eclipse EMF modeling framework and validated on three different use cases

Knowledge Reuse for Customization: Metamodels in an Open Design Community for 3d Printing

Theories of knowledge reuse posit two distinct processes: reuse for replication and reuse for innovation. We identify another distinct process, reuse for customization. Reuse for customization is a process in which designers manipulate the parameters of metamodels to produce models that fulfill their personal needs. We test hypotheses about reuse for customization in Thingiverse, a community of designers that shares files for three-dimensional printing. 3D metamodels are reused more often than the 3D models they generate. The reuse of metamodels is amplified when the metamodels are created by designers with greater community experience. Metamodels make the community's design knowledge available for reuse for customization-or further extension of the metamodels, a kind of reuse for innovation

Applying the business process and practice alignment meta-model: Daily practices and process modelling

Background: Business Process Modelling (BPM) is one of the most important phases of information system design. Business Process (BP) meta-models allow capturing informational and behavioural aspects of business processes. Unfortunately, standard BP meta-modelling approaches focus just on process description, providing different BP models. It is not possible to compare and identify related daily practices in order to improve BP models. This lack of information implies that further research in BP meta-models is needed to reflect the evolution/change in BP. Considering this limitation, this paper introduces a new BP meta-model designed by Business Process and Practice Alignment Meta-model (BPPAMeta-model). Our intention is to present a meta-model that addresses features related to the alignment between daily work practices and BP descriptions. Objectives: This paper intends to present a meta-model which is going to integrate daily work information into coherent and sound process definitions. Methods/Approach: The methodology employed in the research follows a design-science approach. Results: The results of the case study are related to the application of the proposed meta-model to align the specification of a BP model with work practices models. Conclusions: This meta-model can be used within the BPPAM methodology to specify or improve business processes models based on work practice descriptions

Ontology Summit 2008 Communiqué: Towards an open ontology repository

Each annual Ontology Summit initiative makes a statement appropriate to each Summits theme as part of our general advocacy designed to bring ontology science and engineering into the mainstream. The theme this year is "Towards an Open Ontology Repository". This communiqué represents the joint position of those who were engaged in the year's summit discourse on an Open Ontology Repository (OOR) and of those who endorse below. In this discussion, we have agreed that an "ontology repository is a facility where ontologies and related information artifacts can be stored, retrieved and managed." We believe in the promise of semantic technologies based on logic, databases and the Semantic Web, a Web of exposed data and of interpretations of that data (i.e., of semantics), using common standards. Such technologies enable distinguishable, computable, reusable, and sharable meaning of Web and other artifacts, including data, documents, and services. We also believe that making that vision a reality requires additional supporting resources and these resources should be open, extensible, and provide common services over the ontologies