9,817 research outputs found
Generic unified modelling process for developing semantically rich, dynamic and temporal models
Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a modelâs quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models
Designing Reusable Systems that Can Handle Change - Description-Driven Systems : Revisiting Object-Oriented Principles
In the age of the Cloud and so-called Big Data systems must be increasingly
flexible, reconfigurable and adaptable to change in addition to being developed
rapidly. As a consequence, designing systems to cater for evolution is becoming
critical to their success. To be able to cope with change, systems must have
the capability of reuse and the ability to adapt as and when necessary to
changes in requirements. Allowing systems to be self-describing is one way to
facilitate this. To address the issues of reuse in designing evolvable systems,
this paper proposes a so-called description-driven approach to systems design.
This approach enables new versions of data structures and processes to be
created alongside the old, thereby providing a history of changes to the
underlying data models and enabling the capture of provenance data. The
efficacy of the description-driven approach is exemplified by the CRISTAL
project. CRISTAL is based on description-driven design principles; it uses
versions of stored descriptions to define various versions of data which can be
stored in diverse forms. This paper discusses the need for capturing holistic
system description when modelling large-scale distributed systems.Comment: 8 pages, 1 figure and 1 table. Accepted by the 9th Int Conf on the
Evaluation of Novel Approaches to Software Engineering (ENASE'14). Lisbon,
Portugal. April 201
A bibliographic metadata infrastructure for the twenty-first century
The current library bibliographic infrastructure was constructed in the early days of computers â before the Web, XML, and a variety of other technological advances that now offer new opportunities. General requirements of a modern metadata infrastructure for libraries are identified, including such qualities as versatility, extensibility, granularity, and openness. A new kind of metadata infrastructure is then proposed that exhibits at least some of those qualities. Some key challenges that must be overcome to implement a change of this magnitude are identified
CaosDB - Research Data Management for Complex, Changing, and Automated Research Workflows
Here we present CaosDB, a Research Data Management System (RDMS) designed to
ensure seamless integration of inhomogeneous data sources and repositories of
legacy data. Its primary purpose is the management of data from biomedical
sciences, both from simulations and experiments during the complete research
data lifecycle. An RDMS for this domain faces particular challenges: Research
data arise in huge amounts, from a wide variety of sources, and traverse a
highly branched path of further processing. To be accepted by its users, an
RDMS must be built around workflows of the scientists and practices and thus
support changes in workflow and data structure. Nevertheless it should
encourage and support the development and observation of standards and
furthermore facilitate the automation of data acquisition and processing with
specialized software. The storage data model of an RDMS must reflect these
complexities with appropriate semantics and ontologies while offering simple
methods for finding, retrieving, and understanding relevant data. We show how
CaosDB responds to these challenges and give an overview of the CaosDB Server,
its data model and its easy-to-learn CaosDB Query Language. We briefly discuss
the status of the implementation, how we currently use CaosDB, and how we plan
to use and extend it
Identifying and improving reusability based on coupling patterns
Open Source Software (OSS) communities have not yet taken full advantage of reuse mechanisms. Typically many OSS projects which share the same application domain and topic, duplicate effort and code, without fully leveraging the vast amounts of available code.
This study proposes the empirical evaluation of source code folders of OSS projects in order to determine their actual internal reuse and their potential as shareable, fine-grained and externally reusable software components by future projects.
This paper empirically analyzes four OSS systems, identifies which components (in the form of folders) are currently being reused internally and studies their coupling characteristics. Stable components (i.e., those which act as service providers rather than service consumers) are shown to be more likely to be reusable. As a means of supporting replication of these successful instances of OSS reuse, source folders with similar patterns are extracted from the studied systems, and identified as externally reusable components
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