Next Generation Evaluation: Embracing Complexity, Connectivity, and Change

This Learning Brief draws from literature and research, as well as more than a dozen interviews with foundation leaders, evaluation practitioners, and social sector thought leaders, with the intention of starting the conversation in the field around Next Generation Evaluation characteristics and approaches

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

Cognition, Incentives, and Public Governance:Laboratory Federalism from the Organizational Viewpoint

The Second Generation Theory (SGT) of fiscal federalism, which draws upon contemporary economic and industrial organization theory, hitherto focuses only on the negative benefits of public decentralization: the potentially superior ability to align perverse incentives vis-à-vis the centralized governance alternative. The SGT neglects the positive benefits of decentralization (mistake-ridden learning, flexibility, and option discovery), although the limitations of organization theory do not justify such neglect. By likening intergovernmental grants to incomplete contracts, this work shows that the SGT can include the laboratory nature of decentralization.Experimentation, incomplete contracts, intergovernmental grants, learning, Second Generation Theory of fiscal federalism.

Channeling Change: Making Collective Impact Work

Large-scale social change requires broad cross-sector coordination, yet the social sector remains focused on the isolated intervention of individual organizations. Substantially greater progress could be made in alleviating many of our most serious and complex social problems if nonprofits, governments, businesses, and the public were brought together around a common agenda to create collective impact. Published in the Stanford Social Innovation Review, Winter 2011

Statistical analysis of the owl:sameAs network for aligning concepts in the linking open data cloud

The massively distributed publication of linked data has brought to the attention of scientific community the limitations of classic methods for achieving data integration and the opportunities of pushing the boundaries of the field by experimenting this collective enterprise that is the linking open data cloud. While reusing existing ontologies is the choice of preference, the exploitation of ontology alignments still is a required step for easing the burden of integrating heterogeneous data sets. Alignments, even between the most used vocabularies, is still poorly supported in systems nowadays whereas links between instances are the most widely used means for bridging the gap between different data sets. We provide in this paper an account of our statistical and qualitative analysis of the network of instance level equivalences in the Linking Open Data Cloud (i.e. the sameAs network) in order to automatically compute alignments at the conceptual level. Moreover, we explore the effect of ontological information when adopting classical Jaccard methods to the ontology alignment task. Automating such task will allow in fact to achieve a clearer conceptual description of the data at the cloud level, while improving the level of integration between datasets. <br/

Net Gains: A Handbook for Network Builders Seeking Social Change

This handbook provides the growing number of people who are developing networks for social change with practical advice based on the experiences of network builders, case studies of networks small and large, local and international, and emerging scientific knowledge about "connectivity." It is intended to join, complement, and spur other efforts to capture and make widely available what is being learned in the business, government, and civil sectors about why and how to use networks, rather than solitary organizations, to generate large-scale impact

A value chain and cluster perspective on competitiveness of European fresh vegetable production – Case studies from Germany, Italy, and Spain

In the present study we combine cluster theory with a value chain approach, with the aim of discovering elements of the European fresh vegetable business that could enable local producers to gain competitive advantages in a global market. European producers of fresh vegetables are under pressure to improve their performance and increase their competitiveness. Competitive advantage can be gained through innovation and by using unique resources stemming from cooperation between producers and complementary actors in local clusters. However, locally clustered producers do not sell to open markets but need access to value chains governed by lead firms, the large European retail chains, which set the rules and conditions of participation. The study presents first results from a multiple case-study analysis involving three different European regions in Germany, Italy and Spain specialized in fresh vegetable production. In-depth interviews with practitioners allowed us to confirm some main trends in business organization in the European fresh vegetable industry, but also to point out some interesting peculiarities of this industry. Local fresh vegetable producers become competitive due to their integration both in local production and wider marketing networks, where unique knowledge is created and interchanged by personal relationships. Further concentration on the local level is claimed to countervail power imbalances that usually favor buyers. The need for leading supermarket chains to build up direct relationships with key suppliers disturbs the functioning of existing relationship patterns in the local cluster. Creation of exclusive relationships with retail chains is pursued by entrepreneurs of innovative producing farms who treat their special knowledge and capacities as competitive advantages in the sharp competition in world markets and do not share it with other cluster actors.Fresh vegetables, value chains, clusters, competitiveness

Data-Driven Shape Analysis and Processing

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis, through reviewing the literature and relating the existing works with both qualitative and numerical comparisons. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.Comment: 10 pages, 19 figure