Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects

Background Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, metadata formats from a data provider are often incompatible with requirements of a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software. Results To address this, we present the Portable Encapsulated Project (PEP) specification, a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many biological samples. In addition to standardization, the PEP specification provides descriptors and modifiers for project-level and sample-level metadata, which improve portability across both computing environments and data processing tools. PEPs include a schema validator framework, allowing formal definition of required metadata attributes for data analysis broadly. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. Conclusions The PEP specification is an important step toward unifying data annotation and processing tools in data-intensive biological research projects. Links to tools and documentation are available at http://pep.databio.org/.

Procurement Risk Framework: Guidance Note on Procurement

This guidance note describes ADB’s procurement risk framework for managing procurement risk throughout the procurement cycle. Effective risk management minimizes impacts on project objectives from adverse events. The guidance note describes how risks are identified, assessed, and managed at the country and sector/agency levels, and how those risks are used as inputs into the identification, assessment, and management of risk at the project level during procurement planning and through contract implementation.

Leveraging multifaceted proximity measures among developers in predicting future collaborations to improve the social capital of software projects

Social capital is an asset earned by people through their social connections. One of the motivations among developers to contribute to open source development and maintenance tasks is to earn social capital. Recent studies suggest that the social capital of the project has an impact on the sustained participation of the developers in open source software (OSS). One way to improve the social capital of the project is to help the developers in connecting with their peers. However, to the best of our knowledge, there is no prior research which attempts to predict future collaborations among developers and establish the significance of these collaborations on improving the social capital at the project level. To address this research gap, in this paper, we model the past collaborations among developers on version control system (VCS) and issue tracking system (ITS) as homogeneous and heterogeneous developer social network (DSN). Along with the novel path count based features, defined on proposed heterogeneous DSN, multifaceted proximity features are used to generate a feature set for machine learning classifiers. Our experiments performed on 5 popular open source projects (Spark, Kafka, Flink, WildFly, Hibernate) indicate that the proposed approach can predict the future collaborations among developers on both the platforms i.e. VCS as well as ITS with a significant accuracy (AUROC up to 0.85 and 0.9 for VCS and ITS respectively). A generic metric- recall of gain in social capital is proposed to investigate the efficacy of these predicted collaborations in improving the social capital of the project. We also concretised this metric on various measures of social capital and found that collaborations predicted by our approach have significant potential to improve the social capital at project level (e.g. Recall of gain in cohesion index up to 0.98 and Recall of gain in average godfather index up to 0.99 for VCS). We also showed that structure of collaboration network has an impact on the accuracy and usefulness of predicted collaborations. Since the past research suggests that many newcomers abandon the open source project due to social barriers which they face after joining the project, our research outcomes can be used to build the recommendation systems which might help to retain such developers by improving their social ties based on similar skills/interests.

“Reverse engineering” research portfolio synergies and tradeoffs from domain expertise in minimum data contexts

In research portfolio planning contexts, an estimate of research policy and project synergies/tradeoffs (i.e. covariances) is essential to the optimal leveraging of institution resources. The data by which to make such estimates generally do not exist. Research institutions may often draw on domain expertise to fill this gap, but it is not clear how such ad hoc information can be quantified and fed into an optimal resource allocation workflow. Drawing on principal components analysis, I propose a method for “reverse engineering” synergies/tradeoffs from domain expertise at both the policy and project level. I discuss extensions to other problems and detail how the method can be fed into a research portfolio optimization workflow. I also briefly discuss the relevance of the proposed method in the context of the currently toxic relations between research communities and the donors that fund them.

Urban Agriculture for Poverty Alleviation:A Case Study of Hyderabad, India

<p>Conceptualising sustainable development as that which seeks to achieve holistic well-being means that as a barrier to attaining and sustaining well-being, poverty takes on a similarly more broad definition. Within this framework it is proposed that the breakdown of community; the extinction of experience; degradation of the natural environment; and food insecurity are examples of poverty in the contemporary urban setting because they obstruct access to overall well-being. Through a case study of the Resource Centres for Urban Agriculture and Food Security - Cities Farming for the Future (RUAF-CFF) project being piloted in Surabhi Colony, Hyderabad, India, urban agriculture is assessed as a means of alleviating these diverse forms of poverty. While the findings indicate some success at the project level, urban agriculture's limited ability to address Hyderabad's more widespread and pressing problems - in particular its water scarcity - coupled with the form of development the city is taking means that it is unlikely urban agriculture will gain the institutional support necessary for its further spread throughout the city. Although such findings do not inspire hope for the future use of urban agriculture as a poverty alleviation strategy within Hyderabad, a number of issues are considered which suggest that urban agriculture should rather be supported for its ability to facilitate 'good change' in our urban centres.</p>

Urban Agriculture for Poverty Alleviation:A Case Study of Hyderabad, India

<p>Conceptualising sustainable development as that which seeks to achieve holistic well-being means that as a barrier to attaining and sustaining well-being, poverty takes on a similarly more broad definition. Within this framework it is proposed that the breakdown of community; the extinction of experience; degradation of the natural environment; and food insecurity are examples of poverty in the contemporary urban setting because they obstruct access to overall well-being. Through a case study of the Resource Centres for Urban Agriculture and Food Security - Cities Farming for the Future (RUAF-CFF) project being piloted in Surabhi Colony, Hyderabad, India, urban agriculture is assessed as a means of alleviating these diverse forms of poverty. While the findings indicate some success at the project level, urban agriculture's limited ability to address Hyderabad's more widespread and pressing problems - in particular its water scarcity - coupled with the form of development the city is taking means that it is unlikely urban agriculture will gain the institutional support necessary for its further spread throughout the city. Although such findings do not inspire hope for the future use of urban agriculture as a poverty alleviation strategy within Hyderabad, a number of issues are considered which suggest that urban agriculture should rather be supported for its ability to facilitate 'good change' in our urban centres.</p>

Cost and Efficiency in Government Outsourcing: Evidence from the Dredging Industry

This paper investigates the how government outsourcing affects efficiency and expenditures by considering how outsourcing decisions are determined along two dimensions: (i) cost differences between private firms and government suppliers of public goods and (ii) dynamics arising from cost complementarities and capacity constraints. I formulate and estimate a dynamic model of government outsourcing using project-level data from the dredging industry. Model estimates indicate substantial cost savings due to outsourcing but also that government presence in the market yields cost reduction. A counterfactual policy featuring direct competition between government and private sector firms finds a total expenditure reduction of 15.7 percent. (JEL D44, H41, H57, L84)