WASOS: An Ontology for Modelling Traditional Knowledge of Sustainable Water Stewardship

Recent work and publications concerning sustainable water stewardship in Rajasthan (India) highlight how contemporary challenges are eroding traditional, communal approaches to water stewardship through mechanised extraction beyond the renewable capacities of ecosystems. Our work is focused on developing a formal ontology for modelling the knowledge of traditional water stewardship in India’s drylands by capturing the key constitutional elements of regenerative methods. Our method follows an iterative evolving prototype process for delivering the first version of the Ontology for Sustainable Water Stewardship (WASOS). The ontology contains a moderate number of high-level classes and properties that represent the water management decisionmaking process. By making key relationships visible, we aim to support decision-making in complex catchments particularly where there are contested urban and rural claims on water

A process pattern model for tackling and improving big data quality

Data seldom create value by themselves. They need to be linked and combined from multiple sources, which can often come with variable data quality. The task of improving data quality is a recurring challenge. In this paper, we use a case study of a large telecom company to develop a generic process pattern model for improving data quality. The process pattern model is defined as a proven series of activities, aimed at improving the data quality given a certain context, a particular objective, and a specific set of initial conditions. Four different patterns are derived to deal with the variations in data quality of datasets. Instead of having to find the way to improve the quality of big data for each situation, the process model provides data users with generic patterns, which can be used as a reference model to improve big data quality

TOLKIN – Tree of Life Knowledge and Information Network: Filling a Gap for Collaborative Research in Biological Systematics

The development of biological informatics infrastructure capable of supporting growing data management and analysis environments is an increasing need within the systematics biology community. Although significant progress has been made in recent years on developing new algorithms and tools for analyzing and visualizing large phylogenetic data and trees, implementation of these resources is often carried out by bioinformatics experts, using one-off scripts. Therefore, a gap exists in providing data management support for a large set of non-technical users. The TOLKIN project (Tree of Life Knowledge and Information Network) addresses this need by supporting capabilities to manage, integrate, and provide public access to molecular, morphological, and biocollections data and research outcomes through a collaborative, web application. This data management framework allows aggregation and import of sequences, underlying documentation about their source, including vouchers, tissues, and DNA extraction. It combines features of LIMS and workflow environments by supporting management at the level of individual observations, sequences, and specimens, as well as assembly and versioning of data sets used in phylogenetic inference. As a web application, the system provides multi-user support that obviates current practices of sharing data sets as files or spreadsheets via email

Case Study: LifeWatch Italy Phytoplankton VRE

LifeWatch Italy, the Italian node of LifeWatch ERIC, has promoted and stimulated the debate on the use of semantics in biodiversity data management. Actually, biodiversity and ecosystems data are very heterogeneous and need to be better managed to improve the actual scientific knowledge extracted, as well as to address the urgent societal challenges concerning environmental issues. LifeWatch Italy has realized the Phytoplankton Virtual Research Environment (hereafter Phytoplankton VRE), a collaborative working environment supporting researchers to address basic and applied studies on phytoplankton ecology. The Phytoplankton VRE provides the IT infrastructure to enable researchers to obtain, share and analyse phytoplankton data at a level of resolution from individual cells to whole assemblages. A semantic approach has been used to address data harmonisation, integration and discovery: an interdisciplinary team has developed a thesaurus on phytoplankton functional traits and linked its concepts to other existing conceptual schemas related to the specific domain

Early changes in Orthopteran assemblages after grassland restoration : a comparison of space-for-time substitution versus repeated-measures monitoring

Grasslands harbour significant biodiversity and their restoration is a common intervention in biodiversity conservation. However, we know very little on how grassland restoration influences arthropod groups. Here we compared orthopteran assemblages in croplands, natural grasslands and one to four-year-old grasslands restored in a large-scale restoration on former croplands in Hortobágy National Park (E-Hungary). Sampling was done by standardized sweep-netting both in a repeated measures design and space-for-time substitution (chronosequence) design. General linear models with repeated measures from five years showed that species richness, abundance and Shannon diversity of orthopterans decreased in the year following restoration but increased afterwards. By the fourth year, species richness almost doubled and abundance increased almost ten-fold in restored grasslands compared to croplands. Multivariate analyses showed that species composition in the first two years did not progress much but by the third and fourth year there was partial overlap with natural grasslands. Local restoration conditions (last crop, seed mixture) and landscape configuration (proportion of natural grasslands < 1 km away) did not influence the above patterns in either the repeated measures or the chronosequence design, whereas time since restoration affected almost all community variables. Our results suggest that generalist ubiquitous species appeared in restored grasslands first and the more sensitive species colonized the restored fields gradually in later years. The qualitative and quantitative properties of the orthopteran assemblages in restored fields did not yet reach those of natural grasslands, therefore, our study suggests that the full regeneration of the orthopteran assemblages takes more than four years

Perspectives on Disconnects Between Scientific Information and Management Decisions on Post-fire Recovery in Western US

Environmental regulations frequently mandate the use of "best available" science, but ensuring that it is used in decisions around the use and protection of natural resources is often challenging. In the Western US, this relationship between science and management is at the forefront of post-fire land management decisions. Recent fires, post-fire threats (e.g. flooding, erosion), and the role of fire in ecosystem health combine to make post-fire management highly visible and often controversial. This paper uses post-fire management to present a framework for understanding why disconnects between science and management decisions may occur. We argue that attributes of agencies, such as their political or financial incentives, can limit how effectively science is incorporated into decision-making. At the other end of the spectrum, the lack of synthesis or limited data in science can result in disconnects between science-based analysis of post-fire effects and agency policy and decisions. Disconnects also occur because of the interaction between the attributes of agencies and the attributes of science, such as their different spatial and temporal scales of interest. After offering examples of these disconnects in post-fire treatment, the paper concludes with recommendations to reduce disconnects by improving monitoring, increasing synthesis of scientific findings, and directing social-science research toward identifying and deepening understanding of these disconnects