Data competence maturity: developing data-driven decision making

Purpose - The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education. Design/methodology/approach - Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to secondary education. Findings - The conceptual model reveals significant opportunities to improve data-driven decision making in schools and local education agencies (LEAs). Moving past the first and second stages of the data competency maturity model should allow educators to better incorporate data into the regular decision-making process. Practical implications - Moving up the DCMM to better integrate data into their decision-making process has the potential to produce profound improvements for schools and LEAs. Data science is about making better decisions. Understanding the path laid out in the DCMM to helping an organization move to a more mature data-driven decision-making process will help improve both student and operational outcomes. Originality/value - This paper brings a new concept, the DCMM, to the educational literature and discusses how these principles can be applied to improve decision making by integrating them into their decision-making process and trying to help the organization mature within this framework

Are Online Auction Markets Efficient? An Empirical Study of Market Liquidity and Abnormal Returns.

Under dynamic loading the stabilising effect of increased strain rate sensitivity of the material restrains neck formation in tension tests and leads to an increase in ductility. On the other hand the adiabatic character of the deformation process reduces the flow stress and promotes instability, localisation and adiabatic shear band initiation. Furthermore, the notch sensitivity of the material increases with increasing strain rate. Dynamic and quasi-static tension and compression tests were carried out on the age hardenable aluminium wrought alloy AA7075. There, dispers distributed precipitations are often the starting point for ductile fracture caused by impact due to the nucleation, growth and coalescence of voids and micro-cracks in case of tension. Neck formation under tensile loading and instabilities like shear bands in case of compression are discussed on the basis of the theory of imperfections under consideration of the increased strain rate sensitivity of the material and the adiabatic character of the deformation process at high strain rates. In case of tensile loading, tests with various notched geometries allowed the study of the influence of degree of multiaxiality. Through combination of experiment and simulation, the influence of strain rate on the local fracture strain could be determined for tensile and compression loading

Event sequence modeling of IT adoption in healthcare

ABSTRACT Information systems research is replete with examples of the importance of business processes defining IT adoption. Business processes are influenced by both organizational and operational concerns. We evaluate the comparative importance of operational and organizational influences for complementary IT systems. In the context of acute-care hospitals the analysis shows that an organizational approach to automating a process is related to different financial outcomes than an operational approach. Six complementary systems supporting a three-stage medication management process are studied: prescribing, dispensing, and administration. The analysis uses firm-level, panel data extracted from the HIMSS Analytics database spanning ten years of IT adoption for 140 hospitals. We have augmented the HIMSS dataset with matching demographic and financial details from the American Hospital Association and the Centers for Medicare and Medicaid Services. Using event sequence analysis we explore whether organizations are more likely to adopt organization boundary spanning systems and if the sequence of adoption follows the temporal ordering of the business process steps. The research also investigates if there is a relationship between the paths to IT adoption and financial performance. Comparison of the two measures suggests that the organizational model of adoption is observed more often in the data. Following the organizational model of adoption is associated with approximately $155 dollar increase in net income per patient day; whereas the operational model of adoption is associated with approximately$225 dollars decrease in net income per patient day. However, this effect diminishes with the adoption of each additional system thus demonstrating that the adoption path effects may only be relevant in the shortterm

Proteogenomic analyses indicate bacterial methylotrophy and archaeal heterotrophy are prevalent below the grass root zone.

Annually, half of all plant-derived carbon is added to soil where it is microbially respired to CO2. However, understanding of the microbiology of this process is limited because most culture-independent methods cannot link metabolic processes to the organisms present, and this link to causative agents is necessary to predict the results of perturbations on the system. We collected soil samples at two sub-root depths (10-20 cm and 30-40 cm) before and after a rainfall-driven nutrient perturbation event in a Northern California grassland that experiences a Mediterranean climate. From ten samples, we reconstructed 198 metagenome-assembled genomes that represent all major phylotypes. We also quantified 6,835 proteins and 175 metabolites and showed that after the rain event the concentrations of many sugars and amino acids approach zero at the base of the soil profile. Unexpectedly, the genomes of novel members of the Gemmatimonadetes and Candidate Phylum Rokubacteria phyla encode pathways for methylotrophy. We infer that these abundant organisms contribute substantially to carbon turnover in the soil, given that methylotrophy proteins were among the most abundant proteins in the proteome. Previously undescribed Bathyarchaeota and Thermoplasmatales archaea are abundant in deeper soil horizons and are inferred to contribute appreciably to aromatic amino acid degradation. Many of the other bacteria appear to breakdown other components of plant biomass, as evidenced by the prevalence of various sugar and amino acid transporters and corresponding hydrolyzing machinery in the proteome. Overall, our work provides organism-resolved insight into the spatial distribution of bacteria and archaea whose activities combine to degrade plant-derived organics, limiting the transport of methanol, amino acids and sugars into underlying weathered rock. The new insights into the soil carbon cycle during an intense period of carbon turnover, including biogeochemical roles to previously little known soil microbes, were made possible via the combination of metagenomics, proteomics, and metabolomics