Dissolving views, memory and sensory experience: The Cosmopoligraphicon or the ‘World in Many Pictures’ in Melbourne, Australia, in 1855

While magic lanterns and dissolving views were a global phenomenon in the nineteenth century, scholars are only starting to examine in depth their social dimensions. This article seeks to extend our understanding of dissolving views by analysing the audience sensory experience in a specific historical context – gold rush Melbourne in 1855. It argues that while a Melbourne audience admired the technological wonder of the magic lantern and the dissolving views, their sensory experience was informed by the colonial social context. The audiences appear to have delighted in immersing themselves in the dissolving views, both learning about the world and reacquainting themselves with parts of the (old) world they had left behind. This article further argues that dissolving views were more than a visual spectacle: they actively engaged the senses in ways that gave emotional meanings to the dissolving views and linked a Melbourne gold rush audience with the world left behind, yet still accessible remotely through memory and sensory imagination.

Data quality management in a business intelligence environment : from the lens of metadata

Business Intelligence is becoming more pervasive in many large and medium-sized organisations. Being a long term undertaking Business Intelligence raises many issues that an organisation has to deal with in order to improve its decision making processes. Data quality is one of the main issues exposed by Business Intelligence. Within the organisation data quality can affect attitudes to Business Intelligence itself, especially from the business users group. Comprehensive management of data quality is a crucial part of any Business Intelligence endeavour. It is important to address all types of data quality issues and come up with an all-in-one solution. We believe that extensive metadata infrastructure is the primary technical solution for management of data quality in Business Intelligence. Moreover, metadata has a more broad application for improving the Business Intelligence environment. Upon identifying the sources of data quality issues in Business Intelligence we propose a concept of data quality management by means of metadata framework and discuss the recommended solution.

The many roads to mitochondrial dysfunction in neuroimmune and neuropsychiatric disorders

BACKGROUND: Mitochondrial dysfunction and defects in oxidative metabolism are a characteristic feature of many chronic illnesses not currently classified as mitochondrial diseases. Examples of such illnesses include bipolar disorder, multiple sclerosis, Parkinson's disease, schizophrenia, depression, autism, and chronic fatigue syndrome. DISCUSSION: While the majority of patients with multiple sclerosis appear to have widespread mitochondrial dysfunction and impaired ATP production, the findings in patients diagnosed with Parkinson's disease, autism, depression, bipolar disorder schizophrenia and chronic fatigue syndrome are less consistent, likely reflecting the fact that these diagnoses do not represent a disease with a unitary pathogenesis and pathophysiology. However, investigations have revealed the presence of chronic oxidative stress to be an almost invariant finding in study cohorts of patients afforded each diagnosis. This state is characterized by elevated reactive oxygen and nitrogen species and/or reduced levels of glutathione, and goes hand in hand with chronic systemic inflammation with elevated levels of pro-inflammatory cytokines. SUMMARY: This paper details mechanisms by which elevated levels of reactive oxygen and nitrogen species together with elevated pro-inflammatory cytokines could conspire to pave a major road to the development of mitochondrial dysfunction and impaired oxidative metabolism seen in many patients diagnosed with these disorders.

Data management challenges in analysis and synthesis in the ecosystem sciences

Open-data has created an unprecedented opportunity with new challenges for ecosystem scientists. Skills in data management are essential to acquire, manage, publish, access and re-use data. These skills span many disciplines and require trans-disciplinary collaboration. Science synthesis centres support analysis and synthesis through collaborative 'Working Groups' where domain specialists work together to synthesise existing information to provide insight into critical problems. The Australian Centre for Ecological Analysis and Synthesis (ACEAS) served a wide range of stakeholders, from scientists to policy-makers to managers. This paper investigates the level of sophistication in data management in the ecosystem science community through the lens of the ACEAS experience, and identifies the important factors required to enable us to benefit from this new data-world and produce innovative science. ACEAS promoted the analysis and synthesis of data to solve transdisciplinary questions, and promoted the publication of the synthesised data. To do so, it provided support in many of the key skillsets required. Analysis and synthesis in multi-disciplinary and multi-organisational teams, and publishing data were new for most. Data were difficult to discover and access, and to make ready for analysis, largely due to lack of metadata. Data use and publication were hampered by concerns about data ownership and a desire for data citation. A web portal was created to visualise geospatial datasets to maximise data interpretation. By the end of the experience there was a significant increase in appreciation of the importance of a Data Management Plan. It is extremely doubtful that the work would have occurred or data delivered without the support of the Synthesis centre, as few of the participants had the necessary networks or skills. It is argued that participation in the Centre provided an important learning opportunity, and has resulted in improved knowledge and understanding of good data management practices.