Position Paper on Dataset Engineering to Accelerate Science

Data is a critical element in any discovery process. In the last decades, we observed exponential growth in the volume of available data and the technology to manipulate it. However, data is only practical when one can structure it for a well-defined task. For instance, we need a corpus of text broken into sentences to train a natural language machine-learning model. In this work, we will use the token \textit{dataset} to designate a structured set of data built to perform a well-defined task. Moreover, the dataset will be used in most cases as a blueprint of an entity that at any moment can be stored as a table. Specifically, in science, each area has unique forms to organize, gather and handle its datasets. We believe that datasets must be a first-class entity in any knowledge-intensive process, and all workflows should have exceptional attention to datasets' lifecycle, from their gathering to uses and evolution. We advocate that science and engineering discovery processes are extreme instances of the need for such organization on datasets, claiming for new approaches and tooling. Furthermore, these requirements are more evident when the discovery workflow uses artificial intelligence methods to empower the subject-matter expert. In this work, we discuss an approach to bringing datasets as a critical entity in the discovery process in science. We illustrate some concepts using material discovery as a use case. We chose this domain because it leverages many significant problems that can be generalized to other science fields.Comment: Published at 2nd Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE) https://ai-2-ase.github.io/papers/16%5cSubmission%5cAAAI_Dataset_Engineering-8.pd

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed

An Object-Oriented Approach to Extracting Productive Fossil Localities from Remotely Sensed Imagery

2015-2016 UNCG University Libraries Open Access Publishing Fund Grant Winner. Most vertebrate fossils are rare and difficult to find and although paleontologists andpaleoanthropologists use geological maps to identify potential fossil-bearing deposits, theprocess of locating fossiliferous localities often involves a great deal of luck. One way to reducethe role of serendipity is to develop predictive models that increase the likelihood of locatingfossils by identifying combinations of geological, geospatial, and spectral features that arecommon to productive localities. We applied GEographic Object-Based Image Analysis(GEOBIA) of high resolution QuickBird and medium resolution images from the Landsat 8Operational Land Imager (OLI) along with GIS data such as slope and surface geology layers toidentify potentially productive Eocene vertebrate fossil localities in the Great Divide Basin,Wyoming. The spectral and spatial characteristics of the image objects that represent a highlyproductive locality (WMU-VP-222) were used to extract similar image objects in the areacovered by the high resolution imagery and throughout the basin using the Landsat imagery.During the 2013 summer field season, twenty-six locations that would not have been spottedfrom the road in a traditional ground survey were visited. Fourteen of the eighteen localities thatwere fossiliferous were identified by the predictive model. In 2014, the GEOBIA techniqueswere applied to Landsat 8 imagery of the entire basin, correctly identifying six new productivelocalities in a previously unsurveyed part of the basin

Multidimensional computation and visualisation for marine controlled source electromagnetic methods

The controlled source electromagnetic method is improving the search for oil and gas in marine settings and is becoming an integral component of many exploration toolkits. While the level of detail and benefit obtained from recorded electromagnetic data sets is limited to the tools available, interpretation is fundamentally restricted by non-unique and equivalent solutions. I create the tools necessary to rapidly compute and visualise multi-dimensional electromagnetic fields generated for a variety of controlled source electromagnetic surveys. This thesis is divided into two parts: the creation of an electromagnetic software framework and the electromagnetic research applications.The creation of a new electromagnetic software framework is covered in Part I. Steps to create and test a modern electromagnetic data structure, three-dimensional visualisation and interactive graphical user interface from the ground up are presented. Bringing together several computer science disciplines ranging from parallel computing, networking and computer human interaction to three-dimensional visualisation, a package specifically tailored to marine controlled source electromagnetic compuation is formed. The electromagnetic framework is comprised of approximately 100,000 lines of new Java code and several third party libraries, which provides low-level graphical, network and execution cross-platform functionality. The software provides a generic framework to integrate most computational engines and algorithms into the coherent global electromagnetic package enabling the interactive forward modelling, inversion and visualisation of electromagnetic data.Part II is comprised of several research applications utilising the developed electromagnetic software framework. Cloud computing and streamline visualisation are covered. These topics are covered to solve several problems in modern controlled source electromagnetic methods. Large 3D electromagnetic modelling and inversion may require days or even weeks to be performed on a single-threaded personal computers. A massively parallelised electromagnetic forward modelling and inversion methods can dramatically was created to improve computational time. The developed ’macro’ parallelisation method facilitated the reduction in computational time by several orders of magnitude with relatively little additional effort and without modification of the internal electromagnetic algorithm. The air wave is a significant component of marine controlled source electromagnetic surveys however there is controversy and confusion over its defintion. The airwave has been described as a reflected, refracted, direct or diffusing wave, which has lead to confusion over its physical reality

Application Of Coastal And Marine Ecological Classification Standard (Cmecs) To Remotely Operated Vehicle (Rov) Video Data For Enhanced Geospatial Analysis Of Deep Sea Environments

The Coastal and Marine Ecological Classification Standard (CMECS) provides a comprehensive framework of common terminology for organizing physical, chemical, biological, and geological information about marine ecosystems. Federally endorsed as a dynamic content standard, all federally funded data must be compliant by 2018; however, applying CMECS to deep sea datasets and underwater video have not been extensively examined. The presented research demonstrates the extent to which CMECS can be applied to deep sea benthic habitats, assesses the feasibility of applying CMECS to remotely operated vehicle (ROV) video data in near-real-time, and establishes best practices for mapping environmental aspects and observed deep sea habitats as viewed by the ROV’s forwardacing camera. All data were collected during 2014 in the Northern Gulf of Mexico by the National Oceanic and Atmospheric Administration’s (NOAA) ROV Deep Discoverer and ship Okeanos Explorer

Internationalization of Água das Pedras to Tokyo (Japan)

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and EconomicsÁgua das Pedras is a natural carbonated mineral water exploited and sold by Unicer S.A, a 44% Danish and 56% Portuguese company, the largest beverage company in Portugal1. The market for bottled water in Portugal has been stabilizing in the past years due to its maturity character. At the same time, the expansion of off-trade distribution channels such as supermarkets and large distribution chains associated with the original limited demand for premium waters have been making the market for sparkling water decrease in value. At the moment, exports in Unicer represent 30% of sales and the company had therefore it had decided to focus its internationalization efforts in the beer and water sectors. The most recent internationalization project designed for the brand was its placement in selected cities in Brazil and the US market, under the ‘Projecto Mil Milhões’, aimed at increasing Água das Pedras profit through market expansion. As an alternative to diversify its markets, Tokyo appears as a challenging opportunity that may open a door to the Asian market through Japan. Japan has an interesting dynamics on bottled water and premium beverages, and it is extremely dependent on agri-food imports to maintain the food supply for its population. This WP will clarify Unicer as a consulting report

Digital twin challenges and opportunities for nuclear fuel manufacturing applications

There have been a number of digital twin (DT) frameworks proposed for multiple disciplines in recent years. However, there is a need to develop systematic methodologies to improve our ability to produce DT solutions for the nuclear fuel industry considering specific requirements and conditions exclusive to the nuclear fuel manufacturing cycle. A methodology tailored for nuclear fuel production is presented in this paper. Due to the nature of the chemical processes involved in fuel manufacturing, we highlight the importance of using a combination of physics-based and data-driven modelling. We introduce key technologies for DT construction and the technical challenges for DT are discussed. Furthermore, we depict typical application scenarios, such as key stages of the nuclear manufacturing cycle. Finally, a number of technology issues and research questions related to DT and nuclear fuel manufacturing are identified