Acspype: An Open-Source Python Package for ac-s Data Acquisition and Processing

<p>Modern scientific research requires open and efficient access to well-documented data to ensure transparency and reproducibility, and to build on existing resources to solve scientific questions of the future. Open access to the results of scientific research - publications, data, samples, code - is now broadly advocated and implemented in policies of funding agencies and publishers because it helps build trust in science, galvanizes the scientific enterprise, and accelerates the pace of discovery and creation of new knowledge. Domain specific data facilities offer specialized services for data curation that are tailored to the needs of scientists in a given domain, ensuring rich, relevant, and consistent metadata for meaningful discovery and reuse of data, as well as data formats and encodings that facilitate data access, data integration, and data analysis for disciplinary and interdisciplinary applications. Domain specific data facilities are uniquely poised to implement best practices that ensure not only the Findability and Accessibility of data under their stewardship, but also their Interoperability and Reusability, which requires detailed data type specific documentation of methods, including data acquisition and processing steps, uncertainties, and other data quality measures. </p><p>The dilemma for domain repositories is that the rigorous implementation of such Best Practices requires substantial effort and expertise, which becomes a challenge when usage of the repository outgrows its resources. Rigorous implementation of Best Practices can also cause frustration of users, who are asked to revise and improve their data submissions, and may make them deposit their data in other, often general repositories that do not perform such rigorous review and therefore minimize the burden of data deposition. </p><p>We will report on recent experiences of EarthChem, a domain specific data facility for the geochemical and petrological science community. EarthChem is recommended by publishers as a trusted repository for the preservation and open sharing of geochemical data. With the implementation of the FAIR Data principles at multiple journals that publish geochemical and petrological research over the past year, the number, volume, and diversity of data submitted to the EarthChem Library has grown dramatically and is challenging existing procedures and resources that do not scale to the new level of usage. Curators are challenged to meet expectations of users for immediate data publication and DOI assignment, and to process submissions that include new data types, are poorly documented, or contain code, images, and other digital content that is outside the scope of the repository. We will discuss possible solutions ranging from tiered data curation support, collaboration with other data repositories, and engagement with publishers and editors to enhance guidance and education of authors.</p><p> </p><p> </p>

Genetic data are being generated at unprecedented rates. Policies of many journals, institutions and funding bodies aim to ensure that these data are publicly archived so that published results are reproducible. Additionally, publicly archived data can be 'repurposed' to address new questions in the future. In 2011, along with other leading journals in ecology and evolution, Molecular Ecology implemented mandatory public data archiving (the Joint Data Archiving Policy). To evaluate the effect of this policy, we assessed the genetic, spatial and temporal data archived for 419 data sets from 289 articles in Molecular Ecology from 2009 to 2013. We then determined whether archived data could be used to reproduce analyses as presented in the manuscript. We found that the journal's mandatory archiving policy has had a substantial positive impact, increasing genetic data archiving from 49 (pre-2011) to 98% (2011-present). However, 31% of publicly archived genetic data sets could not be recreated based on information supplied in either the manuscript or public archives, with incomplete data or inconsistent codes linking genetic data and metadata as the primary reasons. While the majority of articles did provide some geographic information, 40% did not provide this information as geographic coordinates. Furthermore, a large proportion of articles did not contain any information regarding date of sampling (40%). Although the inclusion of spatio-temporal data does require an increase in effort, we argue that the enduring value of publicly accessible genetic data to the molecular ecology field is greatly compromised when such metadata are not archived alongside genetic data.

Friedman and colleagues1 outline a vision of the learning health system founded on the sharing of data and achieved through alignment of information technology, advanced analytics and clinical expertise. The...

Building a data warehouse for infection control

Sharing and re-use of data are essential to the progressive and self-correcting nature of science. In recognition of this principle, journals and funding agencies have adopted policies to encourage sharing of information ('data'), including empirical data as well as computed inferences such as phylogenetic trees.Here we summarize an ongoing analysis of 1) current practices for sharing phylogenetic trees and associated data; 2) current barriers to effective sharing and reuse of such data; and 3) prospects for reducing these barriers to promote more widespread sharing and re-use. Currently, the technical infrastructure is available to support (with some limitations) rudimentary archiving in conjunction with manuscript publication. Yet, most published trees are not archived, and there is no community standard governing the recommended format or content to ensure a re-usable phylogenetic record. Without a shift in emphasis toward re-usability, along with technology and standards to support such a shift, the value of trees (whether disseminated via public archives, or by other means) will be limited. Interviews with actual or potential secondary consumers of phylogenetic results suggest that there is a considerable market for re-use, but that most attempts end in disappointment. Phylogenetic results available via author requests, journal web sites, archival repositories and project web sites rarely include the critical information that secondary consumers seek, such as unique identifiers for biological sources (including species sources and accession numbers), indicators of quality, and documentation of the analytical methods used to obtain the results.Based on the analysis presented here, we suggest that enabling effective re-use entails a commitment by the research community to several changes from current practice: 1) using globally unique identifiers (GUIDs) to reference informational and material entities; 2) developing and using technology for documenting and exchanging the metadata that facilitate re-use; and 3) supporting development and use of a minimal reporting standard that indicates what data and metadata are considered essential for a re-useable phylogenetic record. We suggest that re-use may be catalyzed most rapidly by identifying and targeting (with appropriate technology) the most promising circumstances for re-use. These might include the extraction of sub-trees from large trees (for use in reconciliation, classification, and comparative analysis); the re-use of seed alignments, sub-alignments and homologized characters; the linking of phylogenies to geographic information (for use in ecology, phylogeography and biogeography); and the construction of supertrees and supermatrices.

This article examines the paradigm shift from Extract, Transform, Load (ETL) to Extract, Load, Transform (ELT) architectures within consumer identity data processing workflows. As organizations increasingly prioritize unified customer views across digital touchpoints, traditional ETL approaches have revealed limitations in handling the velocity, volume, and complexity of modern data streams. The transition to ELT represents more than a reordering of steps; it reflects a fundamental reimagining of data architecture in response to cloud computing capabilities and evolving identity resolution requirements. The article explores how ELT architectures enable more flexible handling of consumer identifiers, support sophisticated journey analysis, and facilitate real-time segmentation while enhancing governance and privacy controls. Key advantages discussed include the separation of concerns between data acquisition and transformation, improved scalability through cloud-native processing, and the democratization of data access through SQL-based transformations. Implementation of best practices covering orchestration, performance optimization, data quality management, and privacy-preserving techniques provides practical guidance for organizations modernizing their consumer identity data pipelines.

The migration of Human Capital Management (HCM) systems to cloud-based platforms has emerged as a transformative strategy for organizations seeking to enhance their workforce management capabilities. Cloud-based HCM solutions offer scalability, flexibility, and cost-effectiveness, enabling organizations to streamline HR processes, improve data accessibility, and leverage advanced analytics. This paper explores the best practices for implementing cloud-based HCM systems, emphasizing strategic planning, stakeholder engagement, data security, and change management. Through a comprehensive literature review and analysis of case studies from diverse industries, the study identifies critical factors that contribute to successful HCM cloud implementations. Additionally, the research addresses common challenges such as data migration complexities, integration with legacy systems, and ensuring user adoption. The findings underscore the importance of a structured implementation approach, continuous evaluation, and leveraging vendor support to maximize the benefits of cloud-based HCM solutions. Future research directions are proposed to further refine implementation frameworks, incorporating emerging technologies like artificial intelligence (AI) and machine learning (ML) to enhance HCM functionalities. The insights provided aim to equip HR professionals and organizational leaders with the knowledge to effectively transition to cloud-based HCM systems, thereby fostering a more agile, efficient, and engaged workforce.

Across many fields of science and engineering computers now play a significant role in scientific discovery through both large scale simulation and real time data acquisition. As these scientific simulations increasingly require new levels of complexity and fidelity, and leveraging increasing computational capabilities, scientists are migrating their applications back and forth from workstations to supercomputers, high performance clusters, and new distributed grids of computers. For applications which depend on live real world data, the migration to varied and distributed resources provides additional challenges. This migration involves reassigning and testing individual sensor communications and data path integrity for the application before the application is ready for a real time operating environment. This paper presents one general approach for communicating live real world data to simulations deployed on high-end computational resources. The architecture and design are presented for generic applications, before focusing on a particular scenario for drilling dynamics optimizations. In this scenario, simulations of drilling behavior depend on real time data from on-site (remote) sensors. Sensor data is streamed through to a simulation framework. The framework (available on a desktop computer or a supercomputer) displays relevant information, starts simulations with real time inputs then presents results and recommendations. For our application, we will use the Cactus Code (www.cactuscode.org) open-source high performance scientific computing framework as the simulation framework, and LabVIEW (www.ni.com/LabVIEW) as the data acquisition software. The advances in architecture portability allowed by the framework are summarized, and experiences of system uses are presented. Discussion will include opportunities found and learnings from using this platform in various environments highlighting drilling optimization.

Despite the far-reaching technological developments in the field of robotics (e.g. lightweight robots), the degree of implementation of innovative solutions in industrial practice is still comparatively low. This applies in particular to inexperienced users from small and medium-sized companies (SME). To facilitate the transfer of robot applications into practice, an internet-based configurator has been developed within the ROBOTOP research project. The configurator comprises planning functions along the whole engineering process. With regard to these functions, industrially implemented best practices are a main focus within the concept phase. Furthermore, they form a foundation for all further planning steps. In this context, the term ‘best practice’ refers to successfully implemented industrial applications. The acquisition, structuring and integration of these best practices into the web platform constitute the core of this paper. In order to highlight the emerging considerable benefits for industrial end-users, the digital implementation of best practices within the framework of the ROBOTOP internet platform is presented in the last step. The continuous use of digital planning platforms can ultimately pave the way for a significant increase in the degree of implementation of innovative robot applications.

A deconvolution approach is presented to use spectral light absorption and attenuation data to estimate the concentration of the major nonwater compounds in complex shelf sea waters. The inversion procedure requires knowledge of local material‐specific inherent optical properties (SIOPs) which are determined from natural samples using a bio‐optical model that differentiates between Case I and Case II waters and uses least squares linear regression analysis to provide optimal SIOP values. A synthetic data set is used to demonstrate that the approach is fundamentally consistent and to test the sensitivity to injection of controlled levels of artificial noise into the input data. Self‐consistency of the approach is further demonstrated by application to field data collected in the Ligurian Sea, with chlorophyll (Chl), the nonbiogenic component of total suspended solids (TSSnd), and colored dissolved organic material (CDOM) retrieved with RMSE of 0.61 mg m−3, 0.35 g m−3, and 0.02 m−1, respectively. The utility of the approach is finally demonstrated by application to depth profiles of in situ absorption and attenuation data resulting in profiles of optically significant constituents with associated error bar estimates. The advantages of this procedure lie in the simple input requirements, the avoidance of error amplification, full exploitation of the available spectral information from both absorption and attenuation channels, and the reasonably successful retrieval of constituent concentrations in an optically complex shelf sea.

Obtaining and visualizing the internal state and position information of the remote device using sensors are important aspects of industrial manufacturing. For large-scale geo-sensors that have been recently used, map-based management and visualization of the geo-sensor devices have become ubiquitous. Users often build multiple map symbols to represent the multiple states of a device based on traditional map symbols. Visualizing multiple geo-sensor data in real time with one map symbol is difficult. In this paper, a protocol-coupling map symbol and a construction method for real-time data visualization is introduced where different sensor states of the geo-sensor are expressed with one symbol. The sensor data visualization method in supervisory control and data acquisition systems (SCADA) was introduced and applied to the construction and visualization process of map symbols. First, based on the traditional vector map symbols and the communication protocol parsing interface, the mapping relationship between the sensor data item and the graphic element is defined in the map symbol construction process. Second, by referring to the streaming services method in ArcGIS GeoEvent, geo-sensor data acquisition and a transfer broker in a GIS server is built, through which the real-time sensor data can be transferred from the remote side to the map client and used for map symbol rendering. Finally, the new map symbols are used for real-time geo-sensor data visualization in applications. In the application of the real-time monitoring of geo-sensor devices, remote device information was acquired by sensor and transmitted to the broker then cached on the server side. If the cached sensor data has changed compared to the previous, the changed data will be pushed to map client by broker. The communication module in the map client that communicates with the broker receives changed geo-sensor data and triggers a refresh of the map. Then the protocol-coupling map symbol is rendered according to the mapping profile and the status of the geo-sensor device will be displayed on the map in real time. All the methods and processes were verified in client-server and browser-server GIS architecture.

Wireless Sensor Networks (WSNs) have emerged as a transformative technology, facilitating the real-time collection and dissemination of data from a myriad of physical environments. From environmental monitoring and healthcare to industrial automation and smart cities, the applications of WSNs are diverse and impactful. However, the increasing complexity and dynamic nature of these applications pose significant challenges to efficient and adaptive data access in WSNs. The proposed research addresses the multifaceted landscape of WSNs, acknowledging their crucial role in diverse domains. These networks consist of spatially distributed sensors that collaboratively collect data and communicate it to a central processing unit. Applications of WSNs range from monitoring environmental parameters such as temperature and humidity to more complex tasks like tracking healthcare metrics and managing smart infrastructure. Despite their versatility, WSNs face several challenges that hinder their optimal performance. These challenges include energy constraints of sensor nodes, the dynamic nature of the environment, and the need for realtime and reliable data access. In particular, the adaptability of WSNs to changing conditions and user requirementsremains a critical research challenge. The focus of this research is the development of an Adaptive Sensor Data Access Framework that addresses the challenges. This framework is envisioned to seamlessly integrate with mobile and web environments, thereby providing a responsive and adaptive approach to accessing sensor data in real time. By prioritizing adaptability, the research aims to enhance the overall efficiency, reliability, and user-centric customization of sensor data access. The Adaptive Sensor Data Access Framework will encompass advanced algorithms and mechanisms for real-time adjustments to changing environmental conditions, varying network dynamics, and evolving user preferences. The integration with mobile and web applications will be designed to be seamless, ensuring that the end-users experience a continuous and responsive flow of sensor data tailored to their specific needs. This research is positioned at the intersection of WSNs, mobile/web applications, and adaptive computing. The outcome is expected to yield a groundbreaking framework that not only addresses the challenges prevalent in WSNs but also sets the stage for a new paradigm of user-centric, adaptive sensor data access. The significance of this research extends to applications in environmental monitoring, healthcare, industrial automation, and beyond, where timely and accurate data access is paramount. The proposed research, through the developmentand validation of the Adaptive Sensor Data Access Framework, aims to contribute significantly to the evolution of WSNs, making them more resilient, user-friendly, and adaptable to the ever-changing demands of contemporary applications

Different ways are used for sensor data acquisition and management in wireless and sensor network (WSN). Two major approaches for data acquisition and management are data collection and logging network models. The data collection network provides a database abstraction from the base station. It considers the whole network as a database. Meantime, the data logging network is used to log the sensor readings and metadata inside the mote itself. Data logging network is provided a database for a sensor mote. The data collection network deals with real time sensed data and data logging network deals with stored sensor data bulk. Thus, there is a gap between them when communicating with each other. There isn't any existing approach to compare real time data and historical data. Hence, the proposed model bridges the gap between data logging network and data collection network. It addresses the real-world scenarios in a reliable manner, such as historical data and metadata management. A flexible sensor network which can act as both data collection and data logging networks based upon user requirements has been not introduced yet. Therefore, a novel hybrid model is a dire need of WSN. This research proved that the cost of communication energy of the network can be reduced by using the hybrid model. Hence, the total cost will also be reduced in WSN.

If data are the building blocks to generate information needed to acquire knowledge and understanding, then geodata, i.e. data with a geographic component (geodata), are the building blocks for information vital for decision-making at all levels of government, for companies and for citizens. Governments collect geodata and create, develop and use geo-information - also referred to as spatial information - to carry out public tasks as almost all decision-making involves a geographic component, such as a location or demographic information. Geo-information is often considered “special” for technical, economic reasons and legal reasons. Geoinformation is considered special for technical reasons because geo-information is multi-dimensional, voluminous and often dynamic, and can be represented at multiple scales. Because of this complexity, geodata require specialised hardware, software, analysis tools and skills to collect, to process into information and to use geoinformation for analyses. Geo-information is considered special for economic reasons because of the economic aspects, which sets it apart from other products. The fixed production costs to create geo-information are high, especially for large-scale geo-information, such as topographic data, whereas the variable costs of reproduction are low which do not increase with the number of copies produced. In addition, there are substantial sunk costs, which cannot be recovered from the market. As such, geo-information shows characteristics of a public good, i.e. a good that is non-rivalrous and non-excludable. However, to protect the high investments costs, re-use of geo-information may be limited by legal and/or technological means such as intellectual property rights and digital rights management. Thus, by making geo-information excludable, it becomes a club good, i.e. a non-rivalrous but excludable good. By claiming intellectual property rights, such as copyright and/or database rights, and restricting (re-)use through licences and licence fees, geo-information can be commercially exploited and used to recover some of the investment costs. Geo-information is considered special for a number of legal reasons. First, as geo-information has a geographic component, e.g. a reference to a location, geoinformation may contain personal data, sensitive company data, environmentally sensitive data, or data that may pose a threat to the national security. Therefore, the dataset may have to be adapted, aggregated or anonymised before it can be made public. Secondly, geo-information may be subject to intellectual property rights. There may be a copyright on cartographic images or database rights on digital information. Such intellectual property rights may be claimed by third parties involved in the information chain, e.g. a private company supplying aerial photography to the National Mapping Authority. The data holder may also claim intellectual property rights to commercially exploit the dataset and recoup some of the vast investment costs made to produce the dataset. Lastly, there may be other (international) legislation or agreements that may either impede or promote publishing public sector information, whereby in some cases, these policies may contradict each other. It has been recognised that to deal with national, regional and global challenges, it is essential that geo-information collected by one level of government or government organisation be shared between all levels of government via a so-called Spatial Data Infrastructure (SDI). The main principles governing SDIs are that data are collected once and (re-)used many times; that data should be easy to discover, access and use; and that data are harmonised so that it is possible to combine spatial data from different sources seamlessly. In line with the SDI governing principles, this dissertation considers accessibility of information to include all these aspects. Accessibility concerns not only access to data, i.e. to be able to view the data without being able to alter the contents but also re-use of data, i.e. to be able to download and/or invoke the data and to share data, including to be able to provide feedback and/or to provide input for co-generated information. Accessibility to public sector geo-information is not only essential for effective and efficient government policy-making but is also associated with realising other ambitions. Examples of these ambitions are a more transparent and accountable government, more citizens’ participation in democratic processes, (co-)generation of solutions to societal problems, and to increase economic value due to companies creating innovative products and services with public sector information as a resource. Especially the latter ambition has been the subject of many international publications stressing the enormous potential economic value of re-use of public sector (geo-) information by companies. Previous research indicated that re-users of public sector information in Europe encountered barriers related to technical, organisational, legal and financial aspects, which was deemed to be the main reason why in Europe the number of value added products and services based on public service information were lagging compared to the United States. Especially the latter two barriers (restrictive licence conditions and high licence fees) were often cited to be the main barriers for reusers in Europe. However, in spite of considerable resources invested by governments to establish spatial data infrastructures, to facilitate data portals and to release public sector information as open data, i.e. without legal and financial restrictions, the expected surge of value added products based on public sector information has not quite eventuated to date and the expected benefits still appear to lag expectations. When this research started a decade ago, the debate around accessibility of public sector information focussed on access policies. Access policies ranged from open access (data available with a minimum of legal restrictions and for no more than marginal dissemination costs) to full cost recovery, whereby all costs incurred in collection, creation, processing, maintenance and dissemination costs to be recovered from the re-users. Most of the public sector bodies in the European Union adhered to a cost recovery policy for allowing re-use of public sector information. In 2003, the European Commission adopted two directives to ensure better accessibility of public sector information Directive 2003/4/EC of the European Parliament and of the Council of 28 January 2003 on public access to environmental information and repealing Council Directive 90/313/EEC, the so-called Access Directive, provided citizens the right of access to environmental information. Citizens should be able to access documents related to the environment via a register, preferably in an electronic form and if a copy of a document was requested, the charges must not exceed marginal dissemination costs. Directive 2003/98/EC of the European Parliament and of the Council of 17 November 2003 on the re-use of public sector information, the co-called PSI Directive, intended to create conditions for a level playing field for all re-users of public sector information. However, the PSI Directive of 2003 left room for public sector organisations to maintain a cost recovery regime with restrictive licence conditions. In spite of these directives, access policies for geographic data were slow to change in most European nations. At the end of the last decade, accessibility of public sector information received two major impulses. The first major impulse was the implementation of Directive 2007/2/ EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE), the cocalled INSPIRE Directive, established a framework of standardisation rules for the data and publishing via web services, which significantly contributed to the accessibility of public sector geo-information. The second major impulse was the development of open data policies following the Digital Agenda for Europe adopted in 2010 and the USA Open Government Directive of 2009 and the Digital Agenda for Europe of 2010. These two impulses were the main drivers in Europe to start a careful move from cost recovery policies to open access or open data policies and for more public sector information to be made available as open data. Thus, of the four barriers to re-use of public sector information data cited in Chapter 1 (legal, financial, technical and organisational barriers), two barriers should have been lifted to a large degree due to open data. This shift to open data provided an excellent opportunity to test the hypothesis that the main barriers for re-users of public sector information were indeed restrictive licences and high fees as suggested by earlier research. Chapter 2 showed that by 2008, most European Union Member States had transposed and implemented the 2003/98/EC PSI Directive, however, in various ways and with considerable delay. By 2008, the effects of the PSI Directive were only slowly starting to emerge. A number of Member States reviewed their access policies and more public sector information became available for re-use. Some Member States made the information available free-of-charge or reduced their fees significantly. In many cases, where re-use fees were reduced the number of regular re-users increased significantly and total revenue even increased in spite of lower fees. Although the 2007/2/EC INSPIRE Directive paved the way for technical interoperability by providing guidelines for web services and catalogues, neither the INSPIRE Directive nor the PSI Directive had tackled the issue of legal interoperability. Chapter 2 also demonstrated that a major barrier to creating a level playing field for the private sector was the fact that some public sector bodies acted as value added resellers by developing and selling products and services based on their own data. Thus, the level playing field envisioned by the European Commission had not been realised. Chapter 3 researched the aspect of harmonised licences as a first step towards legal interoperability. Earlier research had indicated that one of the biggest barriers for re-users were complex, intransparent and inconsistent licence conditions, especially for re-users wanting to combine data from multiple sources. A survey of licences used by public sector data providers in the Netherlands demonstrated that although there were differences in length and language, there were also many similarities. The conclusion was that the introduction of a licence suite inspired by the Creative Commons concept would be a step towards increased transparency and consistency of geo-information license agreements. This chapter introduced a conceptual model for such a geo-information licence suite, the so-called Geo Shared licences. Both Creative Commons and Geo Shared licence suites enable harmonisation of licence conditions and promote transparency and legal interoperability, especially when re-users combine data from different sources. The Geo Shared licence suite became a serious option for inclusion into the draft version of the INSPIRE Directive as an annex. Unfortunately, the concept of one licence suite for the entire European Union came too early in 2006. The Geo Shared licences were further developed and implemented into the Dutch National Geo Register. In 2009, the European Commission recognised that PSI was the single largest source of information in Europe and the potential for re-use of PSI needed to be highlighted in the digital age. As part of a review of the 2003/98/EC PSI Directive, the European Commission carried out a round of consultations with stakeholders to seek their views on specific issues to be addressed in the future in 2010. In addition, the Commission commissioned a number of studies. These studies included a review of studies on public sector information re-use and related market studies, an assessment of the different models of supply and charging for public sector information and a study on public sector re-user in the cultural sector. The first study, carried out by Graham Vickery in 2011, showed that the overall economic gain from opening up public sector information as a resource for new products and services could be in the order of €40 billion per annum in the European Union. Both the Vickery Report and the second study, the so-called POPSIS Study, showed that for most public sector data providers their revenues from licence fees were relatively low in comparison to their total budget. After the evaluation, Directive 2013/37/EU of the European Parliament and of the Council of 26 June 2013 amending Directive 2003/98/EC on the re-use of public sector information was adopted and came into force on 17 July 2013. Chapter 4 described the main changes of the 2013/37/EU Amended PSI Directive, including the recommendation to employ open data licences. This chapter continued with a review of the various open data licences in use in Europe and analysed their interoperability. Although adoption of open data licences for public sector information should have addressed legal interoperability barriers for re-users, in practice, the different types of open data licences might not be so interoperable after all. Effectively, only a public domain declaration, such as a Creative Commons Zero (CC0) declaration, is suitable for open data re-users requiring with cross-border data sets and that such a public domain declaration is published in a prominent place to remove uncertainty for re-users. Without a public domain declaration, re-use of open data is still impeded as re-users are loathe to invest time into the development of value added products or services when it is uncertain if and which restrictions may be applicable and what the impact may be on their product or service. This dissertation also researched the financial and economic aspects of public sector information accessibility. Chapters 1 and 2 indicated that a cost recovery regime for dissemination of public sector information provided a financial barrier for private sector re-users because the fees charged were perceived to be too high. However, in 2008, there were still many advocates for maintaining a cost recovery regime. Especially public sector bodies that are not funded by the national Treasury, the socalled self-funding agencies, needed revenue from data sales to cover a substantial part of their operational costs. A sustainable source of revenue was viewed as essential to maintain the data at an adequate level, and to ensure actuality and continuity. Chapter 5 explored the potential business models and pricing mechanisms for public sector INSPIRE web services. Although, depending on the type of web service, and type of re-user, there might have been an argument for employing a subscription model as a pricing mechanism, business models based on generating revenue from public sector information would not be viable in the long run and were not in the spirit of the INSPIRE Directive. This research concluded that public sector information web services employing different pricing regimes were counterproductive to achieving financial interoperability. In Chapter 6, business models for public sector data providers were revisited, this time from an open data perspective. Government agencies, including self-funding government agencies are under increasing pressure to implement open data policies. This chapter analysed the business models of self-funding agencies either already providing open data or under pressure to provide (some) open data in the near future. The analysis showed which adaptions might be necessary to ensure the long-term availability of high quality open data and the long-term financial sustainability of self-funding agencies. The case studies confirmed that providing (raw) open data does not necessarily lead to losses in revenue in the long term as long as the organisation has enough flexibility to adapt its role in the information value chain, especially when revenue from licence fees represents only a relative small part of their total budget. The case studies indicated that switching to open data has resulted in internal efficiency gains. In practice, it is difficult to isolate and quantify the internal efficiency gains that are solely attributable to open data as the researched organisations continuously implement efficiency measures. However, the reported decreases in internal and external transaction costs due to open data are in line with the case study carried out in Chapter 7. Open data also provided an excellent opportunity to assess the effects of open data ex ante as baseline measurements could be carried out. To develop both quantitative and qualitative indicators to assess the success of a policy change is a challenge for open data initiatives. In Chapter 7, a model to assess the effects on the organisation of an open data provider was developed. Liander, a private energy network administrator mandated with a public task, planned to publish some of their datasets as open data in the autumn of 2013. This offered an excellent opportunity to apply the developed assessment model to provide an insight into internal, external, and relational effects on Liander. A benchmark was carried out prior to release of open data and a follow-up measurement one year later. The benchmark provided an insight into the then work processes and into the preparations required to implement open data. The follow-up monitor indicated that Liander open data are used by a wide range of users and have had a positive effect on the development of apps to aid energy savings. However, it remains a challenge to quantify the societal effects of such apps. The follow-up monitor also indicated that regular re-users of Liander data used the open data to improve existing applications and work processes rather than to create new products. The case study demonstrated that private energy companies could successfully release open data. The case study also showed that Liander served as a best-practice case for open data and had a flywheel effect on companies within the same sector. By 2015, nearly all energy network administrators had published similar open data. The monitoring model developed in this project was assessed to be suitable to monitor the open data effects on the organisation of the data provider. The assessment model developed and tested in Chapter 7 proved to be suitable to monitor the effects of open data on organisational level. However, to provide a more complete picture of the effects of open data and to assess if there are other barriers for re-users, a more holistic approach was required to assess the maturity of open data. Therefore, a holistic open data assessment framework addressing the supplier side, the governance side, and the user side of the open data was developed and applied to the Dutch open data infrastructure in Chapter 8. This Holistic Open Data Maturity Assessment Framework was used to evaluate the State of the Open Data Nation in the Netherlands and to provide valuable information on (potential) bottlenecks. The framework showed that geographic data scored significantly better than other types of government data. The standardisation and implementation rules laid down by INSPIRE Directive framework appear to have been a catalyst for moving geographic data to a higher level of maturity. The maturity assessment framework provided Dutch policy makers with useful inputs for further development of the open data ecosystem and development of well-founded strategies that will ensure the full potential of open data will be reached. Since the publication of the State of the Open Data Nation in 2014, a number of the recommendations have already been implemented. This dissertation demonstrated that many aspects that should facilitate accessibility, such as standardised metadata, have already been addressed for geodata. This research also showed that for other types of data, there is still a long way to go. There is a growing demand for other types of data, such as financial data and healthcare data. Public sector organisations holding such types of data need hands-on guidelines to enable publication of their datasets, preferably as open data. However, data published as open data are forever and cannot be recalled. Therefore, the decision to publish public sector data as open data is complex: datasets are often of a heterogeneous nature and may contain microdata (data that quantify observations or facts, such as data collected during surveys) Although microdata may not necessarily contain personal data, the datasets will probably have to be processed before publication to address confidentiality and data quality issues. In addition, there is a tension between open data and protection of personal data. The big question remains to which level the data need to be aggregated and/or anonymised to ensure protection of personal data now and in the future, and at the same time keeping sufficient significance to be re-usable. Another issue that needs further research is data-ownership of sensor data and co-created data. Increasingly, sensor data generated by e.g. smart phones, smart energy meters and traffic sensors are collected by the public sector and the private sector and become part of a big data ecosystem. In addition, public sector organisations cooperate with other public sector organisations and the private sector to create information from their data, so-called co-created information. Citizens also collect data or complement information on a voluntary basis, e.g. bird counts data. Co-created information will become more commonplace in the coming decades, as will the contribution of sensor data to a big data ecosystem. However, the aspect of who owns the data in which part of the information value chain has not been researched. Uncertainty related to third party rights will pose a barrier to publishing open data. Therefore, the aspect of data-ownership for sensor data and for co-created data should be further researched.

REVIEWS points up a general tendency in the book. Chance does not acknowledge recent research in a number of the fields connected to her subject (mythography , literary history, gender theory, or intellectual history), and this diminishes the impact of her research. Although this study evidences several weaknesses, its full descriptions of mythographic works are useful contributions to existing scholarship, as is the record of manuscript research. The ambitious design of the project—evidencing the author’s untiring enthusiasm for mythography —could, moreover, invite readers to investigate further this important branch of medieval learning. And, finally, Chance’s emphasis on mythographers’ covert interest in sexuality is a helpful revision of the traditional Robertsonian approach to these texts. Theresa Tinkle University of Michigan Carolyn P. Collette. Species, Phantasms, and Images: Vision and Medieval Psychology in The Canterbury Tales. Ann Arbor: The University of Michigan Press, 2001. Pp. ix, 208. $47.50. This book outlines basic principles of late medieval faculty psychology and explores how those principles inform the operations of sight and the representation of images in The Canterbury Tales. The most striking feature of medieval optical theory that differentiates it from optics today is the belief in ‘‘species,’’ the animate principle (or substance) linking the viewer with the object seen and grounding the act of vision in the ethics of universal intersubjectivity: ‘‘all subjects are objects, all objects are subjects. To look is to participate in a web of connections, to open oneself to the power of things—human, created, inert, divine’’ (p. 20). Chaucer, Collette argues, was well-informed about optical theory and used the principles of species and of visual phantasms in complex ways throughout his poetry. Moreover, he not only accepted the tents of optical theory, but made them a ground for his art, using optics to explore human relationships, truth and fictionality, the reliability of the imagination , and the responsibility of human will. Following an introduction that outlines optical theory, the remaining chapters of the book explore the workings of optics and faculty psychol393 ................. 9680$$ CH16 11-01-10 12:37:07 PS STUDIES IN THE AGE OF CHAUCER ogy in ten of the Canterbury Tales. Chapter Two, ‘‘The ‘Foule Prisoun of This Lyf’: Limited Visions in The Knight’s Tale,’’ argues that the actions of sight drive the tale at crucial moments and that the tale as a whole offers a commentary on both mutability and the unreliability of sensory data. Palamon and Arcite are blinded by their vision of Emily; Theseus, who uses sensory data about the physical world as ground of his philosophy , fails to prove universal order; the Knight/Narrator’s record of things seen reveals not chivalric glory, but rather ‘‘the darker forces that shape chivalric life’’ (p. 49). Chapter Three, ‘‘Tales of Marriage, Fantasye, and Wille,’’ pairs The Wife of Bath’s Tale with The Clerk’s Tale and The Merchant’s Tale with The Franklin’s Tale, arguing that each pair explores not just marital intersubjectivity , but also the ordered workings of sense, will, and imagination and the individual mind. Individual will is the principle of self-governance ; when will fails to govern the psyche, that failure has disastrous consequences for marriages. The Wife of Bath’s Tale is a story about the education of the rapist knight’s will to recognize the true good; The Clerk’s Tale reverses the recognition trope to explore the ways obsessional will can pervert right vision. While those two tales explore the workings of will, The Merchant’s Tale and The Franklin’s Tale are centered in the effect of ‘‘fantasye’’ on will. When ‘‘fantasye’’ (based on sight of an object or person) becomes obsessional, the disordered will correlates with marital discord. Chapter Four pairs The Physician’s Tale with The Pardoner’s Tale, arguing that both tales turn on a visual experience and examine the response of the will to visual desire—Appius’s sight of Virginia, the rioters’ sight of the gold. The Physician’s Tale, it is argued, locates its representation of Virginia and the discourse of nature within late medieval discourse on images. Sketching out first a brief but useful overview of the Lollard critique of images, Collette argues...