Towards an automatic data value analysis method for relational databases

Data is becoming one of the world’s most valuable resources and it is suggested that those who own the data will own the future. However, despite data being an important asset, data owners struggle to assess its value. Some recent pioneer works have led to an increased awareness of the necessity for measuring data value. They have also put forward some simple but engaging survey-based methods to help with the first-level data assessment in an organisation. However, these methods are manual and they depend on the costly input of domain experts. In this paper, we propose to extend the manual survey-based approaches with additional metrics and dimensions derived from the evolving literature on data value dimensions and tailored specifically for our use case study. We also developed an automatic, metric-based data value assessment approach that (i) automatically quantifies the business value of data in Relational Databases (RDB), and (ii) provides a scoring method that facilitates the ranking and extraction of the most valuable RDB tables. We evaluate our proposed approach on a real-world RDB database from a small online retailer (MyVolts) and show in our experimental study that the data value assessments made by our automated system match those expressed by the domain expert approach

Structural Vulnerability Analysis of Electric Power Distribution Grids

Power grid outages cause huge economical and societal costs. Disruptions in the power distribution grid are responsible for a significant fraction of electric power unavailability to customers. The impact of extreme weather conditions, continuously increasing demand, and the over-ageing of assets in the grid, deteriorates the safety of electric power delivery in the near future. It is this dependence on electric power that necessitates further research in the power distribution grid security assessment. Thus measures to analyze the robustness characteristics and to identify vulnerabilities as they exist in the grid are of utmost importance. This research investigates exactly those concepts- the vulnerability and robustness of power distribution grids from a topological point of view, and proposes a metric to quantify them with respect to assets in a distribution grid. Real-world data is used to demonstrate the applicability of the proposed metric as a tool to assess the criticality of assets in a distribution grid

A Tripartite Framework for Leadership Evaluation

The Tripartite Framework for Leadership Evaluation provides a comprehensive examination of the leadership evaluation landscape and makes key recommendations about how the field of leadership evaluation should proceed. The chief concern addressed by this working paper is the use of student outcome data as a measurement of leadership effectiveness. A second concern in our work with urban leaders is the absence or surface treatment of race and equity in nearly all evaluation instruments or processes. Finally, we call for an overhaul of the conventional cycle of inquiry, which is based largely on needs analysis and leader deficits, and incomplete use of evidence to support recurring short cycles within the larger yearly cycle of inquiry

Towards Validating Risk Indicators Based on Measurement Theory (Extended version)

Due to the lack of quantitative information and for cost-efficiency, most risk assessment methods use partially ordered values (e.g. high, medium, low) as risk indicators. In practice it is common to validate risk indicators by asking stakeholders whether they make sense. This way of validation is subjective, thus error prone. If the metrics are wrong (not meaningful), then they may lead system owners to distribute security investments inefficiently. For instance, in an extended enterprise this may mean over investing in service level agreements or obtaining a contract that provides a lower security level than the system requires. Therefore, when validating risk assessment methods it is important to validate the meaningfulness of the risk indicators that they use. In this paper we investigate how to validate the meaningfulness of risk indicators based on measurement theory. Furthermore, to analyze the applicability of the measurement theory to risk indicators, we analyze the indicators used by a risk assessment method specially developed for assessing confidentiality risks in networks of organizations

Estimating ToE Risk Level using CVSS

Security management is about calculated risk and requires continuous evaluation to ensure cost, time and resource effectiveness. Parts of which is to make future-oriented, cost-benefit investments in security. Security investments must adhere to healthy business principles where both security and financial aspects play an important role. Information on the current and potential risk level is essential to successfully trade-off security and financial aspects. Risk level is the combination of the frequency and impact of a potential unwanted event, often referred to as a security threat or misuse. The paper presents a risk level estimation model that derives risk level as a conditional probability over frequency and impact estimates. The frequency and impact estimates are derived from a set of attributes specified in the Common Vulnerability Scoring System (CVSS). The model works on the level of vulnerabilities (just as the CVSS) and is able to compose vulnerabilities into service levels. The service levels define the potential risk levels and are modelled as a Markov process, which are then used to predict the risk level at a particular time

Towards Validating Risk Indicators Based on Measurement Theory

Due to the lack of quantitative information and for cost-efficiency purpose, most risk assessment methods use partially ordered values (e.g. high, medium, low) as risk indicators.\ud In practice it is common to validate risk scales by asking stakeholders whether they make sense. This way of validation is subjective, thus error prone. If the metrics are wrong (not meaningful), then they may lead system owners to distribute security investments inefficiently. Therefore, when validating risk assessment methods it is important to validate the meaningfulness of the risk scales that they use. In this paper we investigate how to validate the meaningfulness of risk indicators based on measurement theory. Furthermore, to analyze the applicability of measurement theory to risk indicators, we analyze the indicators used by a particular risk assessment method specially developed for assessing confidentiality risks in networks of organizations

Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction

Assessing systemic risk in financial markets is of great importance but it often requires data that are unavailable or available at a very low frequency. For this reason, systemic risk assessment with partial information is potentially very useful for regulators and other stakeholders. In this paper we consider systemic risk due to fire sales spillover and portfolio rebalancing by using the risk metrics defined by Greenwood et al. (2015). By using the Maximum Entropy principle we propose a method to assess aggregated and single bank's systemicness and vulnerability and to statistically test for a change in these variables when only the information on the size of each bank and the capitalization of the investment assets are available. We prove the effectiveness of our method on 2001-2013 quarterly data of US banks for which portfolio composition is available.Comment: 36 pages, 6 figures, Accepted on Journal of Economic Dynamics and Contro

Impact Investing: a primer for family offices

The goal of this report is to help family offices ask the right questions as they contemplate their path into impact investing. It is important to recognize that impact investing may not suit all investors. There will be family offices which conclude impact investing is not appropriate at this stage for them. While we are passionate about the potential of impact investing, we acknowledge the best future for the sector is where each investor can make informed choices about their own best interest. Each investor and investment institution needs to evaluate if impact investing fits with its needs, interests and unique context. It is with that in mind that we offer this report as a resource and tool that family offices can use to begin the conversations internally, to craft and design their own engagement strategy on impact investing with family members, advisers and potential investees, as well as to ensure that not only is their wealth growing in value, but also that their wealth can reflect their values

Built Asset Management Climate Change Model

Purpose - Climate change continues to pose major challenges to those responsible for the management of built assets. The adaptation required to address long-term building performance affected by climate change rarely get prioritised above more immediate, short-term needs (general built asset management needs). This paper, thus presents results of an action research addressing climate change adaptation of selected social housing stock in the UK. Design /methodology/approach – The study adopts an in-depth participatory action research with a London based social landlord and integrates climate change adaptation framework and performance based model established through author’s previous research projects. Findings - A staged process for including adaptation measures in built asset management strategy is developed along with metrics to analyse the performance of the housing stock against climate change impacts of flooding. The prioritisation of adaptation measure implementation into long term built asset management plans was examined through cost based appraisal. Research Limitation – The research was carried out with a singular organisation, already acquainted with potential climate change impacts, vulnerability and adaptive capacity assessment. The process adopted will differ for similar organisation in the sector with different settings and limited working knowledge of climate change impact assessment. Originality /Value –. In addition to the practical results from the study the paper outlines a novel process that integrates resilience concepts, risk framing (to climate change impacts) and performance management into built asset management (maintenance and refurbishment) planning. Practical implications - The paper concludes with a 10 step process developed as an aide memoir to guide social landlords through the climate change adaptation planning process

Towards an integrated perspective on fleet asset management: engineering and governance considerations

The traditional engineering perspective on asset management concentrates on the operational performance the assets. This perspective aims at managing assets through their life-cycle, from technical specification, to acquisition, operation including maintenance, and disposal. However, the engineering perspective often takes for granted organizational-level factors. For example, a focus on performance at the asset level may lead to ignore performance measures at the business unit level. The governance perspective on asset management usually concentrates on organizational factors, and measures performance in financial terms. In doing so, the governance perspective tends to ignore the engineering considerations required for optimal asset performance. These two perspectives often take each other for granted. However experience demonstrates that an exclusive focus on one or the other may lead to sub-optimal performance. For example, the two perspectives have different time frames: engineering considers the long term asset life-cycle whereas the organizational time frame is based on a yearly financial calendar. Asset fleets provide a relevant and important context to investigate the interaction between engineering and governance views on asset management as fleets have distributed system characteristics. In this project we investigate how engineering and governance perspectives can be reconciled and integrated to enable optimal asset and organizational performance in the context of asset fleets