scholarly journals The Complexity and Expressive Power of Limit Datalog

2022 ◽  
Vol 69 (1) ◽  
pp. 1-83
Author(s):  
Mark Kaminski ◽  
Egor V. Kostylev ◽  
Bernardo Cuenca Grau ◽  
Boris Motik ◽  
Ian Horrocks
Keyword(s):  
Data Analysis ◽  
Expressive Power ◽  
Arithmetic Functions ◽  
Linear Programs ◽  
Data Complexity ◽  
Descriptive Complexity ◽  
Data Intensive ◽  
Additional Stability ◽  
Decidability And Complexity ◽  
The Impact

Motivated by applications in declarative data analysis, in this article, we study Datalog Z —an extension of Datalog with stratified negation and arithmetic functions over integers. This language is known to be undecidable, so we present the fragment of limit Datalog Z programs, which is powerful enough to naturally capture many important data analysis tasks. In limit Datalog Z , all intensional predicates with a numeric argument are limit predicates that keep maximal or minimal bounds on numeric values. We show that reasoning in limit Datalog Z is decidable if a linearity condition restricting the use of multiplication is satisfied. In particular, limit-linear Datalog Z is complete for Δ 2 EXP and captures Δ 2 P over ordered datasets in the sense of descriptive complexity. We also provide a comprehensive study of several fragments of limit-linear Datalog Z . We show that semi-positive limit-linear programs (i.e., programs where negation is allowed only in front of extensional atoms) capture coNP over ordered datasets; furthermore, reasoning becomes coNEXP-complete in combined and coNP-complete in data complexity, where the lower bounds hold already for negation-free programs. In order to satisfy the requirements of data-intensive applications, we also propose an additional stability requirement, which causes the complexity of reasoning to drop to EXP in combined and to P in data complexity, thus obtaining the same bounds as for usual Datalog. Finally, we compare our formalisms with the languages underpinning existing Datalog-based approaches for data analysis and show that core fragments of these languages can be encoded as limit programs; this allows us to transfer decidability and complexity upper bounds from limit programs to other formalisms. Therefore, our article provides a unified logical framework for declarative data analysis which can be used as a basis for understanding the impact on expressive power and computational complexity of the key constructs available in existing languages.

scholarly journals Foundations of Declarative Data Analysis Using Limit Datalog Programs

2017 ◽  
Author(s):  
Mark Kaminski ◽  
Bernardo Cuenca Grau ◽  
Egor V. Kostylev ◽  
Boris Motik ◽  
Ian Horrocks
Keyword(s):  
Information Systems ◽  
Data Analysis ◽  
Arithmetic Functions ◽  
Data Complexity ◽  
Additional Stability ◽  
Sound Foundation

Motivated by applications in declarative data analysis, we study DatalogZ---an extension of positive Datalog with arithmetic functions over integers. This language is known to be undecidable, so we propose two fragments. In limit DatalogZ predicates are axiomatised to keep minimal/maximal numeric values, allowing us to show that fact entailment is coNExpTime-complete in combined, and coNP-complete in data complexity. Moreover, an additional stability requirement causes the complexity to drop to ExpTime and PTime, respectively. Finally, we show that stable DatalogZ can express many useful data analysis tasks, and so our results provide a sound foundation for the development of advanced information systems.

scholarly journals Stratified Negation in Limit Datalog Programs

2018 ◽  
Author(s):  
Mark Kaminski ◽  
Bernardo Cuenca Grau ◽  
Egor V. Kostylev ◽  
Boris Motik ◽  
Ian Horrocks
Keyword(s):  
Data Analysis ◽  
Logic Programming ◽  
Arithmetic Function ◽  
Expressive Power ◽  
General Purpose ◽  
Data Complexity ◽  
Prior Work ◽  
Complexity Bounds ◽  
Logical Language ◽  
Query Engine

There has recently been an increasing interest in declarative data analysis, where analytic tasks are specified using a logical language, and their implementation and optimisation are delegated to a general-purpose query engine. Existing declarative languages for data analysis can be formalised as variants of logic programming equipped with arithmetic function symbols and/or aggregation, and are typically undecidable. In prior work, the language of limit programs was proposed, which is sufficiently powerful to capture many analysis tasks and has decidable entailment problem. Rules in this language, however, do not allow for negation. In this paper, we study an extension of limit programs with stratified negation-as-failure. We show that the additional expressive power makes reasoning computationally more demanding, and provide tight data complexity bounds. We also identify a fragment with tractable data complexity and sufficient expressivity to capture many relevant tasks.

scholarly journals Complexity and Expressive Power of Disjunction and Negation in Limit Datalog

2020 ◽  
Vol 34 (03) ◽  
pp. 2862-2869 ◽  
Author(s):  
Mark Kaminski ◽  
Bernardo Cuenca Grau ◽  
Egor V. Kostylev ◽  
Ian Horrocks
Keyword(s):  
Data Analysis ◽  
Expressive Power ◽  
Arithmetic Functions ◽  
Stable Model ◽  
Declarative Language ◽  
Ordered Structures ◽  
Disjunctive Programs ◽  
Linearity Condition

Limit Datalog is a fragment of Datalogℤ—the extension of Datalog with arithmetic functions over the integers—which has been proposed as a declarative language suitable for capturing data analysis tasks. In limit Datalog programs, all intensional predicates with a numeric argument are limit predicates that keep maximal (or minimal) bounds on numeric values. Furthermore, to ensure decidability of reasoning, limit Datalog imposes a linearity condition restricting the use of multiplication in rules. In this paper, we study the complexity and expressive power of limit Datalog programs extended with disjunction in the heads of rules and non-monotonic negation under the stable model semantics. We show that allowing for unrestricted use of negation leads to undecidability of reasoning. Decidability can be restored by stratifying the use of negation over predicates carrying numeric values. We show that the resulting language is Π2EXP -complete in combined complexity and that it captures Π2P over ordered structures in the sense of descriptive complexity.We also provide a study of several fragments of this language: we show that the complexity and expressive power of the full language are already reached for disjunction-free programs; furthermore, we show that semi-positive disjunctive programs are coNEXPcomplete and that they capture coNP.

INDONESIA LANGUAGE INTERFERENCE FORM IN BASIC PPL LEARNING THAILAND UNHASY COLLEGE SYUDENTS

2020 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Siti Mariana Ulfa
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Data Collection ◽  
Teaching Practice ◽  
Data Presentation ◽  
Analysis Techniques ◽  
Thai Students ◽  
The Impact ◽  
Collection Methods ◽  
Recording Techniques

AbstractHumans on earth need social interaction with others. Humans can use more than one language in communication. Thus, the impact that arises when the use of one or more languages is the contact between languages. One obvious form of contact between languages is interference. Interference can occur at all levels of life. As in this study, namely Indonesian Language Interference in Learning PPL Basic Thailand Unhasy Students. This study contains the form of interference that occurs in Thai students who are conducting teaching practices in the classroom. This type of research is descriptive qualitative research that seeks to describe any interference that occurs in the speech of Thai students when teaching practice. Data collection methods in this study are (1) observation techniques, (2) audio-visual recording techniques using CCTV and (3) recording techniques, by recording all data that has been obtained. Whereas the data wetness uses, (1) data triangulation, (2) improvement in perseverance and (3) peer review through discussion. Data analysis techniques in this study are (1) data collection, (2) data reduction, (3) data presentation and (4) conclusions. It can be seen that the interference that occurs includes (1) interference in phonological systems, (2) interference in morphological systems and (3) interference in syntactic systems. 

Household and Population-Level Behavioural Changes Due to COVID-19 Pandemic: A Smart Thermostat Based Comparative Data Analysis

2021 ◽  
Vol 10 (1) ◽  
pp. 1-6
Author(s):  
Kirti Sundar Sahu ◽  
Arlene Oetomo ◽  
Niloofar Jalali ◽  
Plinio P. Morita
Keyword(s):  
Data Analysis ◽  
Population Level ◽  
World Health ◽  
Motion Sensors ◽  
Household Level ◽  
Work From Home ◽  
Significant Difference ◽  
Health Organization ◽  
Smart Thermostat ◽  
The Impact

The World Health Organization declared the coronavirus outbreak as a pandemic on March 11, 2020. To inhibit the spread of COVID-19, governments around the globe, including Canada, have implemented physical distancing and lockdown measures, including a work-from-home policy. Canada in 2020 has developed a 24-Hour Movement Guideline for all ages laying guidance on the ideal amount of physical activity, sedentary behaviour, and sleep (PASS) for an individual in a day. The purpose of this study was to investigate changes on the household and population-level in lifestyle behaviours (PASS) and time spent indoors at the household level, following the implementation of physical distancing protocols and stay-at-home guidelines. For this study, we used 2019 and 2020 data from ecobee, a Canadian smart Wi-Fi thermostat company, through the Donate Your Data (DYD) program. Using motion sensors data, we quantified the amount of sleep by using the absence of movement, and similarly, increased sensor activation to show a longer duration of household occupancy. The key findings of this study were; during the COVID-19 pandemic, overall household-level activity increased significantly compared to pre-pandemic times, there was no significant difference between household-level behaviours between weekdays and weekends during the pandemic, average sleep duration has not changed, but the pattern of sleep behaviour significantly changed, specifically, bedtime and wake up time delayed, indoor time spent has been increased and outdoor time significantly reduced. Our data analysis shows the feasibility of using big data to monitor the impact of the COVID-19 pandemic on the household and population-level behaviours and patterns of change.

scholarly journals Evaluation of an Educational Outreach Campaign (IMPACT) on Pain Management Delivered to General Practices in Walsall

2021 ◽  
Vol 29 (Supplement_1) ◽  
pp. i48-i49
Author(s):  
S Visram ◽  
J Saini ◽  
R Mandvia
Keyword(s):  
Data Analysis ◽  
Pain Management ◽  
Cancer Pain ◽  
Educational Intervention ◽  
Opioid Analgesics ◽  
Educational Outreach ◽  
Opioid Prescribing ◽  
Prescribing Trends ◽  
The Impact

Abstract Introduction Opioid class drugs are a commonly prescribed form of analgesic widely used in the treatment of acute, cancer and chronic non-cancer pain. Up to 90% of individuals presenting to pain centres receive opioids, with doctors in the UK prescribing more and stronger opioids (1). Concern is increasing that patients with chronic pain are inappropriately being moved up the WHO ‘analgesic ladder’, originally developed for cancer pain, without considering alternatives to medications, (2). UK guidelines on chronic non-cancer pain management recommend weak opioids as a second-line treatment, when the first-line non-steroidal anti-inflammatory drugs / paracetamol) ineffective, and for short-term use only. A UK educational outreach programme by the name IMPACT (Improving Medicines and Polypharmacy Appropriateness Clinical Tool) was conducted on pain management. This research evaluated the IMPACT campaign, analysing the educational impact on the prescribing of morphine, tramadol and other high-cost opioids, in the Walsall CCG. Methods Standardised training material was delivered to 50 practices between December 2018 and June 2019 by IMPACT pharmacists. The training included a presentation on pain control, including dissemination of local and national guidelines, management of neuropathic, low back pain and sciatica as well as advice for prescribers on prescribing opioids in long-term pain, with the evidence-base. Prescribing trends in primary care were also covered in the training, and clinicians were provided with resources to use in their practice. Data analysis included reviewing prescribing data and evaluating the educational intervention using feedback from participants gathered via anonymous questionnaires administered at the end of the training. Prescribing data analysis was conducted by Keele University’s Medicines Management team via the ePACT 2 system covering October 2018 to September 2019 (two months before and three months after the intervention) were presented onto graphs to form comparisons in prescribing trends of the Midland CCG compared to England. Results Questionnaires completed at the end of sessions showed high levels of satisfaction, with feedback indicating that participants found the session well presented, successful at highlighting key messages, and effective in using evidence-based practice. 88% of participants agreed the IMPACT campaign increased their understanding of the management and assessment of pain, and prescribing of opioids and other resources available to prescribers. The majority (85%) wished to see this form of education being repeated regularly in the future for other therapeutic areas. Analysis of the prescribing data demonstrated that the total volume of opioid analgesics decreased by 1.7% post-intervention in the Midlands CCG in response to the pharmacist-led educational intervention. As supported by literature, the use of educational strategies, including material dissemination and reminders as well as group educational outreach was effective in engaging clinicians, as demonstrated by the reduction in opioid prescribing and high GP satisfaction in this campaign. Conclusion The IMPACT campaign was effective at disseminating pain-specific guidelines for opioid prescribing to clinicians, leading to a decrease in overall prescribing of opioid analgesics. Educational outreach as an approach is practical and a valuable means to improve prescribing by continuing medical education. References 1. Els, C., Jackson, T., Kunyk, D., Lappi, V., Sonnenberg, B., Hagtvedt, R., Sharma, S., Kolahdooz, F. and Straube, S. (2017). Adverse events associated with medium- and long-term use of opioids for chronic non-cancer pain: an overview of Cochrane Reviews. Cochrane Database of Systematic Reviews. This provided the statistic of percentage receiving opioids that present to pain centres. 2. Heit, H. (2010). Tackling the Difficult Problem of Prescription Opioid Misuse. Annals of Internal Medicine, 152(11), p.747. Issues with prescriptions and inappropriate moving up the WHO ladder.

scholarly journals Impact of COVID-19 on the Customer End of Retail Supply Chains: A Big Data Analysis of Consumer Satisfaction

2021 ◽  
Vol 13 (3) ◽  
pp. 1464
Author(s):  
Patrick Brandtner ◽  
Farzaneh Darbanian ◽  
Taha Falatouri ◽  
Chibuzor Udokwu
Keyword(s):  
Data Analysis ◽  
Supply Chains ◽  
Consumer Satisfaction ◽  
Future Research ◽  
Grocery Shopping ◽  
Product Availability ◽  
Analysis Technique ◽  
Retail Chains ◽  
Retail Supply Chains ◽  
The Impact

The COVID-19 pandemic has been one of the biggest disruptive events of recent decades and has had a global effect on society and the economy. The political regulations resulting from COVID-19 also led to significant changes in physical grocery shopping. However, the specific impact of COVID-19 on consumer satisfaction at the customer end of retail supply chains, i.e., the point-of-sale (PoS), has not yet been addressed. By gathering and analyzing consumer satisfaction data (ratings) and sentiments (evaluation comments) available on the open web, the current study evaluates the impact of COVID-19 on consumer satisfaction at the PoS. Focusing on the five biggest retail chains in Austria, the results show that there was a general and significant decline in consumer satisfaction due to the pandemic. The results also show a high impact of political regulations on consumer satisfaction. Furthermore, the text-mining based analysis of evaluation comments indicate that store layout and facilities, as well as product availability and waiting time had a great impact on consumer satisfaction. In total, over 533,000 consumer satisfaction ratings and over 153,000 textual comments have been analyzed, providing the basis for a comprehensive and sound discussion of the impact of COVID-19 on consumer satisfaction and perceptions. Future research could focus on applying the used data analysis technique and the adapted consumer sentiment dimensions in different settings, such as countries other than Austria or smaller retail chains.

scholarly journals Reproducible and accessible analysis of transposon insertion sequencing in Galaxy for qualitative essentiality analyses

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Delphine Larivière ◽  
Laura Wickham ◽  
Kenneth Keiler ◽  
Anton Nekrutenko ◽  
Keyword(s):  
Data Analysis ◽  
Promoter Sequence ◽  
Entire Genome ◽  
Link Type ◽  
Transposon Insertion ◽  
Control Procedures ◽  
Reproducible Analysis ◽  
Using Data ◽  
Transposon Insertion Sequencing ◽  
The Impact

Abstract Background Significant progress has been made in advancing and standardizing tools for human genomic and biomedical research. Yet, the field of next-generation sequencing (NGS) analysis for microorganisms (including multiple pathogens) remains fragmented, lacks accessible and reusable tools, is hindered by local computational resource limitations, and does not offer widely accepted standards. One such “problem areas” is the analysis of Transposon Insertion Sequencing (TIS) data. TIS allows probing of almost the entire genome of a microorganism by introducing random insertions of transposon-derived constructs. The impact of the insertions on the survival and growth under specific conditions provides precise information about genes affecting specific phenotypic characteristics. A wide array of tools has been developed to analyze TIS data. Among the variety of options available, it is often difficult to identify which one can provide a reliable and reproducible analysis. Results Here we sought to understand the challenges and propose reliable practices for the analysis of TIS experiments. Using data from two recent TIS studies, we have developed a series of workflows that include multiple tools for data de-multiplexing, promoter sequence identification, transposon flank alignment, and read count repartition across the genome. Particular attention was paid to quality control procedures, such as determining the optimal tool parameters for the analysis and removal of contamination. Conclusions Our work provides an assessment of the currently available tools for TIS data analysis. It offers ready to use workflows that can be invoked by anyone in the world using our public Galaxy platform (https://usegalaxy.org). To lower the entry barriers, we have also developed interactive tutorials explaining details of TIS data analysis procedures at https://bit.ly/gxy-tis.

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