Databases and Information Systems Commons^™

Lessons From The Club Homeschool Capstone: Testing, Data Discipline, And The Computer Science Curriculum, Shane Brown

University Honors Theses

This thesis looks at the CLUB Homeschool Capstone project to argue that Portland State University's Computer Science curriculum should introduce testing and data quality discipline earlier and more intentionally than it does now. As team lead of a seven-person team, I coordinated sprint planning, communicated with the sponsor, and developed custom Discourse plugins that enhanced an existing forum platform instead of creating a separate application database, as requested by the sponsor. The project's requirements document called for a formal testing plan, but our team lacked the practical experience to implement one. This gap became evident through my internships as a …

The Institutional Challenges Of A Quantified Self Study: An Attempt To Ascertain How Data Collected From A Mobile Device Can Be An Indicator Of Personal Mental Health Over Time, Julian Lazaras

University Honors Theses

The adoption of an application of new technology always comes with a bias, this is never more true for the case of human behavioral analytics within higher education. While movements such as the quantified self movement make strides to reinterpret the realm of data analytics, psychology, and computer science, there are inevitably limitations to the adoption and application of such approaches within the standard realm of research. Herein is presented a case where an effort to evaluate the prospect of use of mobile phone data as secondary indicators of personal mental health through the lens of data analysis was put …

Improving Tattle-Tale K-Deniability, Nicholas G.E. Morales

Student Research Symposium

Ensuring privacy for databases is an ongoing struggle. While the majority of work has focused on using access control lists to protect sensitive data these methods are vulnerable to inference attacks. A set of algorithms, referred to as Tattle-Tale, was developed that could protect sensitive data from being inferred however its runtime performance wasn’t suitable for production code. This set of algorithms contained two main subsets, Full Deniability and K-Deniability. My research focused on improving the runtime or utility of the K-Deniability algorithms. I investigated the runtime of the K-Deniability algorithms to identify what was slowing the process down. Aside …

A Novel Caching Algorithm For Efficient Fine-Grained Access Control In Database Management Systems, Anadi Shakya

Student Research Symposium

Fine-grained access Control (FGAC) in DBMS is vital for restricting user access to authorized data and enhancing security. FGAC policies govern how users are granted access to specific resources based on detailed criteria, ensuring security and privacy measures. Traditional methods struggle with scaling policies to thousands, causing delays in query responses. This paper introduces a novel caching algorithm designed to address this challenge by accelerating query processing and ensuring compliance with FGAC policies. In our approach, we create a circular hashmap and employ different replacement techniques to efficiently manage the cache, prioritizing entries that are visited more frequently. To evaluate …

Epl Card Reader Capstone: The Strengths Of Partner Programming From A Team Leader's Perspective, Zach Yost

University Honors Theses

This essay looks to reflect back upon the successes and failures of the EPL Card Reader capstone project, sponsored by Edward Ivory, head of Portland State University's Electronics Prototyping Lab. The EPL Card Reader's goal is to provide a means of tracking and updating student activity and training on the various machines in the lab. Using a local computer port to host this web app a lab administrator or manager is able to scan a student's access badge to review which machines they have been trained on as well as update that training status. The app also has a running …

Forest Park Trail Monitoring, Adan Robles, Colton S. Maybee, Erin Dougherty

REU Final Reports

Forest Park, one of the largest public parks in the United States with over 40 trails to pick from when planning a hiking trip. One of the main problems this park has is that there are too many trails, and a lot of the trails extend over 3 miles. Due to these circumstances’ trails are not checked frequently and hikers are forced to hike trails in the area with no warnings of potential hazards they can encounter. In this paper I researched how Forest Park currently monitors its trails and then set up a goal to solve the problem. We …

Digitally Reporting Trail Obstructions In Forest Park, Colton S. Maybee

REU Final Reports

The inclusion of technology on the trail can lead to better experiences for everyone involved in the hobby. Hikers can play a more prominent role in the maintenance of the trails by being able to provide better reports of obstructions while directly on the trail. This paper goes into the project of revamping the obstruction report system applied at Forest Park in Portland, Oregon. Most of my contributions to the project focus on mobile app development with some research into path planning algorithms related to the continuations of this project.

Client Access Feature Engineering For The Homeless Community Of The City Of Portland, Oswaldo Ceballos Jr

altREU Projects

Given the severity of homeless in many cities across the country, the project at hand attempts to assist a service provider organization called Central City Concern (CCC) with their mission of providing services to the community of Portland. These services include housing, recovery, health care, and jobs. With many different types of services available through the works of CCC, there exists an abundance of information and data pertaining to the individuals that interact with the CCC service system. The goal of this project is to perform an exploratory analysis and feature engineer the existing datasets CCC has collected over the …

Balancing Security, Performance And Deployability In Encrypted Search, David Joel Pouliot

Dissertations and Theses

Encryption is an important tool for protecting data, especially data stored in the cloud. However, standard encryption techniques prevent efficient search. Searchable encryption attempts to solve this issue, protecting the data while still providing search functionality. Retaining the ability to search comes at a cost of security, performance and/or utility.

An important practical aspect of utility is compatibility with legacy systems. Unfortunately, the efficient searchable encryption constructions that are compatible with these systems have been proven vulnerable to attack, even against weaker adversary models.

The goal of this work is to address this security problem inherent with efficient, legacy compatible …

The Complexities Of Open Data, Hector Dominguez

Systems Science Friday Noon Seminar Series

Hector Dominguez is the current Open Data Coordinator at the City of Portland, and there are several lessons learned and strategies developed in the several months of work in this position. Hector will share some challenges on creating trusted and reliable data and information services, as well as the opportunities to work with Urban Data to resolve city challenges and to support achieving the City's goals in the coming years.

In this talk, Hector will share how modeling and defining the right metrics are not the only factors to implementing a citywide program, but rather, how ethics, communications and strategy …

Data Warehousing Class Project Report, Gaya Haciane, Chuan Chieh Lu, Rassaniya Lerdphayakkarat, Rudraxi Mitra

Engineering and Technology Management Student Projects

Data mining is widely described or defined as the discipline of: “making sense of the data”. In today’s day and age, the rise of ubiquity of information calls for more advanced and developed techniques to mine the data and come up with insights. Data mining finds applications in many different fields and industries: Whether it is in Embryology, Crops, Elections, or Business Marketing...etc. It is not a wild assumption to consider that every organization in the world has some data mining capabilities or its main activity necessitates it and they have some third party organization doing that for them. One …

Exploratory Reconstructability Analysis Of Accident Tbi Data, Martin Zwick, Nancy Ann Carney, Rosemary Nettleton

Complex Systems Faculty Publications and Presentations

This paper describes the use of reconstructability analysis to perform a secondary study of traumatic brain injury data from automobile accidents. Neutral searches were done and their results displayed with a hypergraph. Directed searches, using both variable-based and state-based models, were applied to predict performance on two cognitive tests and one neurological test. Very simple state-based models gave large uncertainty reductions for all three DVs and sizeable improvements in percent correct for the two cognitive test DVs which were equally sampled. Conditional probability distributions for these models are easily visualized with simple decision trees. Confounding variables and counter-intuitive findings are …

Fast And Adaptive Indexing Of Multi-Dimensional Observational Data, Sheng Wang, David Maier, Beng Chin Ooi

Computer Science Faculty Publications and Presentations

Sensing devices generate tremendous amounts of data each day, which include large quantities of multi-dimensional measurements. These data are expected to be immediately available for real-time analytics as they are streamed into storage. Such scenarios pose challenges to state-of-the-art indexing methods, as they must not only support efficient queries but also frequent updates. We propose here a novel indexing method that ingests multi-dimensional observational data in real time. This method primarily guarantees extremely high throughput for data ingestion, while it can be continuously refined in the background to improve query efficiency. Instead of representing collections of points using Minimal Bounding …

Identifying Relationships Between Scientific Datasets, Abdussalam Alawini

Dissertations and Theses

Scientific datasets associated with a research project can proliferate over time as a result of activities such as sharing datasets among collaborators, extending existing datasets with new measurements, and extracting subsets of data for analysis. As such datasets begin to accumulate, it becomes increasingly difficult for a scientist to keep track of their derivation history, which complicates data sharing, provenance tracking, and scientific reproducibility. Understanding what relationships exist between datasets can help scientists recall their original derivation history. For instance, if dataset A is contained in dataset B, then the connection between A and B could be that A was …

Optimizing Data Movement In Hybrid Analytic Systems, Patrick Michael Leyshock

Dissertations and Theses

Hybrid systems for analyzing big data integrate an analytic tool and a dedicated data-management platform, storing data and operating on the data at both components. While hybrid systems have benefits over alternative architectures, in order to be effective, data movement between the two hybrid components must be minimized. Extant hybrid systems either fail to address performance problems stemming from inter-component data movement, or else require the user to explicitly reason about and manage data movement. My work presents the design, implementation, and evaluation of a hybrid analytic system for array-structured data that automatically minimizes data movement between the hybrid components. …

Search Tool That Utilizes Scientific Metadata Matched Against User-Entered Parameters, Veronika Margaret Megler, David Maier

Computer Science Faculty Publications and Presentations

A method for providing proximate dataset recommendations can begin with the creation of metadata records corresponding to datasets that represent scientific data by a scientific dataset search tool. The metadata records can conform to a standardized structural definition, and may be hierarchical. Values for the data elements of the metadata records can be contained within the datasets. Metadata records with a value that is proximate to a user-entered search parameter can be identified. A proximity score can be calculated for each identified metadata record. The proximity score can express a relevance of the corresponding dataset to the user-entered search parameters. …

Based On Repeated Experience, System For Modification Of Expression And Negating Overload From Media And Optimizing Referential Efficiency, Peter R. Badovinatz, Veronika M. Megler

Computer Science Faculty Publications and Presentations

Content items are revealed to a user based on whether they have been previously reviewed by the user. A number of content items are thus received over time. The content items may be discrete content items, or may be portions of a content stream, and may be received over different media. For each content item, it is determined whether the content item was previously reviewed by a user. Where the content item was not previously reviewed, the item is revealed to the user, such as by being displayed or announced to the user. Where the content item was previously reviewed, …

Data Near Here: Bringing Relevant Data Closer To Scientists, Veronika M. Megler, David Maier

Computer Science Faculty Publications and Presentations

Large scientific repositories run the risk of losing value as their holdings expand, if it means increased effort for a scientist to locate particular datasets of interest. We discuss the challenges that scientists face in locating relevant data, and present our work in applying Information Retrieval techniques to dataset search, as embodied in the Data Near Here application.

Taming The Metadata Mess, Veronika Margaret Megler

Computer Science Faculty Publications and Presentations

The rapid growth of scientific data shows no sign of abating. This growth has led to a new problem: with so much scientific data at hand, stored in thousands of datasets, how can scientists find the datasets most relevant to their research interests? We have addressed this problem by adapting Information Retrieval techniques, developed for searching text documents, into the world of (primarily numeric) scientific data. We propose an approach that uses a blend of automated and “semi-curated” methods to extract metadata from large archives of scientific data, then evaluates ranked searches over this metadata. We describe a challenge identified …

The Problem Of Semantics In The Metadata Mess, Veronika Margaret Megler, David Maier

Computer Science Faculty Publications and Presentations

This presentation addresses problems related to the volume of available scientific data, and its accessibility or inaccessibility to researchers who seek it. Topics addressed include metadata and reducing semantic diversity, especially as they refer to geospatial and other architectures

A Data-Descriptive Feedback Framework For Data Stream Management Systems, Rafael J. Fernández Moctezuma

Dissertations and Theses

Data Stream Management Systems (DSMSs) provide support for continuous query evaluation over data streams. Data streams provide processing challenges due to their unbounded nature and varying characteristics, such as rate and density fluctuations. DSMSs need to adapt stream processing to these changes within certain constraints, such as available computational resources and minimum latency requirements in producing results. The proposed research develops an inter-operator feedback framework, where opportunities for run-time adaptation of stream processing are expressed in terms of descriptions of substreams and actions applicable to the substreams, called feedback punctuations. Both the discovery of adaptation opportunities and the exploitation of …

Relativistic Red-Black Trees, Philip William Howard, Jonathan Walpole

Computer Science Faculty Publications and Presentations

Operating system performance and scalability on sharedmemory many-core systems depends critically on efficient access to shared data structures. Scalability has proven difficult to achieve for many data structures. In this paper we present a novel and highly scalable concurrent red-black tree. Red-black trees are widely used in operating systems, but typically exhibit poor scalability. Our red-black tree has linear read scalability, uncontended read performance that is at least 25% faster than other known approaches, and deterministic lookup times for a given tree size, making it suitable for realtime applications.

Finding Haystacks With Needles: Ranked Search For Data Using Geospatial And Temporal Characteristics, Veronika Margaret Megler, David Maier

Computer Science Faculty Publications and Presentations

The past decade has seen an explosion in the number and types of environmental sensors deployed, many of which provide a continuous stream of observations. Each individual observation consists of one or more sensor measurements, a geographic location, and a time. With billions of historical observations stored in diverse databases and in thousands of datasets, scientists have difficulty finding relevant observations. We present an approach that creates consistent geospatial-temporal metadata from large repositories of diverse data by blending curated and automated extracts. We describe a novel query method over this metadata that returns ranked search results to a query with …

Can Infopipes Facilitate Reuse In A Traffic Application?, Emerson Murphy-Hill, Chuan-Kai Lin, Andrew P. Black, Jonathan Walpole

Computer Science Faculty Publications and Presentations

Infopipes are presented as reusable building blocks for streaming applications. To evaluate this claim, we have built a significant traffic application in Smalltalk using Infopipes. This poster presents a traffic problem and solution, a short introduction to Infopipes, and the types of reuse Infopipes facilitate in our implementation.

Reconstructability Analysis With Fourier Transforms, Martin Zwick

Complex Systems Faculty Publications and Presentations

Fourier methods used in two‐ and three‐dimensional image reconstruction can be used also in reconstructability analysis (RA). These methods maximize a variance‐type measure instead of information‐theoretic uncertainty, but the two measures are roughly collinear and the Fourier approach yields results close to that of standard RA. The Fourier method, however, does not require iterative calculations for models with loops. Moreover, the error in Fourier RA models can be assessed without actually generating the full probability distributions of the models; calculations scale with the size of the data rather than the state space. State‐based modeling using the Fourier approach is also …

Directed Extended Dependency Analysis For Data Mining, Thaddeus T. Shannon, Martin Zwick

Complex Systems Faculty Publications and Presentations

Extended dependency analysis (EDA) is a heuristic search technique for finding significant relationships between nominal variables in large data sets. The directed version of EDA searches for maximally predictive sets of independent variables with respect to a target dependent variable. The original implementation of EDA was an extension of reconstructability analysis. Our new implementation adds a variety of statistical significance tests at each decision point that allow the user to tailor the algorithm to a particular objective. It also utilizes data structures appropriate for the sparse data sets customary in contemporary data mining problems. Two examples that illustrate different approaches …

An Overview Of Reconstructability Analysis, Martin Zwick

Complex Systems Faculty Publications and Presentations

This paper is an overview of reconstructability analysis (RA), a discrete multivariate modeling methodology developed in the systems literature; an earlier version of this tutorial is Zwick (2001). RA was derived from Ashby (1964), and was developed by Broekstra, Cavallo, Cellier Conant, Jones, Klir, Krippendorff, and others (Klir, 1986, 1996). RA resembles and partially overlaps log‐line (LL) statistical methods used in the social sciences (Bishop et al., 1978; Knoke and Burke, 1980). RA also resembles and overlaps methods used in logic design and machine learning (LDL) in electrical and computer engineering (e.g. Perkowski et al., 1997). Applications of RA, like …

Infosphere Project: An Overview, Calton Pu, Jonathan Walpole

Computer Science Faculty Publications and Presentations

We describe the Infosphere project, which is building the systems software support for information-driven applications such as digital libraries and electronic commerce. The main technical contribution is the Infopipe abstraction to support information flow with quality of service. Using building blocks such as program specialization, software feedback, domain-specific languages, and personalized information filtering, the Infopipe software generates code and manage resources to provide the specified quality of service with support for composition and restructuring.

Structured Web Databases, Shuang Li

Dissertations and Theses

Recent research has focused on the cooperation of web server and database server software in the deployment of data-intensive web sites. That work has focused either on storing data in a database that can be used to generate the contents of a web site, or on providing interfaces and gateways to enable queries to be invoked from web pages and executed at external database servers.

This thesis describes the implementation of a prototype of the Data Web system that is being implemented at Portland State University. With Data Web, a user can embed in a web page virtual tables that …

Prestructuring Neural Networks Via Extended Dependency Analysis With Application To Pattern Classification, George G. Lendaris, Thaddeus T. Shannon, Martin Zwick

Complex Systems Faculty Publications and Presentations

We consider the problem of matching domain-specific statistical structure to neural-network (NN) architecture. In past work we have considered this problem in the function approximation context; here we consider the pattern classification context. General Systems Methodology tools for finding problem-domain structure suffer exponential scaling of computation with respect to the number of variables considered. Therefore we introduce the use of Extended Dependency Analysis (EDA), which scales only polynomially in the number of variables, for the desired analysis. Based on EDA, we demonstrate a number of NN pre-structuring techniques applicable for building neural classifiers. An example is provided in which EDA …