Big Data, Big Challenges : A Healthcare Perspective : Background, Issues, Solutions and Research Directions
https://libcat.nshealth.ca/en/permalink/provcat44173
Mowafa Househ, Andre W. Kushniruk, Elizabeth M. Borycki, editors.
--Cham:
Springer
, 2019.
- Available Online
- View e-Book
- Location
- Online
This is the first book offering a comprehensive, yet concise, view on both the challenges and opportunities related to the use of big data in health care. The different chapters report on different perspectives: from health management to patient safety; from the human factor perspective to the ethical and economic ones, and more. By providing a historical background on the use of big data, and critically analyzing current approaches together with issues and challenges related to their applicati…
- Available Online
- View e-Book
- Other Authors
- Househ, Mowafa
- Kushniruk, Andre W.
- Borycki, Elizabeth M.
- Responsibility
- Mowafa Househ, Andre W. Kushniruk, Elizabeth M. Borycki, editors
- Place of Publication
- Cham
- Publisher
- Springer
- Date of Publication
- 2019
- Physical Description
- 1 online resource (viii, 144 p.)
- Series
- Lecture Notes in Bioengineering
- Series Title
- Lecture notes in bioengineering
- ISBN
- 9783030061098
- 9783030061081 (Print ed.)
- 9783030061104 (Print ed.)
- ISSN
- 2195-271X
- Subjects (MeSH)
- Data Analysis
- Data Mining
- Medical Informatics - trends
- Abstract
- This is the first book offering a comprehensive, yet concise, view on both the challenges and opportunities related to the use of big data in health care. The different chapters report on different perspectives: from health management to patient safety; from the human factor perspective to the ethical and economic ones, and more. By providing a historical background on the use of big data, and critically analyzing current approaches together with issues and challenges related to their applications, the work presented not only sheds light on the problems of big data, but also paves the way for possible solutions and future research directions. The book offers a useful reference guide to health information technology professionals, healthcare managers, healthcare practitioners, and patients alike, helping them in their decision making processes, as well as to students and academicians learning or dealing with data science related research issues in healthcare.
- Format
- e-Book
- Location
- Online
Big Data-Enabled Nursing : Education, Research and Practice
https://libcat.nshealth.ca/en/permalink/provcat41716
Connie W. Delaney, Charlotte A. Weaver, Judith J. Warren, Thomas R. Clancy, Roy L. Simpson, editors.
--Cham:
Springer
, 2017.
- Available Online
- View e-Book
- Location
- Online
This text reflects how the learning health system infrastructure is maturing and being advanced by health information exchanges (HIEs) with multiple organizations blending their data or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. Historically, nursing, in all of its missions of researc…
- Available Online
- View e-Book
- Other Authors
- Delaney, Connie W
- Weaver, Charlotte A
- Warren, Judith J
- Clancy, Thomas R
- Simpson, Roy L
- Responsibility
- Connie W. Delaney, Charlotte A. Weaver, Judith J. Warren, Thomas R. Clancy, Roy L. Simpson, editors
- Place of Publication
- Cham
- Publisher
- Springer
- Date of Publication
- 2017
- Physical Description
- 1 online resource (xxxv, 488 pages) : 61 illus., 48 illus. in color
- Series Title
- Health informatics
- ISBN
- 9783319533001
- 9783319532998 (print ed.)
- ISSN
- 1431-1917
- Subjects (MeSH)
- Data Mining
- Nursing Informatics - trends
- Abstract
- This text reflects how the learning health system infrastructure is maturing and being advanced by health information exchanges (HIEs) with multiple organizations blending their data or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing has consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Big Data-Enabled Nursing reflects on how health systems have developed and how electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. It provides instruction on the new opportunities for nursing and educates readers on the new skills in research methodologies that are being further enabled by new partnerships spanning all sectors.
- Contents
- Part I. The New and Exciting World of “Big Data” -- 1. Why Big Data?: Why Nursing? -- 2. Big Data in Healthcare: A Wide Look at a Broad Subject -- 3. A Big Data Primer -- Part II. Technologies and Science of Big Data -- 4. A Closer Look at Enabling Technologies and Knowledge Value -- 5. Big Data in Healthcare: New Methods of Analysis -- 6. Generating the Data for Analyzing the Effects of Interprofessional Teams for Improving Triple Aim Outcomes -- 7. Wrestling with Big Data: How Nurse Leaders Can Engage -- 8. Inclusion of Flowsheets from Electronic Health Records to Extend Data for Clinical and Translational Science Awards (CTSA) Research -- 9. Working in the New Big Data World: Academic/Corporate Partnership Model -- Part III. Revolution of Knowledge Discovery, Dissemination, Translation Through Data Science -- 10. Data Science: Transformation of Research and Scholarship -- 11. Answering Research Questions with National Clinical Research Networks -- 12. Enhancing Data Access and Utilization: Federal Big Data Initiative and Relevance to Health Disparities Research -- 13. Big Data Impact on Transformation of Healthcare Systems -- 14. State of the Science in Big Data Analytics -- Part IV. Looking at Today and the Near Future -- 15. Big Data Analytics Using the VA’s ‘VINCI’ Database to Look at Delirium -- 16. Leveraging the Power of Interprofessional EHR Data to Prevent Delirium: The Kaiser Permanente Story -- 17. Mobilizing the Nursing Workforce with Data and Analytics at the Point of Care -- 18. The Power of Disparate Data Sources for Answering Thorny Questions in Healthcare: Four Case Studies -- Part V. A Call for Readiness -- 19. What Big Data and Data Science Mean for Schools of Nursing and Academia -- 20. Quality Outcomes and Credentialing: Implication for Informatics and Big Data Science -- 21. Big Data Science and Doctoral Education in Nursing -- 22. Global Society & Big Data: Here’s the Future We Can Get Ready For -- 23. Big-Data Enabled Nursing: Future Possibilities.
- Format
- e-Book
- Location
- Online
Big Data in Healthcare : Extracting Knowledge from Point-of-Care Machines
https://libcat.nshealth.ca/en/permalink/provcat41863
Pouria Amirian, Trudie Lang, Francois van Loggerenberg, editors.
--Cham:
Springer
, 2017.
- Available Online
- View e-Book
- Location
- Online
This book reviews a number of issues including: Why data generated from POC machines are considered as Big Data. What are the challenges in storing, managing, extracting knowledge from data from POC devices? Why is it inefficient to use traditional data analysis with big data? What are the solutions for the mentioned issues and challenges? What type of analytics skills are required in health care? What big data technologies and tools can be used efficiently with data generated from POC devices?…
- Available Online
- View e-Book
- Other Authors
- Amirian, Pouria
- Lang, Trudie
- van Loggerenberg, Francois
- Responsibility
- Pouria Amirian, Trudie Lang, Francois van Loggerenberg, editors
- Place of Publication
- Cham
- Publisher
- Springer
- Date of Publication
- 2017
- Physical Description
- 1 online resource (vii, 100 pages) : 46 illus., 45 illus. in color
- ISBN
- 9783319629902
- 9783319629889 (print ed.)
- ISSN
- 1864-8118
- Subjects (MeSH)
- Data Mining
- Health Planning
- Internet
- Medical Informatics
- Point-of-Care Systems
- Telemedicine
- Telemetry
- Abstract
- This book reviews a number of issues including: Why data generated from POC machines are considered as Big Data. What are the challenges in storing, managing, extracting knowledge from data from POC devices? Why is it inefficient to use traditional data analysis with big data? What are the solutions for the mentioned issues and challenges? What type of analytics skills are required in health care? What big data technologies and tools can be used efficiently with data generated from POC devices? This book shows how it is feasible to store vast numbers of anonymous data and ask highly specific questions that can be performed in real-time to give precise and meaningful evidence to guide public health policy.
- Contents
- Introduction: Improving Healthcare with Big Data -- Data Science and Analytics -- Big Data and Big Data Technologies -- Big Data Analytics for Extracting Disease Surveillance Information: An Untapped Opportunity -- Ebola and Twitter. What Insights Can Public Health Draw from Social Media?
- Format
- e-Book
- Location
- Online
Bisociative Knowledge Discovery : An Introduction to Concept, Algorithms, Tools, and Applications
https://libcat.nshealth.ca/en/permalink/provcat43947
Michael R. Berthold (ed.).
--Heidelberg:
Springer
, c2012.
- Available Online
- View e-Book
- Access
- Open access
- Location
- Online
Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied originates from one domain. The focus of this book, and the BISON project from which the contributions originate, is a network-based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information…
- Available Online
- View e-Book
- Other Authors
- Berthold, Michael R.
- Responsibility
- Michael R. Berthold (ed.)
- Place of Publication
- Heidelberg
- Publisher
- Springer
- Date of Publication
- c2012
- Physical Description
- 1 online resource (x, 486 p.) : 146 illus.
- Series
- Lecture Notes in Artificial Intelligence
- Series Vol.
- 7250
- Series Title
- Lecture notes in computer science. Lecture notes in artificial intelligence
- LNCS sublibrary. SL 7, Artificial intelligence
- ISBN
- 9783642318306
- 9783642318313 (Print ed.)
- 9783642318290 (Print ed.)
- Subjects (MeSH)
- Data Mining
- Informatics - methods
- Pattern Recognition, Automated
- Specialty
- Medical Informatics
- Abstract
- Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied originates from one domain. The focus of this book, and the BISON project from which the contributions originate, is a network-based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of seeking well-defined global or local patterns, the aim was to find domain-bridging associations. These are particularly interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art survey, together with a detailed introduction to the book, are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.
- Contents
- Part I: Bisociation -- Towards Bisociative Knowledge Discovery -- Towards Creative Information Exploration Based on Koestler’s Concept of Bisociation -- From Information Networks to Bisociative Information Networks -- Part II: Representation and Network Creation -- Network Creation: Overview -- Selecting the Links in BisoNets Generated from Document Collections -- Bridging Concept Identification for Constructing Information Networks from Text Documents -- Discovery of Novel Term Associations in a Document Collection -- Cover Similarity Based Item Set Mining -- Patterns and Logic for Reasoning with Networks -- Part III: Network Analysis -- Network Analysis: Overview -- BiQL: A Query Language for Analyzing Information Networks -- Review of BisoNet Abstraction Techniques -- Simplification of Networks by Edge Pruning -- Network Compression by Node and Edge Mergers -- Finding Representative Nodes in Probabilistic Graphs -- (Missing) Concept Discovery in Heterogeneous Information Networks -- Node Similarities from Spreading Activation -- Towards Discovery of Subgraph Bisociations -- Part IV: Exploration -- Exploration: Overview -- Data Exploration for Bisociative Knowledge Discovery: A Brief Overview of Tools and Evaluation Methods -- On the Integration of Graph Exploration and Data Analysis: The Creative Exploration Toolkit -- Bisociative Knowledge Discovery by Literature Outlier Detection -- Exploring the Power of Outliers for Cross-Domain Literature Mining -- Bisociative Literature Mining by Ensemble Heuristics -- Part V: Applications and Evaluation -- Applications and Evaluation: Overview -- Biomine: A Network-Structured Resource of Biological Entities for Link Prediction -- Semantic Subgroup Discovery and Cross-Context Linking for Microarray Data Analysis -- Contrast Mining from Interesting Subgroups -- Link and Node Prediction in Metabolic Networks with Probabilistic Logic -- Modelling a Biological System: Network Creation by Triplet Extraction from Biological Literature -- Bisociative Exploration of Biological and Financial Literature Using Clustering -- Bisociative Discovery in Business Process Models -- Bisociative Music Discovery and Recommendation.
- Access
- Open access
- Format
- e-Book
- Location
- Online
Clinical Text Mining : Secondary Use of Electronic Patient Records
https://libcat.nshealth.ca/en/permalink/provcat43946
Hercules Dalianis.
--Cham:
SpringerOpen
, c2018.
- Available Online
- View e-Book
- Access
- Open access
- Location
- Online
This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and descr…
- Available Online
- View e-Book
- Author
- Dalianis, Hercules
- Responsibility
- Hercules Dalianis
- Place of Publication
- Cham
- Publisher
- SpringerOpen
- Date of Publication
- c2018
- Physical Description
- 1 online resource (xvii, 181 p.) : 54 illus., 28 illus. in color
- ISBN
- 9783319785035
- 9783319785028 (Print ed.)
- 9783319785042 (Print ed.)
- 9783030087159 (Print ed.)
- Subjects (MeSH)
- Data Mining
- Electronic Health Records
- Machine Learning
- Health Records, Personal - ethics
- Natural Language Processing
- Specialty
- Medical Informatics
- Abstract
- This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.
- Contents
- 1. Introduction -- 2. The history of the patient record and the paper record -- 3. User needs: clinicians, clinical researchers and hospital management -- 4. Characteristics of patient records and clinical corpora -- 5. Medical classifications and terminologies -- 6. Evaluation metrics and evaluation -- 7. Basic building blocks for clinical text processing -- 8. Computational methods for text analysis and text classification -- 9. Ethics and privacy of patient records for clinical text mining research -- 10. Applications of clinical text mining -- 11. Networks and shared tasks in clinical text mining -- 12. Conclusions and outlook.
- Access
- Open access
- Format
- e-Book
- Location
- Online
Data and Text Processing for Health and Life Sciences
https://libcat.nshealth.ca/en/permalink/provcat43941
Francisco M. Couto.
--Cham:
SpringerOpen
, c2019.
- Available Online
- View e-Book
- Access
- Open access
- Location
- Online
This open access book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and mine literature, and to explore the semantics encoded in biomedical ontologies. To store data this book relies on open standard text fil…
- Available Online
- View e-Book
- Author
- Couto, Francisco M.
- Responsibility
- Francisco M. Couto
- Place of Publication
- Cham
- Publisher
- SpringerOpen
- Date of Publication
- c2019
- Physical Description
- 1 online resource (xv, 98 p.) : 483 illus., 74 illus. in color.
- Series Vol.
- v. 1137
- Series Title
- Advances in experimental medicine and biology
- ISBN
- 9783030138455
- 9783030138448 (Print ed.)
- 9783030138462 (Print ed.)
- ISSN
- 0065-2598
- Subjects (MeSH)
- Biomedical Research - methods
- Data Mining
- Electronic Data Processing
- Medical Informatics - methods
- Specialty
- Medical Informatics
- Abstract
- This open access book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and mine literature, and to explore the semantics encoded in biomedical ontologies. To store data this book relies on open standard text file formats, such as TSV, CSV, XML, and OWL, that can be open by any text editor or spreadsheet application. The first two chapters, Introduction and Resources, provide a brief introduction to the shell scripting and describe popular data resources in Health and Life Sciences. The third chapter, Data Retrieval, starts by introducing a common data processing task that involves multiple data resources. Then, this chapter explains how to automate each step of that task by introducing the required commands line tools one by one. The fourth chapter, Text Processing, shows how to filter and analyze text by using simple string matching techniques and regular expressions. The last chapter, Semantic Processing, shows how XPath queries and shell scripting is able to process complex data, such as the graphs used to specify ontologies. Besides being almost immutable for more than four decades and being available in most of our personal computers, shell scripting is relatively easy to learn by Health and Life specialists as a sequence of independent commands. Comprehending them is like conducting a new laboratory protocol by testing and understanding its procedural steps and variables, and combining their intermediate results. Thus, this book is particularly relevant to Health and Life specialists or students that want to easily learn how to process data and text, and which in return may facilitate and inspire them to acquire deeper bioinformatics skills in the future.
- Contents
- Introduction -- Resources -- Data Retrieval -- Text Processing -- Semantic Processing.
- Access
- Open access
- Format
- e-Book
- Location
- Online
Interactive Process Mining in Healthcare
https://libcat.nshealth.ca/en/permalink/provcat46390
Carlos Fernandez-Llatas, editor.
--Cham:
Springer
, c2021.
- Available Online
- View e-Book
- Access
- NEW Springer 2021
- Location
- Online
This book provides a practically applicable guide to the methodologies and technologies for the application of interactive process mining paradigm. Case studies are presented where this paradigm has been successfully applied in emergency medicine, surgery processes, human behavior modelling, strokes and outpatients’ services, enabling the reader to develop a deep understanding of how to apply process mining technologies in healthcare to support them in inferring new knowledge from past actions,…
- Available Online
- View e-Book
- Other Authors
- Fernandez-Llatas, Carlos
- Responsibility
- Carlos Fernandez-Llatas, editor
- Place of Publication
- Cham
- Publisher
- Springer
- Date of Publication
- c2021
- Physical Description
- 1 online resource (xiv, 306 p.) : 130 illus., 92 illus. in color
- Series Title
- Health informatics
- ISBN
- 9783030539931
- 9783030539924 (Print ed.)
- 9783030539948 (Print ed.)
- 9783030539955 (Print ed.)
- ISSN
- 1431-1917
- Subjects (MeSH)
- Data Mining
- Medical Informatics
- Process Assessment, Health Care
- Abstract
- This book provides a practically applicable guide to the methodologies and technologies for the application of interactive process mining paradigm. Case studies are presented where this paradigm has been successfully applied in emergency medicine, surgery processes, human behavior modelling, strokes and outpatients’ services, enabling the reader to develop a deep understanding of how to apply process mining technologies in healthcare to support them in inferring new knowledge from past actions, and providing accurate and personalized knowledge to improve their future clinical decision-making. Interactive Process Mining in Healthcare comprehensively covers how machine learning algorithms can be utilized to create real scientific evidence to improve daily healthcare protocols, and is a valuable resource for a variety of health professionals seeking to develop new methods to improve their clinical decision-making. .
- Contents
- 1. Interactive Process Mining in Healthcare: An Introduction -- Part I. Basics - 2. Value-Driven Digital Transformation in Health and Medical Care -- 3. Towards a Knowledge and Data-Driven Perspective in Medical Processes -- 4. Process Mining in Healthcare -- 5. Data Quality in Process Mining -- 6. Towards Open Process Models in Healthcare: Open Standards and Legal Considerations -- Part II. Interactive Process Mining in Health -- 7. Applying Interactive Process Mining Paradigm in Healthcare Domain -- 8. Bringing Interactive Process Mining to Health Professionals: Interactive Data Rodeos -- 9. Interactive Process Mining in Practice: Interactive Process Indicators -- Part III. Interactive Process Mining in Action -- 10. Interactive Process Mining in Emergencies -- 11. Interactive Process Mining in Surgery with Real Time Location Systems: Interactive Trace Correction -- 12. Interactive Process Mining in Type 2 Diabetes Mellitus -- 13. Interactive Process Mining in IoT and Human Behaviour Modelling -- 14. Interactive Process Mining for Medical Training -- 15. Interactive Process Mining for Discovering Dynamic Risk Models in Chronic Diseases -- 16. Interactive Process Mining-Induced Change Management Methodology for Healthcare -- 17. Interactive Process Mining Challenges.
- Access
- NEW Springer 2021
- Format
- e-Book
- Location
- Online
Linked Open Data : Creating Knowledge Out of Interlinked Data : Results of the LOD2 Project
https://libcat.nshealth.ca/en/permalink/provcat43948
Sören Auer, Volha Bryl, Sebastian Tramp (eds.).
--Cham:
Springer
, c2014.
- Available Online
- View e-Book
- Access
- Open access
- Location
- Online
Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised le…
- Available Online
- View e-Book
- Other Authors
- Auer, Sören
- Bryl, Volha
- Tramp, Sebastian
- Responsibility
- Sören Auer, Volha Bryl, Sebastian Tramp (eds.)
- Place of Publication
- Cham
- Publisher
- Springer
- Date of Publication
- c2014
- Physical Description
- 1 online resource (vii, 215 p.) : 73 illus.
- Series
- Information Systems and Applications, incl. Internet/Web, and HCI
- Series Vol.
- 8661
- Series Title
- LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI
- Lecture notes in computer science
- ISBN
- 9783319098463
- 9783319098470 (Print ed.)
- 9783319098456 (Print ed.)
- Subjects (MeSH)
- Data Mining
- Informatics - methods
- Semantic Web
- Specialty
- Medical Informatics
- Abstract
- Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea. The aim of this project was to advance the state-of-the-art in research and development in four key areas relevant for Linked Data, namely 1. RDF data management; 2. the extraction, creation, and enrichment of structured RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.
- Contents
- 1. Introduction to LOD2 -- Technology -- 2. Advances in Large-Scale RDF Data Management -- 3. Knowledge Base Creation, Enrichment and Repair -- 4. Interlinking and Knowledge Fusion -- 5. Facilitating the Exploration and Visualization of Linked Data -- 6. Supporting the Linked Data Life Cycle Using an Integrated Tool Stack -- Use Cases -- 7. LOD2 for Media and Publishing -- 8. Building Enterprise Ready Applications Using Linked Open Data -- 9. Lifting Open Data Portals to the Data Web -- 10. Linked Open Data for Public Procurement.
- Access
- Open access
- Format
- e-Book
- Location
- Online
Web analytics strategies for information professionals : a LITA guide
https://libcat.nshealth.ca/en/permalink/provcat26024
Tabatha Farney and Nina McHale.
--Chicago, IL:
ALA TechSource
, 2013.
- Call Number
- Z 674.75 .W67 F235w 2013
- Location
- Dickson Building
- Call Number
- Z 674.75 .W67 F235w 2013
- Author
- Farney, Tabatha
- Corporate Author
- Library and Information Technology Association (U.S.)
- Other Authors
- McHale, Nina
- Responsibility
- Tabatha Farney and Nina McHale
- Place of Publication
- Chicago, IL
- Publisher
- ALA TechSource
- Date of Publication
- 2013
- Physical Description
- 224 p.
- Series Title
- LITA guides
- ISBN
- 9781555708979
- Subjects (MeSH)
- Libraries, Digital - organization & administration
- Management Information Systems
- Data Mining
- Data Interpretation, Statistical
- Internet
- Format
- Book
- Location
- Dickson Building
- Loan Period
- 3 weeks
