research – UX Maturity Assessment results

I think NN/G’s model is one of the most comprehensive ones that make sense and cover all the different level. There is a series of articles on that (as someone mentioned in the comments) explaining the 8 stages.

https://www.nngroup.com/articles/ux-maturity-stages-1-4/

https://www.nngroup.com/articles/ux-maturity-stages-5-8/

However more specifically, I participated in one of NN/Gs seminars and they explained at length what the different stages mean and what they entail for a company. They even provided a survey for us participants to fill in that would help us figure out at which level our company’s UX maturity stands. This is probably closest to what you need and would probably help you to define your organisation’s UX maturity (at least by NN/G’s standards).

As an example, according to the survey, Facebook was at stage 8 on that scale.

Beyond that, the main gist was that it takes time to go through the 8 stages, years and decades even, but those time limits can be affected by a ux-centric management presence or someone higher up that is willing to make the switch into a more UX friendly structure.

Unfortunately, I do not have the ability to share that seminar material with you and I cannot seem to find the survey anywhere online.

However you can find multiple sources around the net that give a decent indication. I hope this info is helpful somewhat and can give you a better perspective.

research – Are there any studies of users getting jaded of dialog requests?

Dialog boxes are needed. In the old HCI thinking, a user interface is essentially a dialog between a human, and a computer.

However, handling of the dialog boxes can become habitual. The typical example is Word or any similar document editor: when you close an unsaved document, usually, you don’t want to save it. In those exceptional times when you actually want to save it, you’re prone to click “don’t save” anyway.

Therefore, it is a recommended best practice to avoid opening dialog boxes often. Provide forgiveness instead of asking for confirmation: provide a way so that the user can undo. If you look at document editors on iOS (Pages, or OmniOutliner), they don’t have confirmation dialogs at all, and I guess the Lion version of Pages doesn’t have it either.

Also, the users are sometimes not able to comprehend the situation in question. Like, in this case, I bet an average user doesn’t really know, what “Microsoft Windows Component Publisher” means. There is no meaningful action in this case from the view of the user.

In other cases, the dialog box doesn’t tell the user what can he do, what would be the result of each of the choices, and how would the user benefit from those possible futures. Always provide the right context, and make the options always clear from the users’ perspective.

The users are always trying to achieve a goal. If the goal is to remove an application, they do whatever it takes to remove the application, even if a dialog box tells them it also removes their whole windows installation, publishes their nasty pictures on the internet, and sell their soul on eBay.

Together with this, and the habituality of choosing a default option, it’s rather discouraged to do dialog boxes most of the time.

I’ll grab the studies for you, and edit this answer in a moment, just couldn’t find it at Nielsen (useit.com – albeit I’m sure it’s there), but I have a few UX books lying around here.

Edit: Unfortunately, I didn’t find the usual psychologic journal stuff about this,as this has been a known fact since the eighties, and even writers from the nineties were too lazy to cite these studies correctly.

  • A case study from the Nielsen-Norman group is here
  • General guidelines for error pages from Nielsen is here, and there is a course where they tell you about Dialogue Design
  • Raskin was famously a big enemy of dialog boxes (look at the Canon Cat), and he describes these problems in The Humane Interface, Chapter 2-3: Locus of Attention
    • He also cites Baars, Bernard J. A Cognitive Theory of Consciousness (Cambridge, U.K: Cambridge University Press, 1988) and Card, Stuart K., Thomas P. Moran, and Allen Newell . The Psychology of Human-Computer Interaction (Hillsdale, NJ: Lawrence Erlbaum Associates, 1983), although I have no idea what these writings contain, and I have no access to them
  • Chapter Five of Norman’s classic Design of Everyday Things deals with errors, but it does deal with it in the physical environment, as the whole book tries to use the physical environment as a metaphor for the virtual one.
  • Jeff Johnson talks about interface issues in Designing with the Mind in Mind, for example in Chapter 6, _Pop-up message in error dialog box”, but he doesn’t tell about habits.

I could also quote the Apple Human Interface Guidelines (or iOS guidelines) and perhaps also the Windows Interface Guidelines, but they are about practical issues. Also I grabbed two other UX books and I could grab a 90s edition of SEPA (Software Engineering: A Practitioners’ Approach), where I remember there was the 10 commandment of user interfaces, that was an often-quoted UI rule-of-thumb guideline, but I don’t think I’d find its reference.

All in all, it seems this is something that we understood for 30 years, and everyone is just too lazy to back up their claim. Perhaps it is this way because everyone knows from their private life how easy is to make such mistakes, and it is the most easily tested thing in experimental settings.

As for what to do instead of error boxes, read Raskins’ book, or Norman’s book. As for looking at how an alert-less application flow looks like,look at Google Docs or Lion / iOS 5 versions of Pages.

Sorry, I couldn’t find it, it seems even I just remember that this is how it should be done and these are the reasons, but I can’t find in my library where did it actually come from.

python – Downloading and parsing research papers

I am trying to write a script which gets a research paper from a website by calling their API and then traverse it sentence-wise with some conditions.

The paper is accessible in XML format. I am directly using the nltk.sent_tokenize() to break the relevant part of XML document into list of sentences and then searching for “diseases”(number of diseases in my dataframe is 12000) in every sentence using regex and if a match is found then i search for “biomarkers”(this dataframe has 20000 rows and datatype of row is of type list with each list having an average of 2 values i.e. there are more than 40000 values which are to be matched) in the same sentence. And finally the result is saved in database if disease and biomarker are found in the same sentence.

In the worst case steps taken to accomplish the task would be 900.000(papers which are to be traversed)*15(number of sentences in each paper)*12.000(number of disease which are to be searched)*40.000(number of marker which are to be searched).

At the moment the code is parsing 60-70 papers in an hour which is a bit too slow.

The following is the code which I have tried. I am searching for the existing bottlenecks in my code. Any suggestions to optimise the code would be highly appreciated.

import timeit
import mysql.connector
from urllib.request import urlopen
import urllib.request
import xml.dom.minidom
import xml.etree.ElementTree as ET
import requests
import xml
import lxml.etree
from lxml import etree
import re
import math
import nltk 
import pandas as pd

start = timeit.default_timer()
print("start_time:", start)
mydb = mysql.connector.connect(host="localhost",user="root",password="",database="biomarker")
mycursor = mydb.cursor() 
mycursor.execute("DROP TABLE  IF EXISTS papers_sentence_com_ppr")
mycursor.execute("create table papers_sentence_com_ppr (id INT AUTO_INCREMENT PRIMARY KEY, paper_id VARCHAR(255), marker VARCHAR(255),marker_id VARCHAR(255), disease_name VARCHAR(255),AUTHORS  TEXT, sentence  TEXT)")
mycursor.execute("ALTER TABLE biomarker.papers_sentence_com_ppr CONVERT TO CHARACTER SET utf8")
#mycursor.execute("create table papers (id INT AUTO_INCREMENT PRIMARY KEY, paper_id VARCHAR(255), count VARCHAR(255),disease_name VARCHAR(255))")
df1 = pd.read_sql_query("select name from biomarker.disease2", mydb)

df = pd.read_sql_query("select * from biomarker.table_35", mydb)
print(df1)

biomarker_txt = df.at(2,'CA')
biomarker = biomarker_txt.split(" ")
print(len(biomarker))
#mycursor.execute("create table papers (id INT AUTO_INCREMENT PRIMARY KEY, paper_id VARCHAR(255), count VARCHAR(255),disease_name VARCHAR(255))")



urla='https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=(%22biomarker%22%20OR%20%22biomarkers%22%20OR%20%22biological%20marker%22%20OR%20%22biological%20markers%22)%20%20AND%20%20(LANG%3A%22eng%22%20OR%20LANG%3A%22en%22%20OR%20LANG%3A%22us%22)%20AND%20%20(HAS_ABSTRACT%3Ay)%20%20AND%20%20(SRC%3A%22PPR%22)&resultType=idlist&pageSize=1000&format=xml'
urlb='https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=(%22biomarker%22%20OR%20%22biomarkers%22%20OR%20%22biological%20marker%22%20OR%20%22biological%20markers%22)%20%20AND%20%20(LANG%3A%22eng%22%20OR%20LANG%3A%22en%22%20OR%20LANG%3A%22us%22)%20AND%20%20(HAS_ABSTRACT%3Ay)%20%20AND%20%20(SRC%3A%22PPR%22)&resultType=idlist&pageSize=1000&format=xml'


array1 = ()
re1=requests.get(urla)
root = ET.fromstring(re1.content)
for hitCount in root.iter('hitCount'):
    hit_count=int(hitCount.text)
result_value=hit_count
hit_count1=hit_count/1000
hit_count=math.ceil(hit_count1)

hit_count=10




counter1=0
counter3=0
y=0
i=1


for x in range(hit_count):
    
    re1=requests.get(urla)
    root1 = ET.fromstring(re1.content)
    
    for id in root1.iter('id'):
        id_text=id.text
       
        array1.append(id.text)
    for nextCursorMark in root1.iter('nextCursorMark'):
       
        counter3=counter3+1
        print(counter3)
        urla=urlb
        urla =urla+"&cursorMark="+nextCursorMark.text







for i in range(result_value):# will run 900.000 times for 900.000 papers
    print("paper no:", i,)
    paper_id=(array1(i)) #array1 contains list of paper ids
    print("paper_id:", paper_id)       
    make_url= 'https://www.ebi.ac.uk/europepmc/webservices/rest/search?query=ext_id:'+paper_id+'&resultType=core&format=xml'
    re2=requests.get(make_url)
    root2 = ET.fromstring(re2.content)
    for abstractText in root2.iter('abstractText'):
           
            abstract_text_without_tags= re.sub(r"<(^>)*>"," ",abstractText.text )#extract the relevant xml part
            
           
            
            
            nltk_tokens = nltk.sent_tokenize(abstract_text_without_tags)#break the text into sentences
            
            for text in range(len(nltk_tokens)):#depends on the length of text
                    
                    for zz in range(len(df)):#df has 20.000 rows
                        biomarker_txt=((df.at(zz,'CA'))) 
                        biomarker = biomarker_txt.split(" ")# a cell could have more than value which are separated by an space
                        for tt in range(len(biomarker)):
                            if len(biomarker(tt))>2:
                                matches_for_marker = re.findall(rf"b{re.escape(biomarker(tt))}b", nltk_tokens(text))
                                if len(matches_for_marker)!=0:
                                    for y in range(len(df1)):
                                        disease_name=(df1.at(y,'name'))
                                        
                                        regex_for_dis = rf"b{disease_name}b"
                                        
                        
                                        matches_for_dis= re.findall(regex_for_dis, nltk_tokens(text), re.IGNORECASE | re.MULTILINE)
                                        #matches_for_dis = (re.findall(rf"b{(df1.at(y,'name'))}b", nltk_tokens(text), re.IGNORECASE | re.MULTILINE) for y in  range(len(df1)))
                       
                                        
                                        if len(matches_for_dis)!=0:
                                            
                            
                                            for firstPublicationDate in root2.iter('firstPublicationDate'):
                                                firstPublicationDate=firstPublicationDate.text
                                            for authorString in root2.iter('authorString'):
                                                counter1=counter1+1
                                            
                                            mycursor.execute("insert into papers_sentence_com_ppr (id, paper_id,firstPublicationDate, marker,marker_id, disease_name, AUTHORS, sentence) values (%s,%s,%s, %s, %s,%s, %s,%s)", (counter1, paper_id,firstPublicationDate, biomarker(tt),(df.at(zz,'Entry')), (df1.at(y,'name')), authorString.text, nltk_tokens(text)))
                                            #print("***********************************************************DATABASE_ENTRY*************************************************************n")
                                            mydb.commit()






```

research – How to conduct a design / UX workshop with an in-house team?

I’m looking for ideas for conducting a quick, valuable design workshop (max a few hours). Only people who are involved in building the related digital product will participate (including me, also part of the team).

The goal is to identify critical UX issues, mostly by looking at the UI, and improve the overall look and feel of the product in the future.

I’m aware of the limitations we have in evaluating product due to every-day contact and co-creation. I’m looking for exercise which helps us to see the product and its problems in a fresh way, break our mental models (is this even possible?). Bring out voices that are hidden every day, too.
Any ideas, resources, case studies?

research – How to conduct a design / UX audit with an in-house team?

I’m looking for ideas for conducting a quick, valuable design audit (max few hours). Only people who are involved in building the related digital product will participate (including me, also part of the team). The goal is to identify critical UX issues, mostly by looking at the UI, and improve the overall look and feel of the product in the future. Any ideas, resources, case studies)?

research – How to conduct an design / ux audit with the in-house team?

I’m looking for ideas for conducting a quick, valuable design audit (max few hours). Only people who are involved in building this digital product will participate (including me, also part of the team). The goal is to identify critical UX issues, mostly by looking at the UI, and improve the overall look and feel of the product in the future. Any ideas, resources, case studies 🙂 ?

I will be your Reliable virtual assistant for any data entry and keyword research for $20

I will be your Reliable virtual assistant for any data entry and keyword research

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  • Scanned Image to Word/ Excel
  • PDF to Excel or Word
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Looking for writer to write high quality Law book reviews based on research.

Hello,

I’m looking for a high quality writer who can write high quality book reviews about Law related books based on research and reading other reviews (from Google search, Amazon, Barnes & Novel, Google Books etc…).
SEMrush

Requirements:

  • High English level & writing skills – must!
  • Books enthusiastic – must!
  • Law education/knowledge/enthusiasm – must!
  • Former experience with book reviews – advantage!

If you think you are capable, please contact me with more details and why you think you’re suitable for the job.