Begin by setting up your Kafka environment. Download Apache Kafka from the official website and extract the files. Ensure you have Java installed on your system as Kafka is a Java-based application. Start the Zookeeper server using the command `bin/zookeeper-server-start.sh config/zookeeper.properties`, then start the Kafka server using `bin/kafka-server-start.sh config/server.properties`.

Before sending data to Kafka, you need to create a topic where your CSV data will be published. Use the command `bin/kafka-topics.sh --create --topic --bootstrap-server localhost:9092 --partitions 1 --replication-factor 1` to create a topic. Replace `` with a suitable name for your topic.

Ensure your CSV file is properly formatted and accessible. Each row in your CSV should represent a single record, and columns should be separated by commas. Open the CSV to verify consistency and correctness in the data types and values.

Write a script in your preferred programming language (such as Python) to read data from the CSV file. Use libraries like `csv` in Python to open and parse the CSV file. Create a function that reads each row and prepares it for sending to Kafka.

```python
import csv

def read_csv(file_path):
with open(file_path, mode='r') as file:
csv_reader = csv.reader(file)
for row in csv_reader:
yield row
```

Use a Kafka client library to send data to Kafka. In Python, you can use `kafka-python`. Install it using `pip install kafka-python`. Create a producer in your script to send each row of data to the Kafka topic established earlier.

```python
from kafka import KafkaProducer
import json

producer = KafkaProducer(bootstrap_servers='localhost:9092',
value_serializer=lambda v: json.dumps(v).encode('utf-8'))

for record in read_csv('path_to_your_csv.csv'):
producer.send('', value=record)
producer.flush()
```

After sending data, verify that it has been successfully published to the Kafka topic. Use the Kafka console consumer to read messages from your topic and ensure your data is correctly published. Run the command `bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic --from-beginning`.

Implement error handling and logging within your script to manage any issues that may arise during data processing. This includes handling exceptions during CSV reading, connectivity issues with Kafka, and unsuccessful data publication attempts. Use try-except blocks and logging libraries to ensure robust error handling and logging.

```python
import logging

logging.basicConfig(level=logging.INFO)

try:
for record in read_csv('path_to_your_csv.csv'):
producer.send('', value=record)
except Exception as e:
logging.error(f"An error occurred: {e}")
finally:
producer.flush()
producer.close()
```

This guide offers a direct and practical approach to moving data from a CSV file to Kafka without relying on third-party connectors or integrations, utilizing basic scripts and Kafka’s native capabilities.